WorldWideScience

Sample records for data-enabled research experiences

  1. Informatics methods to enable sharing of quantitative imaging research data.

    Science.gov (United States)

    Levy, Mia A; Freymann, John B; Kirby, Justin S; Fedorov, Andriy; Fennessy, Fiona M; Eschrich, Steven A; Berglund, Anders E; Fenstermacher, David A; Tan, Yongqiang; Guo, Xiaotao; Casavant, Thomas L; Brown, Bartley J; Braun, Terry A; Dekker, Andre; Roelofs, Erik; Mountz, James M; Boada, Fernando; Laymon, Charles; Oborski, Matt; Rubin, Daniel L

    2012-11-01

    The National Cancer Institute Quantitative Research Network (QIN) is a collaborative research network whose goal is to share data, algorithms and research tools to accelerate quantitative imaging research. A challenge is the variability in tools and analysis platforms used in quantitative imaging. Our goal was to understand the extent of this variation and to develop an approach to enable sharing data and to promote reuse of quantitative imaging data in the community. We performed a survey of the current tools in use by the QIN member sites for representation and storage of their QIN research data including images, image meta-data and clinical data. We identified existing systems and standards for data sharing and their gaps for the QIN use case. We then proposed a system architecture to enable data sharing and collaborative experimentation within the QIN. There are a variety of tools currently used by each QIN institution. We developed a general information system architecture to support the QIN goals. We also describe the remaining architecture gaps we are developing to enable members to share research images and image meta-data across the network. As a research network, the QIN will stimulate quantitative imaging research by pooling data, algorithms and research tools. However, there are gaps in current functional requirements that will need to be met by future informatics development. Special attention must be given to the technical requirements needed to translate these methods into the clinical research workflow to enable validation and qualification of these novel imaging biomarkers. Copyright © 2012 Elsevier Inc. All rights reserved.

  2. Research Data Reusability: Conceptual Foundations, Barriers and Enabling Technologies

    Directory of Open Access Journals (Sweden)

    Costantino Thanos

    2017-01-01

    Full Text Available High-throughput scientific instruments are generating massive amounts of data. Today, one of the main challenges faced by researchers is to make the best use of the world’s growing wealth of data. Data (reusability is becoming a distinct characteristic of modern scientific practice. By data (reusability, we mean the ease of using data for legitimate scientific research by one or more communities of research (consumer communities that is produced by other communities of research (producer communities. Data (reusability allows the reanalysis of evidence, reproduction and verification of results, minimizing duplication of effort, and building on the work of others. It has four main dimensions: policy, legal, economic and technological. The paper addresses the technological dimension of data reusability. The conceptual foundations of data reuse as well as the barriers that hamper data reuse are presented and discussed. The data publication process is proposed as a bridge between the data author and user and the relevant technologies enabling this process are presented.

  3. Long-Lived Digital Data Collections Enabling Research and Education in the 21st Century

    Science.gov (United States)

    2005-09-01

    Collections: Enabling Research and Education in the 21st Century40 LoNG-LiVED DiGiTAL DATA CoLLECTioNS AND LARGE FACiLiTiES Workshop participants drew...Long-Lived Digital Data Collections: Enabling Research and Education in the 21st Century NSB-05-40 Report Documentation Page Form...COVERED - 4. TITLE AND SUBTITLE Long-Lived Digital Data Collections Enabling Research and Education in the 21st Century 5a. CONTRACT NUMBER 5b

  4. BioenergyKDF: Enabling Spatiotemporal Data Synthesis and Research Collaboration

    Energy Technology Data Exchange (ETDEWEB)

    Myers, Aaron T [ORNL; Movva, Sunil [ORNL; Karthik, Rajasekar [ORNL; Bhaduri, Budhendra L [ORNL; White, Devin A [ORNL; Thomas, Neil [ORNL; Chase, Adrian S Z [ORNL

    2014-01-01

    The Bioenergy Knowledge Discovery Framework (BioenergyKDF) is a scalable, web-based collaborative environment for scientists working on bioenergy related research in which the connections between data, literature, and models can be explored and more clearly understood. The fully-operational and deployed system, built on multiple open source libraries and architectures, stores contributions from the community of practice and makes them easy to find, but that is just its base functionality. The BioenergyKDF provides a national spatiotemporal decision support capability that enables data sharing, analysis, modeling, and visualization as well as fosters the development and management of the U.S. bioenergy infrastructure, which is an essential component of the national energy infrastructure. The BioenergyKDF is built on a flexible, customizable platform that can be extended to support the requirements of any user community especially those that work with spatiotemporal data. While there are several community data-sharing software platforms available, some developed and distributed by national governments, none of them have the full suite of capabilities available in BioenergyKDF. For example, this component-based platform and database independent architecture allows it to be quickly deployed to existing infrastructure and to connect to existing data repositories (spatial or otherwise). As new data, analysis, and features are added; the BioenergyKDF will help lead research and support decisions concerning bioenergy into the future, but will also enable the development and growth of additional communities of practice both inside and outside of the Department of Energy. These communities will be able to leverage the substantial investment the agency has made in the KDF platform to quickly stand up systems that are customized to their data and research needs.

  5. Enabling Self-Monitoring Data Exchange in Participatory Medicine.

    Science.gov (United States)

    Lopez-Campos, Guillermo; Ofoghi, Bahadorreza; Martin-Sanchez, Fernando

    2015-01-01

    The development of new methods, devices and apps for self-monitoring have enabled the extension of the application of these approaches for consumer health and research purposes. The increase in the number and variety of devices has generated a complex scenario where reporting guidelines and data exchange formats will be needed to ensure the quality of the information and the reproducibility of results of the experiments. Based on the Minimal Information for Self Monitoring Experiments (MISME) reporting guideline we have developed an XML format (MISME-ML) to facilitate data exchange for self monitoring experiments. We have also developed a sample instance to illustrate the concept and a Java MISME-ML validation tool. The implementation and adoption of these tools should contribute to the consolidation of a set of methods that ensure the reproducibility of self monitoring experiments for research purposes.

  6. Enabling cross-disciplinary research by linking data to Open Access publications

    Science.gov (United States)

    Rettberg, N.

    2012-04-01

    OpenAIREplus focuses on the linking of research data to associated publications. The interlinking of research objects has implications for optimising the research process, allowing the sharing, enrichment and reuse of data, and ultimately serving to make open data an essential part of first class research. The growing call for more concrete data management and sharing plans, apparent at funder and national level, is complemented by the increasing support for a scientific infrastructure that supports the seamless access to a range of research materials. This paper will describe the recently launched OpenAIREplus and will detail how it plans to achieve its goals of developing an Open Access participatory infrastructure for scientific information. OpenAIREplus extends the current collaborative OpenAIRE project, which provides European researchers with a service network for the deposit of peer-reviewed FP7 grant-funded Open Access publications. This new project will focus on opening up the infrastructure to data sources from subject-specific communities to provide metadata about research data and publications, facilitating the linking between these objects. The ability to link within a publication out to a citable database, or other research data material, is fairly innovative and this project will enable users to search, browse, view, and create relationships between different information objects. In this regard, OpenAIREplus will build on prototypes of so-called "Enhanced Publications", originally conceived in the DRIVER-II project. OpenAIREplus recognizes the importance of representing the context of publications and datasets, thus linking to resources about the authors, their affiliation, location, project data and funding. The project will explore how links between text-based publications and research data are managed in different scientific fields. This complements a previous study in OpenAIRE on current disciplinary practices and future needs for infrastructural

  7. The Microgravity Research Experiments (MICREX) Data Base

    Science.gov (United States)

    Winter, C. A.; Jones, J. C.

    1996-01-01

    An electronic data base identifying over 800 fluids and materials processing experiments performed in a low-gravity environment has been created at NASA Marshall Space Flight Center. The compilation, called MICREX (MICrogravity Research Experiments) was designed to document all such experimental efforts performed (1) on U.S. manned space vehicles, (2) on payloads deployed from U.S. manned space vehicles, and (3) on all domestic and international sounding rockets (excluding those of China and the former U.S.S.R.). Data available on most experiments include (1) principal and co-investigator (2) low-gravity mission, (3) processing facility, (4) experimental objectives and results, (5) identifying key words, (6) sample materials, (7) applications of the processed materials/research area, (8) experiment descriptive publications, and (9) contacts for more information concerning the experiment. This technical memorandum (1) summarizes the historical interest in reduced-gravity fluid dynamics, (2) describes the importance of a low-gravity fluids and materials processing data base, (4) describes thE MICREX data base format and computational World Wide Web access procedures, and (5) documents (in hard-copy form) the descriptions of the first 600 fluids and materials processing experiments entered into MICREX.

  8. Enabling Long-Term Earth Science Research: Changing Data Practices (Invited)

    Science.gov (United States)

    Baker, K. S.

    2013-12-01

    Data stewardship plans are shaped by our shared experiences. As a result, community engagement and collaborative activities are central to the stewardship of data. Since modes and mechanisms of engagement have changed, we benefit from asking anew: ';Who are the communities?' and ';What are the lessons learned?'. Data stewardship with its long-term care perspective, is enriched by reflection on community experience. This presentation draws on data management issues and strategies originating from within long-term research communities as well as on recent studies informed by library and information science. Ethnographic case studies that capture project activities and histories are presented as resources for comparative analysis. Agency requirements and funding opportunities are stimulating collaborative endeavors focused on data re-use and archiving. Research groups including earth scientists, information professionals, and data systems designers are recognizing the possibilities for new ways of thinking about data in the digital arena. Together, these groups are re-conceptualizing and reconfiguring for data management and data curation. A differentiation between managing data for local use and production of data for re-use remotely in locations and fields remote from the data origin is just one example of the concepts emerging to facilitate development of data management. While earth scientists as data generators have the responsibility to plan new workflows and documentation practices, data and information specialists have responsibility to promote best practices as well as to facilitate the development of community resources such as controlled vocabularies and data dictionaries. With data-centric activities and changing data practices, the potential for creating dynamic community information environments in conjunction with development of data facilities exists but remains elusive.

  9. The GEOSS solution for enabling data interoperability and integrative research.

    Science.gov (United States)

    Nativi, Stefano; Mazzetti, Paolo; Craglia, Max; Pirrone, Nicola

    2014-03-01

    Global sustainability research requires an integrative research effort underpinned by digital infrastructures (systems) able to harness data and heterogeneous information across disciplines. Digital data and information sharing across systems and applications is achieved by implementing interoperability: a property of a product or system to work with other products or systems, present or future. There are at least three main interoperability challenges a digital infrastructure must address: technological, semantic, and organizational. In recent years, important international programs and initiatives are focusing on such an ambitious objective. This manuscript presents and combines the studies and the experiences carried out by three relevant projects, focusing on the heavy metal domain: Global Mercury Observation System, Global Earth Observation System of Systems (GEOSS), and INSPIRE. This research work recognized a valuable interoperability service bus (i.e., a set of standards models, interfaces, and good practices) proposed to characterize the integrative research cyber-infrastructure of the heavy metal research community. In the paper, the GEOSS common infrastructure is discussed implementing a multidisciplinary and participatory research infrastructure, introducing a possible roadmap for the heavy metal pollution research community to join GEOSS as a new Group on Earth Observation community of practice and develop a research infrastructure for carrying out integrative research in its specific domain.

  10. Enabling systematic, harmonised and large-scale biofilms data computation: the Biofilms Experiment Workbench.

    Science.gov (United States)

    Pérez-Rodríguez, Gael; Glez-Peña, Daniel; Azevedo, Nuno F; Pereira, Maria Olívia; Fdez-Riverola, Florentino; Lourenço, Anália

    2015-03-01

    Biofilms are receiving increasing attention from the biomedical community. Biofilm-like growth within human body is considered one of the key microbial strategies to augment resistance and persistence during infectious processes. The Biofilms Experiment Workbench is a novel software workbench for the operation and analysis of biofilms experimental data. The goal is to promote the interchange and comparison of data among laboratories, providing systematic, harmonised and large-scale data computation. The workbench was developed with AIBench, an open-source Java desktop application framework for scientific software development in the domain of translational biomedicine. Implementation favours free and open-source third-parties, such as the R statistical package, and reaches for the Web services of the BiofOmics database to enable public experiment deposition. First, we summarise the novel, free, open, XML-based interchange format for encoding biofilms experimental data. Then, we describe the execution of common scenarios of operation with the new workbench, such as the creation of new experiments, the importation of data from Excel spreadsheets, the computation of analytical results, the on-demand and highly customised construction of Web publishable reports, and the comparison of results between laboratories. A considerable and varied amount of biofilms data is being generated, and there is a critical need to develop bioinformatics tools that expedite the interchange and comparison of microbiological and clinical results among laboratories. We propose a simple, open-source software infrastructure which is effective, extensible and easy to understand. The workbench is freely available for non-commercial use at http://sing.ei.uvigo.es/bew under LGPL license. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

  11. Lessons learned from setting up the NOWESP research data base: Experiences in an interdisciplinary research project

    Science.gov (United States)

    Radach, Günther; Gekeler, Jens

    1996-09-01

    Research carried out within the framework of the MAST project NOWESP (North-West European Shelf Programme) was based on a multi-parameter data set of existing marine data, relevant for estimating trends, variability and fluxes on the Northwest European Shelf. The data sets were provided by the partners of the project. Additional data sets were obtained from several other institutions. During the project, the data were organized in the NOWESP Research Data Base (NRDB), for which a special data base scheme was defined that was capable of storing different types of marine data. Data products, like time series and interpolated fields, were provided to the partners for analysis (Radach et al. [1997]). After three years of project time, the feasibility of such an approach is discussed. Ways of optimizing data access and evaluation are proposed. A project-oriented Research Data Base is a useful tool because of its flexibility and proximity to the research being carried out. However, several requirements must be met to derive optimum benefits from this type of service unit. Since this task usually is carried out by a limited number of staff, an early start of project data management is recommended. To enable future projects to succeed in an analogous compilation of relevant data for their use, as performed in NOWESP, the task of organizing the data sets for any short-term project should be shared between a research data base group and a national or international data centre whose experience and software could be used. It must be ensured that only quality controlled data sets from the individual data-produ cing projects are delivered to the national data centres. It is recommended that data quality control should be performed by the originators and/or data centres before delivering any data sets to the research data base. Delivery of the (full) data sets should be checked and their quality should be approved by authorized data centres.

  12. [Driving modes of the interview in phenomenological research: experience report].

    Science.gov (United States)

    de Paula, Cristiane Cardoso; Padoin, Stela Maris de Mello; Terra, Marlene Gomes; Souza, Ivis Emília de Oliveira; Cabral, Ivone Evangelista

    2014-01-01

    This paper aimed to report the experience of driving modes of an interview on data production in phenomenological research. The proposed study is an experience report of a phenomenological investigation in which the researchers present their experience with children, considering the interview as an existential encounter. It describes ways of conducting the interview in its ontic and ontological dimensions. The ontic dimension refers to the facts related to the interview, presented in the researcher, in the researched subject and in the environment; both in its planning and its development. The ontological dimension is based on empathy and intersubjectivity. The interview enables the access to meaningful structures to comprehend the being, as a way of building investigative/assistance possibilities that enable to reveal the being of the human.

  13. Web-enabled Data Warehouse and Data Webhouse

    Directory of Open Access Journals (Sweden)

    Cerasela PIRVU

    2008-01-01

    Full Text Available In this paper, our objectives are to understanding what data warehouse means examine the reasons for doing so, appreciate the implications of the convergence of Web technologies and those of the data warehouse and examine the steps for building a Web-enabled data warehouse. The web revolution has propelled the data warehouse out onto the main stage, because in many situations the data warehouse must be the engine that controls or analysis the web experience. In order to step up to this new responsibility, the data warehouse must adjust. The nature of the data warehouse needs to be somewhat different. As a result, our data warehouses are becoming data webhouses. The data warehouse is becoming the infrastructure that supports customer relationship management (CRM. And the data warehouse is being asked to make the customer clickstream available for analysis. This rebirth of data warehousing architecture is called the data webhouse.

  14. BMI cyberworkstation: enabling dynamic data-driven brain-machine interface research through cyberinfrastructure.

    Science.gov (United States)

    Zhao, Ming; Rattanatamrong, Prapaporn; DiGiovanna, Jack; Mahmoudi, Babak; Figueiredo, Renato J; Sanchez, Justin C; Príncipe, José C; Fortes, José A B

    2008-01-01

    Dynamic data-driven brain-machine interfaces (DDDBMI) have great potential to advance the understanding of neural systems and improve the design of brain-inspired rehabilitative systems. This paper presents a novel cyberinfrastructure that couples in vivo neurophysiology experimentation with massive computational resources to provide seamless and efficient support of DDDBMI research. Closed-loop experiments can be conducted with in vivo data acquisition, reliable network transfer, parallel model computation, and real-time robot control. Behavioral experiments with live animals are supported with real-time guarantees. Offline studies can be performed with various configurations for extensive analysis and training. A Web-based portal is also provided to allow users to conveniently interact with the cyberinfrastructure, conducting both experimentation and analysis. New motor control models are developed based on this approach, which include recursive least square based (RLS) and reinforcement learning based (RLBMI) algorithms. The results from an online RLBMI experiment shows that the cyberinfrastructure can successfully support DDDBMI experiments and meet the desired real-time requirements.

  15. RImmPort: an R/Bioconductor package that enables ready-for-analysis immunology research data.

    Science.gov (United States)

    Shankar, Ravi D; Bhattacharya, Sanchita; Jujjavarapu, Chethan; Andorf, Sandra; Wiser, Jeffery A; Butte, Atul J

    2017-04-01

    : Open access to raw clinical and molecular data related to immunological studies has created a tremendous opportunity for data-driven science. We have developed RImmPort that prepares NIAID-funded research study datasets in ImmPort (immport.org) for analysis in R. RImmPort comprises of three main components: (i) a specification of R classes that encapsulate study data, (ii) foundational methods to load data of a specific study and (iii) generic methods to slice and dice data across different dimensions in one or more studies. Furthermore, RImmPort supports open formalisms, such as CDISC standards on the open source bioinformatics platform Bioconductor, to ensure that ImmPort curated study datasets are seamlessly accessible and ready for analysis, thus enabling innovative bioinformatics research in immunology. RImmPort is available as part of Bioconductor (bioconductor.org/packages/RImmPort). rshankar@stanford.edu. Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  16. The Microgravity Research Experiments (MICREX) Data Base. Volume 1

    Science.gov (United States)

    Winter, C. A.; Jones, J.C.

    1996-01-01

    An electronic data base identifying over 800 fluids and materials processing experiments performed in a low-gravity environment has been created at NASA Marshall Space Flight Center. The compilation, called MICREX (MICrogravity Research Experiments), was designed to document all such experimental efforts performed (1) on U.S. manned space vehicles, (2) on payloads deployed from U.S. manned space vehicles, and (3) on all domestic and international sounding rockets (excluding those of China and the former U.S.S.R.). Data available on most experiments include (1) principal and co-investigators, (2) low-gravity mission, (3) processing facility, (4) experimental objectives and results, (5) identifying key words, (6) sample materials, (7) applications of the processed materials/research area, (8) experiment descriptive publications, and (9) contacts for more information concerning the experiment. This technical memorandum (1) summarizes the historical interest in reduced-gravity fluid dynamics, (2) describes the experimental facilities employed to examine reduced gravity fluid flow, (3) discusses the importance of a low-gravity fluids and materials processing data base, (4) describes the MICREX data base format and computational World Wide Web access procedures, and (5) documents (in hard-copy form) the descriptions of the first 600 fluids and materials processing experiments entered into MICREX.

  17. Data Curation Education in Research Centers (DCERC)

    Science.gov (United States)

    Marlino, M. R.; Mayernik, M. S.; Kelly, K.; Allard, S.; Tenopir, C.; Palmer, C.; Varvel, V. E., Jr.

    2012-12-01

    Digital data both enable and constrain scientific research. Scientists are enabled by digital data to develop new research methods, utilize new data sources, and investigate new topics, but they also face new data collection, management, and preservation burdens. The current data workforce consists primarily of scientists who receive little formal training in data management and data managers who are typically educated through on-the-job training. The Data Curation Education in Research Centers (DCERC) program is investigating a new model for educating data professionals to contribute to scientific research. DCERC is a collaboration between the University of Illinois at Urbana-Champaign Graduate School of Library and Information Science, the University of Tennessee School of Information Sciences, and the National Center for Atmospheric Research. The program is organized around a foundations course in data curation and provides field experiences in research and data centers for both master's and doctoral students. This presentation will outline the aims and the structure of the DCERC program and discuss results and lessons learned from the first set of summer internships in 2012. Four masters students participated and worked with both data mentors and science mentors, gaining first hand experiences in the issues, methods, and challenges of scientific data curation. They engaged in a diverse set of topics, including climate model metadata, observational data management workflows, and data cleaning, documentation, and ingest processes within a data archive. The students learned current data management practices and challenges while developing expertise and conducting research. They also made important contributions to NCAR data and science teams by evaluating data management workflows and processes, preparing data sets to be archived, and developing recommendations for particular data management activities. The master's student interns will return in summer of 2013

  18. Enabling long-term oceanographic research: Changing data practices, information management strategies and informatics

    Science.gov (United States)

    Baker, Karen S.; Chandler, Cynthia L.

    2008-09-01

    Interdisciplinary global ocean science requires new ways of thinking about data and data management. With new data policies and growing technological capabilities, datasets of increasing variety and complexity are being made available digitally and data management is coming to be recognized as an integral part of scientific research. To meet the changing expectations of scientists collecting data and of data reuse by others, collaborative strategies involving diverse teams of information professionals are developing. These changes are stimulating the growth of information infrastructures that support multi-scale sampling, data repositories, and data integration. Two examples of oceanographic projects incorporating data management in partnership with science programs are discussed: the Palmer Station Long-Term Ecological Research program (Palmer LTER) and the United States Joint Global Ocean Flux Study (US JGOFS). Lessons learned from a decade of data management within these communities provide an experience base from which to develop information management strategies—short-term and long-term. Ocean Informatics provides one example of a conceptual framework for managing the complexities inherent to sharing oceanographic data. Elements are introduced that address the economies-of-scale and the complexities-of-scale pertinent to a broader vision of information management and scientific research.

  19. Using secondary analysis of qualitative data of patient experiences of health care to inform health services research and policy.

    Science.gov (United States)

    Ziebland, Sue; Hunt, Kate

    2014-07-01

    Qualitative research is recognized as an important method for including patients' voices and experiences in health services research and policy-making, yet the considerable potential to analyse existing qualitative data to inform health policy and practice has been little realized. This failure may partly be explained by: a lack of awareness amongst health policy makers of the increasing wealth of qualitative data available; and around 15 years of internal debates among qualitative researchers on the strengths, limitations and validity of re-use of qualitative data. Whilst acknowledging the challenges of qualitative secondary data analysis, we argue that there is a growing imperative to be pragmatic and to undertake analysis of existing qualitative data collections where they have the potential to contribute to health policy formulation. Time pressures are inherent in the policy-making process and in many circumstances it is not possible to seek funding, conduct and analyse new qualitative studies of patients' experiences in time to inform a specific policy. The danger then is that the patient voice, and the experiences of relatives and carers, is either excluded or included in a way that is easily dismissed as 'unrepresentative'. We argue that secondary analysis of qualitative data collections may sometimes be an effective means to enable patient experiences to inform policy decision-making. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

  20. Lowering the Barriers to Using Data: Enabling Desktop-based HPD Science through Virtual Environments and Web Data Services

    Science.gov (United States)

    Druken, K. A.; Trenham, C. E.; Steer, A.; Evans, B. J. K.; Richards, C. J.; Smillie, J.; Allen, C.; Pringle, S.; Wang, J.; Wyborn, L. A.

    2016-12-01

    The Australian National Computational Infrastructure (NCI) provides access to petascale data in climate, weather, Earth observations, and genomics, and terascale data in astronomy, geophysics, ecology and land use, as well as social sciences. The data is centralized in a closely integrated High Performance Computing (HPC), High Performance Data (HPD) and cloud facility. Despite this, there remain significant barriers for many users to find and access the data: simply hosting a large volume of data is not helpful if researchers are unable to find, access, and use the data for their particular need. Use cases demonstrate we need to support a diverse range of users who are increasingly crossing traditional research discipline boundaries. To support their varying experience, access needs and research workflows, NCI has implemented an integrated data platform providing a range of services that enable users to interact with our data holdings. These services include: - A GeoNetwork catalog built on standardized Data Management Plans to search collection metadata, and find relevant datasets; - Web data services to download or remotely access data via OPeNDAP, WMS, WCS and other protocols; - Virtual Desktop Infrastructure (VDI) built on a highly integrated on-site cloud with access to both the HPC peak machine and research data collections. The VDI is a fully featured environment allowing visualization, code development and analysis to take place in an interactive desktop environment; and - A Learning Management System (LMS) containing User Guides, Use Case examples and Jupyter Notebooks structured into courses, so that users can self-teach how to use these facilities with examples from our system across a range of disciplines. We will briefly present these components, and discuss how we engage with data custodians and consumers to develop standardized data structures and services that support the range of needs. We will also highlight some key developments that have

  1. Enabling Open Research Data Discovery through a Recommender System

    Science.gov (United States)

    Devaraju, Anusuriya; Jayasinghe, Gaya; Klump, Jens; Hogan, Dominic

    2017-04-01

    Government agencies, universities, research and nonprofit organizations are increasingly publishing their datasets to promote transparency, induce new research and generate economic value through the development of new products or services. The datasets may be downloaded from various data portals (data repositories) which are general or domain-specific. The Registry of Research Data Repository (re3data.org) lists more than 2500 such data repositories from around the globe. Data portals allow keyword search and faceted navigation to facilitate discovery of research datasets. However, the volume and variety of datasets have made finding relevant datasets more difficult. Common dataset search mechanisms may be time consuming, may produce irrelevant results and are primarily suitable for users who are familiar with the general structure and contents of the respective database. Therefore, we need new approaches to support research data discovery. Recommender systems offer new possibilities for users to find datasets that are relevant to their research interests. This study presents a recommender system developed for the CSIRO Data Access Portal (DAP, http://data.csiro.au). The datasets hosted on the portal are diverse, published by researchers from 13 business units in the organisation. The goal of the study is not to replace the current search mechanisms on the data portal, but rather to extend the data discovery through an exploratory search, in this case by building a recommender system. We adopted a hybrid recommendation approach, comprising content-based filtering and item-item collaborative filtering. The content-based filtering computes similarities between datasets based on metadata such as title, keywords, descriptions, fields of research, location, contributors, etc. The collaborative filtering utilizes user search behaviour and download patterns derived from the server logs to determine similar datasets. Similarities above are then combined with different

  2. NAMMA LANGLEY AEROSOL RESEARCH GROUP EXPERIMENT NAVIGATION DATA V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The NAMMA Langley Aerosol Research Group Experiment Navigation Data is the DC-8 NAV data (ICATS) extracted into columns with time correction. These data files were...

  3. Experiences with a researcher-centric ELN.

    Science.gov (United States)

    Badiola, Katrina A; Bird, Colin; Brocklesby, William S; Casson, John; Chapman, Richard T; Coles, Simon J; Cronshaw, James R; Fisher, Adam; Frey, Jeremy G; Gloria, Danmar; Grossel, Martin C; Hibbert, D Brynn; Knight, Nicola; Mapp, Lucy K; Marazzi, Luke; Matthews, Brian; Milsted, Andy; Minns, Russell S; Mueller, Karl T; Murphy, Kelly; Parkinson, Tim; Quinnell, Rosanne; Robinson, John S; Robertson, Murray N; Robins, Michael; Springate, Emma; Tizzard, Graham; Todd, Matthew H; Williamson, Alice E; Willoughby, Cerys; Yang, Erica; Ylioja, Paul M

    2015-03-01

    Electronic Laboratory Notebooks (ELNs) are progressively replacing traditional paper books in both commercial research establishments and academic institutions. University researchers require specific features from ELNs, given the need to promote cross-institutional collaborative working, to enable the sharing of procedures and results, and to facilitate publication. The LabTrove ELN, which we use as our exemplar, was designed to be researcher-centric ( i.e. , not only aimed at the individual researcher's basic needs rather than to a specific institutional or subject or disciplinary agenda, but also able to be tailored because it is open source). LabTrove is being used in a heterogeneous set of academic laboratories, for a range of purposes, including analytical chemistry, X-ray studies, drug discovery and a biomaterials project. Researchers use the ELN for recording experiments, preserving data collected, and for project coordination. This perspective article describes the experiences of those researchers from several viewpoints, demonstrating how a web-based open source electronic notebook can meet the diverse needs of academic researchers.

  4. BCO-DMO: Enabling Access to Federally Funded Research Data

    Science.gov (United States)

    Kinkade, D.; Allison, M. D.; Chandler, C. L.; Groman, R. C.; Rauch, S.; Shepherd, A.; Gegg, S. R.; Wiebe, P. H.; Glover, D. M.

    2013-12-01

    In a February, 2013 memo1, the White House Office of Science and Technology Policy (OSTP) outlined principles and objectives to increase access by the public to federally funded research publications and data. Such access is intended to drive innovation by allowing private and commercial efforts to take full advantage of existing resources, thereby maximizing Federal research dollars and efforts. The Biological and Chemical Oceanography Data Management Office (BCO-DMO; bco-dmo.org) serves as a model resource for organizations seeking compliance with the OSTP policy. BCO-DMO works closely with scientific investigators to publish their data from research projects funded by the National Science Foundation (NSF), within the Biological and Chemical Oceanography Sections (OCE) and the Division of Polar Programs Antarctic Organisms & Ecosystems Program (PLR). BCO-DMO addresses many of the OSTP objectives for public access to digital scientific data: (1) Marine biogeochemical and ecological data and metadata are disseminated via a public website, and curated on intermediate time frames; (2) Preservation needs are met by collaborating with appropriate national data facilities for data archive; (3) Cost and administrative burden associated with data management is minimized by the use of one dedicated office providing hundreds of NSF investigators support for data management plan development, data organization, metadata generation and deposition of data and metadata into the BCO-DMO repository; (4) Recognition of intellectual property is reinforced through the office's citation policy and the use of digital object identifiers (DOIs); (5) Education and training in data stewardship and use of the BCO-DMO system is provided by office staff through a variety of venues. Oceanographic research data and metadata from thousands of datasets generated by hundreds of investigators are now available through BCO-DMO. 1 White House Office of Science and Technology Policy, Memorandum for

  5. Enabling software defined networking experiments in networked critical infrastructures

    Directory of Open Access Journals (Sweden)

    Béla Genge

    2014-05-01

    Full Text Available Nowadays, the fact that Networked Critical Infrastructures (NCI, e.g., power plants, water plants, oil and gas distribution infrastructures, and electricity grids, are targeted by significant cyber threats is well known. Nevertheless, recent research has shown that specific characteristics of NCI can be exploited in the enabling of more efficient mitigation techniques, while novel techniques from the field of IP networks can bring significant advantages. In this paper we explore the interconnection of NCI communication infrastructures with Software Defined Networking (SDN-enabled network topologies. SDN provides the means to create virtual networking services and to implement global networking decisions. It relies on OpenFlow to enable communication with remote devices and has been recently categorized as the “Next Big Technology”, which will revolutionize the way decisions are implemented in switches and routers. Therefore, the paper documents the first steps towards enabling an SDN-NCI and presents the impact of a Denial of Service experiment over traffic resulting from an XBee sensor network which is routed across an emulated SDN network.

  6. Semantically Enabling Knowledge Representation of Metamorphic Petrology Data

    Science.gov (United States)

    West, P.; Fox, P. A.; Spear, F. S.; Adali, S.; Nguyen, C.; Hallett, B. W.; Horkley, L. K.

    2012-12-01

    More and more metamorphic petrology data is being collected around the world, and is now being organized together into different virtual data portals by means of virtual organizations. For example, there is the virtual data portal Petrological Database (PetDB, http://www.petdb.org) of the Ocean Floor that is organizing scientific information about geochemical data of ocean floor igneous and metamorphic rocks; and also The Metamorphic Petrology Database (MetPetDB, http://metpetdb.rpi.edu) that is being created by a global community of metamorphic petrologists in collaboration with software engineers and data managers at Rensselaer Polytechnic Institute. The current focus is to provide the ability for scientists and researchers to register their data and search the databases for information regarding sample collections. What we present here is the next step in evolution of the MetPetDB portal, utilizing semantically enabled features such as discovery, data casting, faceted search, knowledge representation, and linked data as well as organizing information about the community and collaboration within the virtual community itself. We take the information that is currently represented in a relational database and make it available through web services, SPARQL endpoints, semantic and triple-stores where inferencing is enabled. We will be leveraging research that has taken place in virtual observatories, such as the Virtual Solar Terrestrial Observatory (VSTO) and the Biological and Chemical Oceanography Data Management Office (BCO-DMO); vocabulary work done in various communities such as Observations and Measurements (ISO 19156), FOAF (Friend of a Friend), Bibo (Bibliography Ontology), and domain specific ontologies; enabling provenance traces of samples and subsamples using the different provenance ontologies; and providing the much needed linking of data from the various research organizations into a common, collaborative virtual observatory. In addition to better

  7. Some experiences and opportunities for big data in translational research.

    Science.gov (United States)

    Chute, Christopher G; Ullman-Cullere, Mollie; Wood, Grant M; Lin, Simon M; He, Min; Pathak, Jyotishman

    2013-10-01

    Health care has become increasingly information intensive. The advent of genomic data, integrated into patient care, significantly accelerates the complexity and amount of clinical data. Translational research in the present day increasingly embraces new biomedical discovery in this data-intensive world, thus entering the domain of "big data." The Electronic Medical Records and Genomics consortium has taught us many lessons, while simultaneously advances in commodity computing methods enable the academic community to affordably manage and process big data. Although great promise can emerge from the adoption of big data methods and philosophy, the heterogeneity and complexity of clinical data, in particular, pose additional challenges for big data inferencing and clinical application. However, the ultimate comparability and consistency of heterogeneous clinical information sources can be enhanced by existing and emerging data standards, which promise to bring order to clinical data chaos. Meaningful Use data standards in particular have already simplified the task of identifying clinical phenotyping patterns in electronic health records.

  8. Federated and Cloud Enabled Resources for Data Management and Utilization

    Science.gov (United States)

    Rankin, R.; Gordon, M.; Potter, R. G.; Satchwill, B.

    2011-12-01

    The emergence of cloud computing over the past three years has led to a paradigm shift in how data can be managed, processed and made accessible. Building on the federated data management system offered through the Canadian Space Science Data Portal (www.cssdp.ca), we demonstrate how heterogeneous and geographically distributed data sets and modeling tools have been integrated to form a virtual data center and computational modeling platform that has services for data processing and visualization embedded within it. We also discuss positive and negative experiences in utilizing Eucalyptus and OpenStack cloud applications, and job scheduling facilitated by Condor and Star Cluster. We summarize our findings by demonstrating use of these technologies in the Cloud Enabled Space Weather Data Assimilation and Modeling Platform CESWP (www.ceswp.ca), which is funded through Canarie's (canarie.ca) Network Enabled Platforms program in Canada.

  9. Enabling Data Discovery and Reuse by Improving Software Usability:Data Science Experiences, Lessons, and Gaps

    Science.gov (United States)

    Rosati, A.; Yarmey, L.

    2014-12-01

    It is well understood that a good data scientist needs domain science, analysis, programming, and communication skills to create finished data products, visualizations, and reports. Articles and blogs tout the need for "expert" skill levels in domain knowledge, statistics, storytelling, graphic design, technology…and the list goes on. Since it seems impossible that one person would encompass all these skills, it is often suggested that data science be done by a team instead of an individual. This research into, and experience with, data product design offers an augmented definition - one that elevates relationships and engagement with the final user of a product. Essentially, no matter how fantastic or technically advanced a product appears, the intended audience of that product must be able to understand, use, and find value in the product in order for it to be considered a success. Usability is often misunderstood and seen as common sense or common knowledge, but it is actually an important and challenging piece of product development. This paper describes the National Snow and Ice Data Center's process to usability test the Arctic Data Explorer (ADE). The ADE is a federated data search tool for interdisciplinary Arctic science data that has been improved in features, appearance, functionality, and quality through a series of strategic and targeted usability testing and assessments. Based on the results, it is recommended that usability testing be incorporated into the skill set of each data science team.

  10. Practices to enable the geophysical research spectrum: from fundamentals to applications

    Science.gov (United States)

    Kang, S.; Cockett, R.; Heagy, L. J.; Oldenburg, D.

    2016-12-01

    In a geophysical survey, a source injects energy into the earth and a response is measured. These physical systems are governed by partial differential equations and their numerical solutions are obtained by discretizing the earth. Geophysical simulations and inversions are tools for understanding physical responses and constructing models of the subsurface given a finite amount of data. SimPEG (http://simpeg.xyz) is our effort to synthesize geophysical forward and inverse methodologies into a consistent framework. The primary focus of our initial development has been on the electromagnetics (EM) package, with recent extensions to magnetotelluric, direct current (DC), and induced polarization. Across these methods, and applied geophysics in general, we require tools to explore and build an understanding of the physics (behaviour of fields, fluxes), and work with data to produce models through reproducible inversions. If we consider DC or EM experiments, with the aim of understanding responses from subsurface conductors, we require resources that provide multiple "entry points" into the geophysical problem. To understand the physical responses and measured data, we must simulate the physical system and visualize electric fields, currents, and charges. Performing an inversion requires that many moving pieces be brought together: simulation, physics, linear algebra, data processing, optimization, etc. Each component must be trusted, accessible to interrogation and manipulation, and readily combined in order to enable investigation into inversion methodologies. To support such research, we not only require "entry points" into the software, but also extensibility to new situations. In our development of SimPEG, we have sought to use leading practices in software development with the aim of supporting and promoting collaborations across a spectrum of geophysical research: from fundamentals to applications. Designing software to enable this spectrum puts unique

  11. Participatory Action Research Experiences for Undergraduates

    Science.gov (United States)

    Sample McMeeking, L. B.; Weinberg, A. E.

    2013-12-01

    Research experiences for undergraduates (REU) have been shown to be effective in improving undergraduate students' personal/professional development, ability to synthesize knowledge, improvement in research skills, professional advancement, and career choice. Adding to the literature on REU programs, a new conceptual model situating REU within a context of participatory action research (PAR) is presented and compared with data from a PAR-based coastal climate research experience that took place in Summer 2012. The purpose of the interdisciplinary Participatory Action Research Experiences for Undergraduates (PAREU) model is to act as an additional year to traditional, lab-based REU where undergraduate science students, social science experts, and community members collaborate to develop research with the goal of enacting change. The benefits to traditional REU's are well established and include increased content knowledge, better research skills, changes in attitudes, and greater career awareness gained by students. Additional positive outcomes are expected from undergraduate researchers (UR) who participate in PAREU, including the ability to better communicate with non-scientists. With highly politicized aspects of science, such as climate change, this becomes especially important for future scientists. Further, they will be able to articulate the relevance of science research to society, which is an important skill, especially given the funding climate where agencies require broader impacts statements. Making science relevant may also benefit URs who wish to apply their science research. Finally, URs will gain social science research skills by apprenticing in a research project that includes science and social science research components, which enables them to participate in future education and outreach. The model also positively impacts community members by elevating their voices within and outside the community, particularly in areas severely underserved

  12. Enabling European Archaeological Research: The ARIADNE E-Infrastructure

    Directory of Open Access Journals (Sweden)

    Nicola Aloia

    2017-03-01

    Full Text Available Research e-infrastructures, digital archives and data services have become important pillars of scientific enterprise that in recent decades has become ever more collaborative, distributed and data-intensive. The archaeological research community has been an early adopter of digital tools for data acquisition, organisation, analysis and presentation of research results of individual projects. However, the provision of e-infrastructure and services for data sharing, discovery, access and re-use has lagged behind. This situation is being addressed by ARIADNE: the Advanced Research Infrastructure for Archaeological Dataset Networking in Europe. This EU-funded network has developed an e-infrastructure that enables data providers to register and provide access to their resources (datasets, collections through the ARIADNE data portal, facilitating discovery, access and other services across the integrated resources. This article describes the current landscape of data repositories and services for archaeologists in Europe, and the issues that make interoperability between them difficult to realise. The results of the ARIADNE surveys on users' expectations and requirements are also presented. The main section of the article describes the architecture of the e-infrastructure, core services (data registration, discovery and access and various other extant or experimental services. The on-going evaluation of the data integration and services is also discussed. Finally, the article summarises lessons learned, and outlines the prospects for the wider engagement of the archaeological research community in sharing data through ARIADNE.

  13. Disability, family and technical aids: a study of how disabling/enabling experiences come about in hybrid family relations

    NARCIS (Netherlands)

    Horst, van der H.M.; Hoogsteyns, M.

    2014-01-01

    Research regarding disabling situations generally focuses on disabling situations within a public society ‘out there’. In our research, however, the intimate family setting itself appears central to the emergence of dis/enabling experiences. Moreover, the relationships that shaped these experiences

  14. The MIMIC Code Repository: enabling reproducibility in critical care research.

    Science.gov (United States)

    Johnson, Alistair Ew; Stone, David J; Celi, Leo A; Pollard, Tom J

    2018-01-01

    Lack of reproducibility in medical studies is a barrier to the generation of a robust knowledge base to support clinical decision-making. In this paper we outline the Medical Information Mart for Intensive Care (MIMIC) Code Repository, a centralized code base for generating reproducible studies on an openly available critical care dataset. Code is provided to load the data into a relational structure, create extractions of the data, and reproduce entire analysis plans including research studies. Concepts extracted include severity of illness scores, comorbid status, administrative definitions of sepsis, physiologic criteria for sepsis, organ failure scores, treatment administration, and more. Executable documents are used for tutorials and reproduce published studies end-to-end, providing a template for future researchers to replicate. The repository's issue tracker enables community discussion about the data and concepts, allowing users to collaboratively improve the resource. The centralized repository provides a platform for users of the data to interact directly with the data generators, facilitating greater understanding of the data. It also provides a location for the community to collaborate on necessary concepts for research progress and share them with a larger audience. Consistent application of the same code for underlying concepts is a key step in ensuring that research studies on the MIMIC database are comparable and reproducible. By providing open source code alongside the freely accessible MIMIC-III database, we enable end-to-end reproducible analysis of electronic health records. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association.

  15. The COPD Knowledge Base: enabling data analysis and computational simulation in translational COPD research.

    Science.gov (United States)

    Cano, Isaac; Tényi, Ákos; Schueller, Christine; Wolff, Martin; Huertas Migueláñez, M Mercedes; Gomez-Cabrero, David; Antczak, Philipp; Roca, Josep; Cascante, Marta; Falciani, Francesco; Maier, Dieter

    2014-11-28

    Previously we generated a chronic obstructive pulmonary disease (COPD) specific knowledge base (http://www.copdknowledgebase.eu) from clinical and experimental data, text-mining results and public databases. This knowledge base allowed the retrieval of specific molecular networks together with integrated clinical and experimental data. The COPDKB has now been extended to integrate over 40 public data sources on functional interaction (e.g. signal transduction, transcriptional regulation, protein-protein interaction, gene-disease association). In addition we integrated COPD-specific expression and co-morbidity networks connecting over 6 000 genes/proteins with physiological parameters and disease states. Three mathematical models describing different aspects of systemic effects of COPD were connected to clinical and experimental data. We have completely redesigned the technical architecture of the user interface and now provide html and web browser-based access and form-based searches. A network search enables the use of interconnecting information and the generation of disease-specific sub-networks from general knowledge. Integration with the Synergy-COPD Simulation Environment enables multi-scale integrated simulation of individual computational models while integration with a Clinical Decision Support System allows delivery into clinical practice. The COPD Knowledge Base is the only publicly available knowledge resource dedicated to COPD and combining genetic information with molecular, physiological and clinical data as well as mathematical modelling. Its integrated analysis functions provide overviews about clinical trends and connections while its semantically mapped content enables complex analysis approaches. We plan to further extend the COPDKB by offering it as a repository to publish and semantically integrate data from relevant clinical trials. The COPDKB is freely available after registration at http://www.copdknowledgebase.eu.

  16. Software-Enabled Distributed Network Governance: The PopMedNet Experience.

    Science.gov (United States)

    Davies, Melanie; Erickson, Kyle; Wyner, Zachary; Malenfant, Jessica; Rosen, Rob; Brown, Jeffrey

    2016-01-01

    The expanded availability of electronic health information has led to increased interest in distributed health data research networks. The distributed research network model leaves data with and under the control of the data holder. Data holders, network coordinating centers, and researchers have distinct needs and challenges within this model. The concerns of network stakeholders are addressed in the design and governance models of the PopMedNet software platform. PopMedNet features include distributed querying, customizable workflows, and auditing and search capabilities. Its flexible role-based access control system enables the enforcement of varying governance policies. Four case studies describe how PopMedNet is used to enforce network governance models. Trust is an essential component of a distributed research network and must be built before data partners may be willing to participate further. The complexity of the PopMedNet system must be managed as networks grow and new data, analytic methods, and querying approaches are developed. The PopMedNet software platform supports a variety of network structures, governance models, and research activities through customizable features designed to meet the needs of network stakeholders.

  17. The CUAHSI Water Data Center: Enabling Data Publication, Discovery and Re-use

    Science.gov (United States)

    Seul, M.; Pollak, J.

    2014-12-01

    The CUAHSI Water Data Center (WDC) supports a standards-based, services-oriented architecture for time-series data and provides a separate service to publish spatial data layers as shape files. Two new services that the WDC offers are a cloud-based server (Cloud HydroServer) for publishing data and a web-based client for data discovery. The Cloud HydroServer greatly simplifies data publication by eliminating the need for scientists to set up an SQL-server data base, a requirement that has proven to be a significant barrier, and ensures greater reliability and continuity of service. Uploaders have been developed to simplify the metadata documentation process. The web-based data client eliminates the need for installing a program to be used as a client and works across all computer operating systems. The services provided by the WDC is a foundation for big data use, re-use, and meta-analyses. Using data transmission standards enables far more effective data sharing and discovery; standards used by the WDC are part of a global set of standards that should enable scientists to access unprecedented amount of data to address larger-scale research questions than was previously possible. A central mission of the WDC is to ensure these services meet the needs of the water science community and are effective at advancing water science.

  18. Easy research data handling with an OpenEarth DataLab for geo-monitoring research

    Science.gov (United States)

    Vanderfeesten, Maurice; van der Kuil, Annemiek; Prinčič, Alenka; den Heijer, Kees; Rombouts, Jeroen

    2015-04-01

    OpenEarth DataLab is an open source-based collaboration and processing platform to enable streamlined research data management from raw data ingest and transformation to interoperable distribution. It enables geo-scientists to easily synchronise, share, compute and visualise the dynamic and most up-to-date research data, scripts and models in multi-stakeholder geo-monitoring programs. This DataLab is developed by the Research Data Services team of TU Delft Library and 3TU.Datacentrum together with coastal engineers of Delft University of Technology and Deltares. Based on the OpenEarth software stack an environment has been developed to orchestrate numerous geo-related open source software components that can empower researchers and increase the overall research quality by managing research data; enabling automatic and interoperable data workflows between all the components with track & trace, hit & run data transformation processing in cloud infrastructure using MatLab and Python, synchronisation of data and scripts (SVN), and much more. Transformed interoperable data products (KML, NetCDF, PostGIS) can be used by ready-made OpenEarth tools for further analyses and visualisation, and can be distributed via interoperable channels such as THREDDS (OpenDAP) and GeoServer. An example of a successful application of OpenEarth DataLab is the Sand Motor, an innovative method for coastal protection in the Netherlands. The Sand Motor is a huge volume of sand that has been applied along the coast to be spread naturally by wind, waves and currents. Different research disciplines are involved concerned with: weather, waves and currents, sand distribution, water table and water quality, flora and fauna, recreation and management. Researchers share and transform their data in the OpenEarth DataLab, that makes it possible to combine their data and to see influence of different aspects of the coastal protection on their models. During the project the data are available only for the

  19. The SUPER Program: A Research-based Undergraduate Experience

    Science.gov (United States)

    Ernakovich, J. G.; Boone, R. B.; Boot, C. M.; Denef, K.; Lavallee, J. M.; Moore, J. C.; Wallenstein, M. D.

    2014-12-01

    Producing undergraduates capable of broad, independent thinking is one of the grand challenges in science education. Experience-based learning, specifically hands-on research, is one mechanism for increasing students' ability to think critically. With this in mind, we created a two-semester long research program called SUPER (Skills for Undergraduate Participation in Ecological Research) aimed at teaching students to think like scientists and enhancing the student research experience through instruction and active-learning about the scientific method. Our aim was for students to gain knowledge, skills, and experience, and to conduct their own research. In the first semester, we hosted active-learning workshops on "Forming Hypotheses", "Experimental Design", "Collecting and Managing Data", "Analysis of Data", "Communicating to a Scientific Audience", "Reading Literature Effectively", and "Ethical Approaches". Each lesson was taught by different scientists from one of many ecological disciplines so that students were exposed to the variation in approach that scientists have. In the second semester, students paired with a scientific mentor and began doing research. To ensure the continued growth of the undergraduate researcher, we continued the active-learning workshops and the students attended meetings with their mentors. Thus, the students gained technical and cognitive skills in parallel, enabling them to understand both "the how" and "the why" of what they were doing in their research. The program culminated with a research poster session presented by the students. The interest in the program has grown beyond our expectations, and we have now run the program successfully for two years. Many of the students have gone on to campus research jobs, internships and graduate school, and have attributed part of their success in obtaining their positions to their experience with the SUPER program. Although common in other sciences, undergraduate research experiences are

  20. Emerging Good Practice in Managing Research Data and Research Information within UK Universities

    DEFF Research Database (Denmark)

    Davidson, Joy; Jones, Sarah; Molloy, Laura

    2014-01-01

    Sound data intensive science depends upon effective research data and information management. Efficient and interoperable research information systems will be crucial for enabling and exploiting data intensive research however it is equally important that a research ecosystem is cultivated within...... institutions prepare to meet funding body mandates relating to research data management and sharing and to engage fully in the digital agenda.......Sound data intensive science depends upon effective research data and information management. Efficient and interoperable research information systems will be crucial for enabling and exploiting data intensive research however it is equally important that a research ecosystem is cultivated within...... research-intensive institutions that foster sustainable communication, cooperation and support of a diverse range of research-related staff. Researchers, librarians, administrators, ethics advisors, and IT professionals all have a vital contribution to make in ensuring that research data and related...

  1. Grid computing : enabling a vision for collaborative research

    International Nuclear Information System (INIS)

    von Laszewski, G.

    2002-01-01

    In this paper the authors provide a motivation for Grid computing based on a vision to enable a collaborative research environment. The authors vision goes beyond the connection of hardware resources. They argue that with an infrastructure such as the Grid, new modalities for collaborative research are enabled. They provide an overview showing why Grid research is difficult, and they present a number of management-related issues that must be addressed to make Grids a reality. They list projects that provide solutions to subsets of these issues

  2. Distributed cognition and process management enabling individualized translational research: The NIH Undiagnosed Diseases Program experience

    Directory of Open Access Journals (Sweden)

    Amanda E Links

    2016-10-01

    Full Text Available The National Institutes of Health Undiagnosed Diseases Program (NIH UDP applies translational research systematically to diagnose patients with undiagnosed diseases. The challenge is to implement an information system enabling scalable translational research. The authors hypothesized that similarly complex problems are resolvable through process management and the distributed cognition of communities. The team therefore built the NIH UDP Integrated Collaboration System (UDPICS to form virtual collaborative multidisciplinary research networks or communities. UDPICS supports these communities through integrated process management, ontology-based phenotyping, biospecimen management, cloud-based genomic analysis, and an electronic laboratory notebook. UDPICS provided a mechanism for efficient, transparent, and scalable translational research and thereby addressed many of the complex and diverse research and logistical problems of the NIH UDP. Full definition of the strengths and deficiencies of UDPICS will require formal qualitative and quantitative usability and process improvement measurement.

  3. Distributed Cognition and Process Management Enabling Individualized Translational Research: The NIH Undiagnosed Diseases Program Experience.

    Science.gov (United States)

    Links, Amanda E; Draper, David; Lee, Elizabeth; Guzman, Jessica; Valivullah, Zaheer; Maduro, Valerie; Lebedev, Vlad; Didenko, Maxim; Tomlin, Garrick; Brudno, Michael; Girdea, Marta; Dumitriu, Sergiu; Haendel, Melissa A; Mungall, Christopher J; Smedley, Damian; Hochheiser, Harry; Arnold, Andrew M; Coessens, Bert; Verhoeven, Steven; Bone, William; Adams, David; Boerkoel, Cornelius F; Gahl, William A; Sincan, Murat

    2016-01-01

    The National Institutes of Health Undiagnosed Diseases Program (NIH UDP) applies translational research systematically to diagnose patients with undiagnosed diseases. The challenge is to implement an information system enabling scalable translational research. The authors hypothesized that similar complex problems are resolvable through process management and the distributed cognition of communities. The team, therefore, built the NIH UDP integrated collaboration system (UDPICS) to form virtual collaborative multidisciplinary research networks or communities. UDPICS supports these communities through integrated process management, ontology-based phenotyping, biospecimen management, cloud-based genomic analysis, and an electronic laboratory notebook. UDPICS provided a mechanism for efficient, transparent, and scalable translational research and thereby addressed many of the complex and diverse research and logistical problems of the NIH UDP. Full definition of the strengths and deficiencies of UDPICS will require formal qualitative and quantitative usability and process improvement measurement.

  4. Nano-enabled drug delivery: a research profile.

    Science.gov (United States)

    Zhou, Xiao; Porter, Alan L; Robinson, Douglas K R; Shim, Min Suk; Guo, Ying

    2014-07-01

    Nano-enabled drug delivery (NEDD) systems are rapidly emerging as a key area for nanotechnology application. Understanding the status and developmental prospects of this area around the world is important to determine research priorities, and to evaluate and direct progress. Global research publication and patent databases provide a reservoir of information that can be tapped to provide intelligence for such needs. Here, we present a process to allow for extraction of NEDD-related information from these databases by involving topical experts. This process incorporates in-depth analysis of NEDD literature review papers to identify key subsystems and major topics. We then use these to structure global analysis of NEDD research topical trends and collaborative patterns, inform future innovation directions. This paper describes the process of how to derive nano-enabled drug delivery-related information from global research and patent databases in an effort to perform comprehensive global analysis of research trends and directions, along with collaborative patterns. Copyright © 2014 Elsevier Inc. All rights reserved.

  5. CERN Open Data Portal - Improving usability and user experience of CMS Open Data research tools.

    CERN Document Server

    Hirvonsalo, Harri

    2015-01-01

    This report summarizes the work I have done during my assignment as participant of CERN Summer Students 2015 programme. Main goal of my Summer Student project was to lower the bar for people to start utilizing open data that CMS experiment has released in November 2014 to CERN Open Data Portal (http://opendata.cern.ch). Project included various working packages and tasks, such as: -Determine the obstacles that potential users of CMS research oriented open data who don’t have previous knowledge about internal workflow of analysis tasks at CMS experiment would run into. -Produce more introductory material and tutorials for conducting basic physics analyses with CMSSW to CERN Open Data Portal. -Study the feasibility of podio-framework (https://github.com/hegner/podio) for CMS Open Data users. The project work was done under the supervision of Kati Lassila-Perini whom I thank greatly for her help, patience and support.

  6. Detecting Lung and Colorectal Cancer Recurrence Using Structured Clinical/Administrative Data to Enable Outcomes Research and Population Health Management.

    Science.gov (United States)

    Hassett, Michael J; Uno, Hajime; Cronin, Angel M; Carroll, Nikki M; Hornbrook, Mark C; Ritzwoller, Debra

    2017-12-01

    Recurrent cancer is common, costly, and lethal, yet we know little about it in community-based populations. Electronic health records and tumor registries contain vast amounts of data regarding community-based patients, but usually lack recurrence status. Existing algorithms that use structured data to detect recurrence have limitations. We developed algorithms to detect the presence and timing of recurrence after definitive therapy for stages I-III lung and colorectal cancer using 2 data sources that contain a widely available type of structured data (claims or electronic health record encounters) linked to gold-standard recurrence status: Medicare claims linked to the Cancer Care Outcomes Research and Surveillance study, and the Cancer Research Network Virtual Data Warehouse linked to registry data. Twelve potential indicators of recurrence were used to develop separate models for each cancer in each data source. Detection models maximized area under the ROC curve (AUC); timing models minimized average absolute error. Algorithms were compared by cancer type/data source, and contrasted with an existing binary detection rule. Detection model AUCs (>0.92) exceeded existing prediction rules. Timing models yielded absolute prediction errors that were small relative to follow-up time (differences by cancer type and dataset challenged efforts to create 1 common algorithm for all scenarios. Valid and reliable detection of recurrence using big data is feasible. These tools will enable extensive, novel research on quality, effectiveness, and outcomes for lung and colorectal cancer patients and those who develop recurrence.

  7. SmartCop: Enabling Smart Traffic Violations Ticketing in Vehicular Named Data Networks

    Directory of Open Access Journals (Sweden)

    Syed Hassan Ahmed

    2016-01-01

    Full Text Available Recently, various applications for Vehicular Ad hoc Networks (VANETs have been proposed and smart traffic violation ticketing is one of them. On the other hand, the new Information-Centric Networking (ICN architectures have emerged and been investigated into VANETs, such as Vehicular Named Data Networking (VNDN. However, the existing applications in VANETs are not suitable for VNDN paradigm due to the dependency on a “named content” instead of a current “host-centric” approach. Thus, we need to design the emerging and new architectures for VNDN applications. In this paper, we propose a smart traffic violation ticketing (TVT system for VNDN, named as SmartCop, that enables a cop vehicle (CV to issue tickets for traffic violation(s to the offender(s autonomously, once they are in the transmission range of that CV. The ticket issuing delay, messaging cost, and percentage of violations detected for varying number of vehicles, violators, CVs, and vehicles speeds are estimated through simulations. In addition, we provide a road map of future research directions for enabling safe driving experience in future cars aided with VNDN technology.

  8. Data-Mining Research in Education

    OpenAIRE

    Cheng, Jiechao

    2017-01-01

    As an interdisciplinary discipline, data mining (DM) is popular in education area especially when examining students' learning performances. It focuses on analyzing educational related data to develop models for improving learners' learning experiences and enhancing institutional effectiveness. Therefore, DM does help education institutions provide high-quality education for its learners. Applying data mining in education also known as educational data mining (EDM), which enables to better un...

  9. Data sharing for public health research: A qualitative study of industry and academia.

    Science.gov (United States)

    Saunders, Pamela A; Wilhelm, Erin E; Lee, Sinae; Merkhofer, Elizabeth; Shoulson, Ira

    2014-01-01

    Data sharing is a key biomedical research theme for the 21st century. Biomedical data sharing is the exchange of data among (non)affiliated parties under mutually agreeable terms to promote scientific advancement and the development of safe and effective medical products. Wide sharing of research data is important for scientific discovery, medical product development, and public health. Data sharing enables improvements in development of medical products, more attention to rare diseases, and cost-efficiencies in biomedical research. We interviewed 11 participants about their attitudes and beliefs about data sharing. Using a qualitative, thematic analysis approach, our analysis revealed a number of themes including: experiences, approaches, perceived challenges, and opportunities for sharing data.

  10. Development of a Web-Enabled Informatics Platform for Manipulation of Gene Expression Data

    National Research Council Canada - National Science Library

    Peel, Sheila A; Kopydlowski, Karen; Carel, Roland

    2004-01-01

    .... The Array Repository Data Analysis System (ARDAS 1.0) at Walter Reed Army Institute of Research is a web-enabled bioinformatic platform consisting of a Laboratory Information Management System (LIMS...

  11. Spatial data infrastructures at work analysing the spatial enablement of public sector processes

    CERN Document Server

    Dessers, Ezra

    2013-01-01

    In 'Spatial Data Infrastructures at Work', Ezra Dessers introduces spatial enablement as a key concept to describe the realisation of SDI objectives in the context of individual public sector processes. Drawing on four years of research, Dessers argues that it has become essential, even unavoidable, to manage and (re)design inter-organisational process chains in order to further advance the role of SDIs as an enabling platform for a spatially enabled society. Detailed case studies illustrate that the process he describes is the setting in which one can see the SDI at work.

  12. Archetype-based data warehouse environment to enable the reuse of electronic health record data.

    Science.gov (United States)

    Marco-Ruiz, Luis; Moner, David; Maldonado, José A; Kolstrup, Nils; Bellika, Johan G

    2015-09-01

    The reuse of data captured during health care delivery is essential to satisfy the demands of clinical research and clinical decision support systems. A main barrier for the reuse is the existence of legacy formats of data and the high granularity of it when stored in an electronic health record (EHR) system. Thus, we need mechanisms to standardize, aggregate, and query data concealed in the EHRs, to allow their reuse whenever they are needed. To create a data warehouse infrastructure using archetype-based technologies, standards and query languages to enable the interoperability needed for data reuse. The work presented makes use of best of breed archetype-based data transformation and storage technologies to create a workflow for the modeling, extraction, transformation and load of EHR proprietary data into standardized data repositories. We converted legacy data and performed patient-centered aggregations via archetype-based transformations. Later, specific purpose aggregations were performed at a query level for particular use cases. Laboratory test results of a population of 230,000 patients belonging to Troms and Finnmark counties in Norway requested between January 2013 and November 2014 have been standardized. Test records normalization has been performed by defining transformation and aggregation functions between the laboratory records and an archetype. These mappings were used to automatically generate open EHR compliant data. These data were loaded into an archetype-based data warehouse. Once loaded, we defined indicators linked to the data in the warehouse to monitor test activity of Salmonella and Pertussis using the archetype query language. Archetype-based standards and technologies can be used to create a data warehouse environment that enables data from EHR systems to be reused in clinical research and decision support systems. With this approach, existing EHR data becomes available in a standardized and interoperable format, thus opening a world

  13. Fostering Data Openness by Enabling Science: A Proposal for Micro-Funding

    Directory of Open Access Journals (Sweden)

    Brian Rappert

    2017-09-01

    Full Text Available In recent years, the promotion of data sharing has come with the recognition that not all scientists around the world are equally placed to partake in such activities. Notably, those within developing countries are sometimes regarded as experiencing hardware infrastructure challenges and data management skill shortages. Proposed remedies often focus on the provision of information and communication technology as well as enhanced data management training. Building on prior empirical social research undertaken in sub-Sahara Africa, this article provides a complementary but alternative proposal; namely, fostering data openness by enabling research. Towards this end, the underlying rationale is outlined for a ‘bottom-up’ system of research support that addresses the day-to-day demands in low-resourced environments. This approach draws on lessons from development financial assistance programs in recent decades. In doing so, this article provides an initial framework for science funding that call for holding together concerns for ensuring research can be undertaken in low-resourced laboratory environments with concerns about the data generated in such settings can be shared.

  14. CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and Collaboration

    Science.gov (United States)

    Seul, M.; Brazil, L.; Castronova, A. M.

    2017-12-01

    CUAHSI Data Services: Tools and Cyberinfrastructure for Water Data Discovery, Research and CollaborationEnabling research surrounding interdisciplinary topics often requires a combination of finding, managing, and analyzing large data sets and models from multiple sources. This challenge has led the National Science Foundation to make strategic investments in developing community data tools and cyberinfrastructure that focus on water data, as it is central need for many of these research topics. CUAHSI (The Consortium of Universities for the Advancement of Hydrologic Science, Inc.) is a non-profit organization funded by the National Science Foundation to aid students, researchers, and educators in using and managing data and models to support research and education in the water sciences. This presentation will focus on open-source CUAHSI-supported tools that enable enhanced data discovery online using advanced searching capabilities and computational analysis run in virtual environments pre-designed for educators and scientists so they can focus their efforts on data analysis rather than IT set-up.

  15. Enabling the Use of Authentic Scientific Data in the Classroom--Lessons Learned from the AccessData and Data Services Workshops

    Science.gov (United States)

    Lynds, S. E.; Buhr, S. M.; Ledley, T. S.

    2007-12-01

    Enabling the Use of Authentic Scientific Data in the Classroom--Lessons Learned from the AccessData and Data Services Workshops Since 2004, the annual AccessData and DLESE Data Services workshops have gathered scientists, data managers, technology specialists, teachers, and curriculum developers to work together creating classroom- ready scientific data modules. Teams of five (one participant from each of the five professions) develop topic- specific online educational units of the Earth Exploration Toolbook (serc.carleton.edu/eet/). Educators from middle schools through undergraduate colleges have been represented, as have scientific data professionals from many organizations across the United States. Extensive evaluation has been included in the design of each workshop. The evaluation results have been used each year to improve subsequent workshops. In addition to refining the format and process of the workshop itself, evaluation data collected reveal attendees' experiences using scientific data for educational purposes. Workshop attendees greatly value the opportunity to network with those of other professional roles in developing a real-world education project using scientific data. Educators appreciate the opportunity to work directly with scientists and technology specialists, while researchers and those in technical fields value the classroom expertise of the educators. Attendees' data use experiences are explored every year. Although bandwidth and connectivity were problems for data use in 2004, that has become much less common over time. The most common barriers to data use cited now are discoverability, data format problems, incomplete data sets, and poor documentation. Most attendees agree that the most useful types of online documentation and user support for scientific data are step-by-step instructions, examples, tutorials, and reference manuals. Satellite imagery and weather data were the most commonly used types of data, and these were often

  16. Co-researching with people with learning disabilities: an experience of involvement in qualitative data analysis.

    Science.gov (United States)

    Tuffrey-Wijne, Irene; Butler, Gary

    2010-06-01

    People with learning disabilities have been included in research as co-researchers since the 1990s. However, there is limited literature about the processes of involving people with learning disabilities in the more intellectual and analytical stages of the research process. To examine the potential contribution of people with learning disabilities to data analysis in qualitative research. This article is a reflection on one research experience. The two authors include one researcher with and one without learning disabilities. They each describe their experience and understanding of user involvement in analysing the data of an ethnographic study of people with learning disabilities who had cancer. The researcher with learning disabilities was given extensive vignettes and extracts from the research field notes, and was supported to extract themes, which were cross-compared with the analysis of other members of the research team. The researcher with learning disabilities coped well with the emotive content of the data and with the additional support provided, he was able to extract themes that added validity to the overall analysis. His contribution complemented those of the other members of the research team. There were unexpected benefits, in particular, in terms of a more reciprocal and supportive relationship between the two researchers. It is possible and valuable to extend involvement to data analysis, but to avoid tokenism and maintain academic rigour, there must be a clear rationale for such involvement. Extra support, time and costs must be planned for.

  17. Motivators, enablers, and barriers to building allied health research capacity

    Science.gov (United States)

    Pager, Susan; Holden, Libby; Golenko, Xanthe

    2012-01-01

    Purpose A sound, scientific base of high quality research is needed to inform service planning and decision making and enable improved policy and practice. However, some areas of health practice, particularly many of the allied health areas, are generally considered to have a low evidence base. In order to successfully build research capacity in allied health, a clearer understanding is required of what assists and encourages research as well as the barriers and challenges. Participants and methods This study used written surveys to collect data relating to motivators, enablers, and barriers to research capacity building. Respondents were asked to answer questions relating to them as individuals and other questions relating to their team. Allied health professionals were recruited from multidisciplinary primary health care teams in Queensland Health. Eighty-five participants from ten healthcare teams completed a written version of the research capacity and culture survey. Results The results of this study indicate that individual allied health professionals are more likely to report being motivated to do research by intrinsic factors such as a strong interest in research. Barriers they identified to research are more likely to be extrinsic factors such as workload and lack of time. Allied health professionals identified some additional factors that impact on their research capacity than those reported in the literature, such as a desire to keep at the “cutting edge” and a lack of exposure to research. Some of the factors influencing individuals to do research were different to those influencing teams. These results are discussed with reference to organizational behavior and theories of motivation. Conclusion Supporting already motivated allied health professional individuals and teams to conduct research by increased skills training, infrastructure, and quarantined time is likely to produce better outcomes for research capacity building investment. PMID

  18. New Paradigm for Macromolecular Crystallography Experiments at SSRL: Automated Crystal Screening And Remote Data Collection

    International Nuclear Information System (INIS)

    Soltis, S.M.; Cohen, A.E.; Deacon, A.; Eriksson, T.; Gonzalez, A.; McPhillips, S.; Chui, H.; Dunten, P.; Hollenbeck, M.; Mathews, I.; Miller, M.; Moorhead, P.; Phizackerley, R.P.; Smith, C.; Song, J.; Bedem, H. van dem; Ellis, P.; Kuhn, P.; McPhillips, T.; Sauter, N.; Sharp, K.

    2009-01-01

    Complete automation of the macromolecular crystallography experiment has been achieved at Stanford Synchrotron Radiation Lightsource (SSRL) through the combination of robust mechanized experimental hardware and a flexible control system with an intuitive user interface. These highly reliable systems have enabled crystallography experiments to be carried out from the researchers' home institutions and other remote locations while retaining complete control over even the most challenging systems. A breakthrough component of the system, the Stanford Auto-Mounter (SAM), has enabled the efficient mounting of cryocooled samples without human intervention. Taking advantage of this automation, researchers have successfully screened more than 200 000 samples to select the crystals with the best diffraction quality for data collection as well as to determine optimal crystallization and cryocooling conditions. These systems, which have been deployed on all SSRL macromolecular crystallography beamlines and several beamlines worldwide, are used by more than 80 research groups in remote locations, establishing a new paradigm for macromolecular crystallography experimentation.

  19. Experience-dependent plasticity from eye opening enables lasting, visual cortex-dependent enhancement of motion vision.

    Science.gov (United States)

    Prusky, Glen T; Silver, Byron D; Tschetter, Wayne W; Alam, Nazia M; Douglas, Robert M

    2008-09-24

    Developmentally regulated plasticity of vision has generally been associated with "sensitive" or "critical" periods in juvenile life, wherein visual deprivation leads to loss of visual function. Here we report an enabling form of visual plasticity that commences in infant rats from eye opening, in which daily threshold testing of optokinetic tracking, amid otherwise normal visual experience, stimulates enduring, visual cortex-dependent enhancement (>60%) of the spatial frequency threshold for tracking. The perceptual ability to use spatial frequency in discriminating between moving visual stimuli is also improved by the testing experience. The capacity for inducing enhancement is transitory and effectively limited to infancy; however, enhanced responses are not consolidated and maintained unless in-kind testing experience continues uninterrupted into juvenile life. The data show that selective visual experience from infancy can alone enable visual function. They also indicate that plasticity associated with visual deprivation may not be the only cause of developmental visual dysfunction, because we found that experientially inducing enhancement in late infancy, without subsequent reinforcement of the experience in early juvenile life, can lead to enduring loss of function.

  20. DataCite - A Global Registration Agency for Research Data

    DEFF Research Database (Denmark)

    Heller, Alfred

    2009-01-01

    Since 2005, the German National Library of Science and Technology (TIB) has offered a successful Digital Object Identifier (DOI) registration service for persistent identification of research data. In 2009, TIB, the British Library, the Library of the ETH Zurich, the French Institute for Scientif....... The goal of this cooperation is to establish a not-for-profit agency called DataCite that enables organisations to register research datasets and assign persistent identifiers to them, so that research datasets can be handled as independent, citable, unique scientific objects....

  1. Airborne Research Experience for Educators

    Science.gov (United States)

    Costa, V. B.; Albertson, R.; Smith, S.; Stockman, S. A.

    2009-12-01

    The Airborne Research Experience for Educators (AREE) Program, conducted by the NASA Dryden Flight Research Center Office of Education in partnership with the AERO Institute, NASA Teaching From Space Program, and California State University Fullerton, is a complete end-to-end residential research experience in airborne remote sensing and atmospheric science. The 2009 program engaged ten secondary educators who specialize in science, technology, engineering or mathematics in a 6-week Student Airborne Research Program (SARP) offered through NSERC. Educators participated in collection of in-flight remote sensor data during flights aboard the NASA DC-8 as well as in-situ research on atmospheric chemistry (bovine emissions of methane); algal blooms (remote sensing to determine location and degree of blooms for further in-situ analysis); and crop classification (exploration of how drought conditions in Central California have impacted almond and cotton crops). AREE represents a unique model of the STEM teacher-as-researcher professional development experience because it asks educators to participate in a research experience and then translate their experiences into classroom practice through the design, implementation, and evaluation of instructional materials that emphasize the scientific research process, inquiry-based investigations, and manipulation of real data. Each AREE Master Educator drafted a Curriculum Brief, Teachers Guide, and accompanying resources for a topic in their teaching assignment Currently, most professional development programs offer either a research experience OR a curriculum development experience. The dual nature of the AREE model engaged educators in both experiences. Educators’ content and pedagogical knowledge of STEM was increased through the review of pertinent research articles during the first week, attendance at lectures and workshops during the second week, and participation in the airborne and in-situ research studies, data

  2. Mining the Mind Research Network: A Novel Framework for Exploring Large Scale, Heterogeneous Translational Neuroscience Research Data Sources

    Science.gov (United States)

    Bockholt, Henry J.; Scully, Mark; Courtney, William; Rachakonda, Srinivas; Scott, Adam; Caprihan, Arvind; Fries, Jill; Kalyanam, Ravi; Segall, Judith M.; de la Garza, Raul; Lane, Susan; Calhoun, Vince D.

    2009-01-01

    A neuroinformatics (NI) system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN), database system has been designed and improved through our experience with 200 research studies and 250 researchers from seven different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining. PMID:20461147

  3. Mining the mind research network: a novel framework for exploring large scale, heterogeneous translational neuroscience research data sources.

    Directory of Open Access Journals (Sweden)

    Henry Jeremy Bockholt

    2010-04-01

    Full Text Available A neuroinformatics (NI system is critical to brain imaging research in order to shorten the time between study conception and results. Such a NI system is required to scale well when large numbers of subjects are studied. Further, when multiple sites participate in research projects organizational issues become increasingly difficult. Optimized NI applications mitigate these problems. Additionally, NI software enables coordination across multiple studies, leveraging advantages potentially leading to exponential research discoveries. The web-based, Mind Research Network (MRN, database system has been designed and improved through our experience with 200 research studies and 250 researchers from 7 different institutions. The MRN tools permit the collection, management, reporting and efficient use of large scale, heterogeneous data sources, e.g., multiple institutions, multiple principal investigators, multiple research programs and studies, and multimodal acquisitions. We have collected and analyzed data sets on thousands of research participants and have set up a framework to automatically analyze the data, thereby making efficient, practical data mining of this vast resource possible. This paper presents a comprehensive framework for capturing and analyzing heterogeneous neuroscience research data sources that has been fully optimized for end-users to perform novel data mining.

  4. Research Data Alliance: Understanding Big Data Analytics Applications in Earth Science

    Science.gov (United States)

    Riedel, Morris; Ramachandran, Rahul; Baumann, Peter

    2014-01-01

    The Research Data Alliance (RDA) enables data to be shared across barriers through focused working groups and interest groups, formed of experts from around the world - from academia, industry and government. Its Big Data Analytics (BDA) interest groups seeks to develop community based recommendations on feasible data analytics approaches to address scientific community needs of utilizing large quantities of data. BDA seeks to analyze different scientific domain applications (e.g. earth science use cases) and their potential use of various big data analytics techniques. These techniques reach from hardware deployment models up to various different algorithms (e.g. machine learning algorithms such as support vector machines for classification). A systematic classification of feasible combinations of analysis algorithms, analytical tools, data and resource characteristics and scientific queries will be covered in these recommendations. This contribution will outline initial parts of such a classification and recommendations in the specific context of the field of Earth Sciences. Given lessons learned and experiences are based on a survey of use cases and also providing insights in a few use cases in detail.

  5. Nationwide Buildings Energy Research enabled through an integrated Data Intensive Scientific Workflow and Advanced Analysis Environment

    Energy Technology Data Exchange (ETDEWEB)

    Kleese van Dam, Kerstin [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Lansing, Carina S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Elsethagen, Todd O. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hathaway, John E. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Guillen, Zoe C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Dirks, James A. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Skorski, Daniel C. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Stephan, Eric G. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gorrissen, Willy J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gorton, Ian [Carnegie Mellon Univ., Pittsburgh, PA (United States); Liu, Yan [Concordia Univ., Montreal, QC (Canada)

    2014-01-28

    Modern workflow systems enable scientists to run ensemble simulations at unprecedented scales and levels of complexity, allowing them to study system sizes previously impossible to achieve, due to the inherent resource requirements needed for the modeling work. However as a result of these new capabilities the science teams suddenly also face unprecedented data volumes that they are unable to analyze with their existing tools and methodologies in a timely fashion. In this paper we will describe the ongoing development work to create an integrated data intensive scientific workflow and analysis environment that offers researchers the ability to easily create and execute complex simulation studies and provides them with different scalable methods to analyze the resulting data volumes. The integration of simulation and analysis environments is hereby not only a question of ease of use, but supports fundamental functions in the correlated analysis of simulation input, execution details and derived results for multi-variant, complex studies. To this end the team extended and integrated the existing capabilities of the Velo data management and analysis infrastructure, the MeDICi data intensive workflow system and RHIPE the R for Hadoop version of the well-known statistics package, as well as developing a new visual analytics interface for the result exploitation by multi-domain users. The capabilities of the new environment are demonstrated on a use case that focusses on the Pacific Northwest National Laboratory (PNNL) building energy team, showing how they were able to take their previously local scale simulations to a nationwide level by utilizing data intensive computing techniques not only for their modeling work, but also for the subsequent analysis of their modeling results. As part of the PNNL research initiative PRIMA (Platform for Regional Integrated Modeling and Analysis) the team performed an initial 3 year study of building energy demands for the US Eastern

  6. Data management and global change research: Technology and infrastructure

    International Nuclear Information System (INIS)

    Morrissey, W.A.

    1993-01-01

    There is a consensus among many scientists who would perform global change research that global-scale scientific data management programs and enabling policies need to be developed and implemented concomitantly with, if not in advance of, global change research programs. They are hopeful that US Federal government policies for scientific and technical data and information management will provide timely archival, analysis, and dissemination of global change research data and will enable them to share that data with colleagues, internationally. Federal data managers believe that data management technology and infrastructure requirements for global change research programs can be met through existing or planned enhancements to systems in operation used for scientific data gathering, processing, and dissemination. Scientists are concerned, however, that because of the scope and diversity of global change research programs entirely new systems and approaches to data management may need to be devised

  7. New Catalog of Resources Enables Paleogeosciences Research

    Science.gov (United States)

    Lingo, R. C.; Horlick, K. A.; Anderson, D. M.

    2014-12-01

    The 21st century promises a new era for scientists of all disciplines, the age where cyber infrastructure enables research and education and fuels discovery. EarthCube is a working community of over 2,500 scientists and students of many Earth Science disciplines who are looking to build bridges between disciplines. The EarthCube initiative will create a digital infrastructure that connects databases, software, and repositories. A catalog of resources (databases, software, repositories) has been produced by the Research Coordination Network for Paleogeosciences to improve the discoverability of resources. The Catalog is currently made available within the larger-scope CINERGI geosciences portal (http://hydro10.sdsc.edu/geoportal/catalog/main/home.page). Other distribution points and web services are planned, using linked data, content services for the web, and XML descriptions that can be harvested using metadata protocols. The databases provide searchable interfaces to find data sets that would otherwise remain dark data, hidden in drawers and on personal computers. The software will be described in catalog entries so just one click will lead users to methods and analytical tools that many geoscientists were unaware of. The repositories listed in the Paleogeosciences Catalog contain physical samples found all across the globe, from natural history museums to the basements of university buildings. EarthCube has over 250 databases, 300 software systems, and 200 repositories which will grow in the coming year. When completed, geoscientists across the world will be connected into a productive workflow for managing, sharing, and exploring geoscience data and information that expedites collaboration and innovation within the paleogeosciences, potentially bringing about new interdisciplinary discoveries.

  8. Experiences with a researcher-centric ELN† †Electronic supplementary information (ESI) available. See DOI: 10.1039/c4sc02128b Click here for additional data file.

    Science.gov (United States)

    Badiola, Katrina A.; Bird, Colin; Brocklesby, William S.; Casson, John; Chapman, Richard T.; Coles, Simon J.; Cronshaw, James R.; Fisher, Adam; Gloria, Danmar; Grossel, Martin C.; Hibbert, D. Brynn; Knight, Nicola; Mapp, Lucy K.; Marazzi, Luke; Matthews, Brian; Milsted, Andy; Minns, Russell S.; Mueller, Karl T.; Murphy, Kelly; Parkinson, Tim; Quinnell, Rosanne; Robinson, John S.; Robertson, Murray N.; Robins, Michael; Springate, Emma; Tizzard, Graham; Todd, Matthew H.; Williamson, Alice E.; Willoughby, Cerys; Yang, Erica; Ylioja, Paul M.

    2015-01-01

    Electronic Laboratory Notebooks (ELNs) are progressively replacing traditional paper books in both commercial research establishments and academic institutions. University researchers require specific features from ELNs, given the need to promote cross-institutional collaborative working, to enable the sharing of procedures and results, and to facilitate publication. The LabTrove ELN, which we use as our exemplar, was designed to be researcher-centric (i.e., not only aimed at the individual researcher's basic needs rather than to a specific institutional or subject or disciplinary agenda, but also able to be tailored because it is open source). LabTrove is being used in a heterogeneous set of academic laboratories, for a range of purposes, including analytical chemistry, X-ray studies, drug discovery and a biomaterials project. Researchers use the ELN for recording experiments, preserving data collected, and for project coordination. This perspective article describes the experiences of those researchers from several viewpoints, demonstrating how a web-based open source electronic notebook can meet the diverse needs of academic researchers. PMID:29308130

  9. Practical Use of the Eye Camera in Pedagogical Research (Processing of Selected Data Using the Eye Tracking Method

    Directory of Open Access Journals (Sweden)

    Škrabánková Jana

    2016-06-01

    Full Text Available The paper deals with author’s pilot experiments using the eye tracking method for the primary school children examination. This method enables to gain a large amount of research data based on the tested people’s eye movements monitoring. In the paper, there are processed chosen research data of four gifted students’ examination in the context of their mathematical and logical intelligence.

  10. ArrayWiki: an enabling technology for sharing public microarray data repositories and meta-analyses

    Science.gov (United States)

    Stokes, Todd H; Torrance, JT; Li, Henry; Wang, May D

    2008-01-01

    Background A survey of microarray databases reveals that most of the repository contents and data models are heterogeneous (i.e., data obtained from different chip manufacturers), and that the repositories provide only basic biological keywords linking to PubMed. As a result, it is difficult to find datasets using research context or analysis parameters information beyond a few keywords. For example, to reduce the "curse-of-dimension" problem in microarray analysis, the number of samples is often increased by merging array data from different datasets. Knowing chip data parameters such as pre-processing steps (e.g., normalization, artefact removal, etc), and knowing any previous biological validation of the dataset is essential due to the heterogeneity of the data. However, most of the microarray repositories do not have meta-data information in the first place, and do not have a a mechanism to add or insert this information. Thus, there is a critical need to create "intelligent" microarray repositories that (1) enable update of meta-data with the raw array data, and (2) provide standardized archiving protocols to minimize bias from the raw data sources. Results To address the problems discussed, we have developed a community maintained system called ArrayWiki that unites disparate meta-data of microarray meta-experiments from multiple primary sources with four key features. First, ArrayWiki provides a user-friendly knowledge management interface in addition to a programmable interface using standards developed by Wikipedia. Second, ArrayWiki includes automated quality control processes (caCORRECT) and novel visualization methods (BioPNG, Gel Plots), which provide extra information about data quality unavailable in other microarray repositories. Third, it provides a user-curation capability through the familiar Wiki interface. Fourth, ArrayWiki provides users with simple text-based searches across all experiment meta-data, and exposes data to search engine crawlers

  11. DataShare: Empowering Researcher Data Curation

    Directory of Open Access Journals (Sweden)

    Stephen Abrams

    2014-07-01

    Full Text Available Researchers are increasingly being asked to ensure that all products of research activity – not just traditional publications – are preserved and made widely available for study and reuse as a precondition for publication or grant funding, or to conform to disciplinary best practices. In order to conform to these requirements, scholars need effective, easy-to-use tools and services for the long-term curation of their research data. The DataShare service, developed at the University of California, is being used by researchers to: (1 prepare for curation by reviewing best practice recommendations for the acquisition or creation of digital research data; (2 select datasets using intuitive file browsing and drag-and-drop interfaces; (3 describe their data for enhanced discoverability in terms of the DataCite metadata schema; (4 preserve their data by uploading to a public access collection in the UC3 Merritt curation repository; (5 cite their data in terms of persistent and globally-resolvable DOI identifiers; (6 expose their data through registration with well-known abstracting and indexing services and major internet search engines; (7 control the dissemination of their data through enforceable data use agreements; and (8 discover and retrieve datasets of interest through a faceted search and browse environment. Since the widespread adoption of effective data management practices is highly dependent on ease of use and integration into existing individual, institutional, and disciplinary workflows, the emphasis throughout the design and implementation of DataShare is to provide the highest level of curation service with the lowest possible technical barriers to entry by individual researchers. By enabling intuitive, self-service access to data curation functions, DataShare helps to contribute to more widespread adoption of good data curation practices that are critical to open scientific inquiry, discourse, and advancement.

  12. [Socianalytical device: intervention instrument and data collection in qualitative research in nursing].

    Science.gov (United States)

    Spagnol, Carla Aparecida; L'Abbate, Solange; Monceau, Gilles; Jovic, Ljiljana

    2016-03-01

    The aims of this paper is to describe and to analyze the use of a socioanalytical device as a data collection too as well as a space of professional practice and work relations analysis, with nurses from a School Hospital of the Minas Gerais Federal University, Brazil. The qualitative approach was chosen to develop an intervention research with Institutional Analysis as theoretical and methodological framework. In the first stage of data collection, an exploratory research was carried out through a questionnaire and, in the second phase, a socianalytical device was built in 5 meetings that took place during two months. For the nurses, the analysis device has enabled personal and professional growth; to review positions; to exchange experience and to reflect on their own problems through the experience of other colleagues. We conclude that the socioanalytical device was a space for discussion, for analysis of professional practice and was the methodological strategy for data collection in this research. It has allowed the creation and recreation of forms of intervention, the production of knowledge and has improved quality of health work.

  13. Laboratory science with space data accessing and using space-experiment data

    CERN Document Server

    van Loon, Jack J W A; Zell, Martin; Beysens, Daniel

    2011-01-01

    For decades experiments conducted on space stations like MIR and the ISS have been gathering data in many fields of research in the natural sciences, medicine and engineering. The European Union-sponsored ULISSE project focused on exploring the wealth of unique experimental data provided by revealing raw and metadata from these studies via an Internet Portal. This book complements the portal. It serves as a handbook of space experiments and describes the various types of experimental infrastructure areas of research in the life and physical sciences and technology space missions that hosted scientific experiments the types and structures of the data produced and how one can access the data through ULISSE for further research. The book provides an overview of the wealth of space experiment data that can be used for additional research and will inspire academics (e.g. those looking for topics for their PhD thesis) and research departments in companies for their continued development.

  14. Enabling Research Network Connectivity to Clouds with Virtual Router Technology

    Science.gov (United States)

    Seuster, R.; Casteels, K.; Leavett-Brown, CR; Paterson, M.; Sobie, RJ

    2017-10-01

    The use of opportunistic cloud resources by HEP experiments has significantly increased over the past few years. Clouds that are owned or managed by the HEP community are connected to the LHCONE network or the research network with global access to HEP computing resources. Private clouds, such as those supported by non-HEP research funds are generally connected to the international research network; however, commercial clouds are either not connected to the research network or only connect to research sites within their national boundaries. Since research network connectivity is a requirement for HEP applications, we need to find a solution that provides a high-speed connection. We are studying a solution with a virtual router that will address the use case when a commercial cloud has research network connectivity in a limited region. In this situation, we host a virtual router in our HEP site and require that all traffic from the commercial site transit through the virtual router. Although this may increase the network path and also the load on the HEP site, it is a workable solution that would enable the use of the remote cloud for low I/O applications. We are exploring some simple open-source solutions. In this paper, we present the results of our studies and how it will benefit our use of private and public clouds for HEP computing.

  15. Contextual Interaction Design Research: Enabling HCI

    OpenAIRE

    Murer , Martin; Meschtscherjakov , Alexander; Fuchsberger , Verena; Giuliani , Manuel; Neureiter , Katja; Moser , Christiane; Aslan , Ilhan; Tscheligi , Manfred

    2015-01-01

    International audience; Human-Computer Interaction (HCI) has always been about humans, their needs and desires. Contemporary HCI thinking investigates interactions in everyday life and puts an emphasis on the emotional and experiential qualities of interactions. At the Center for Human-Computer Interaction we seek to bridge meandering strands in the field by following a guiding metaphor that shifts focus to what has always been the core quality of our research field: Enabling HCI, as a leitmo...

  16. Arctic research in the classroom: A teacher's experiences translated into data driven lesson plans

    Science.gov (United States)

    Kendrick, E. O.; Deegan, L.

    2011-12-01

    Incorporating research into high school science classrooms can promote critical thinking skills and provide a link between students and the scientific community. Basic science concepts become more relevant to students when taught in the context of research. A vital component of incorporating current research into classroom lessons is involving high school teachers in authentic research. The National Science Foundation sponsored Research Experience for Teachers (RET) program has inspired me to bring research to my classroom, communicate the importance of research in the classroom to other teachers and create lasting connections between students and the research community. Through my experiences as an RET at Toolik Field Station in Alaska, I have created several hands-on lessons and laboratory activities that are based on current arctic research and climate change. Each lesson uses arctic research as a theme for exemplifying basic biology concepts as well as increasing awareness of current topics such as climate change. For instance, data collected on the Kuparuk River will be incorporated into classroom activities that teach concepts such as primary production, trophic levels in a food chain and nutrient cycling within an ecosystem. Students will not only understand the biological concepts but also recognize the ecological implications of the research being conducted in the arctic. By using my experience in arctic research as a template, my students will gain a deeper understanding of the scientific process. I hope to create a crucial link of information between the science community and science education in public schools.

  17. Planning for an Integrated Research Experiment

    International Nuclear Information System (INIS)

    Barnard, J.J.; Ahle, L.E.; Bangerter, R.O.; Bieniosek, F.M.; Celata, C.M.; Faltens, A.; Friedman, A.; Grote, D.P.; Haber, I.; Henestroza, E.; Kishek, R.A.; Hoon, M.J.L. de; Karpenko, V.P.; Kwan, J.W.; Lee, E.P.; Logan, B.G.; Lund, S.M.; Meier, W.R.; Molvik, A.W.; Sangster, T.C.; Seidl, P.A.; Sharp, W.M.

    2000-01-01

    The authors describe the goals and research program leading to the Heavy Ion Integrated Research Experiment (IRE). They review the basic constraints which lead to a design and give examples of parameters and capabilities of an IRE. We also show design tradeoffs generated by the systems code IBEAM. A multi-pronged Phase 1 research effort is laying the groundwork for the Integrated Research Experiment. Experiment, technology development, theory, simulation, and systems studies are all playing major roles in this Phase I research. The key research areas are: (1) Source and injector (for investigation of a high brightness, multiple beam, low cost injector); (2) High current transport (to examine effects at full driver-scale line charge density, including the maximization of the beam filling-factor and control of electrons); (3) Enabling technology development (low cost and high performance magnetic core material, superconducting magnetic quadrupole arrays, insulators, and pulsers); and (4) Beam simulations and theory (for investigations of beam matching, specification of accelerator errors, studies of emittance growth, halo, and bunch compression, in the accelerator, and neutralization methods, stripping effects, spot size minimization in the chamber); and (5) Systems optimization (minimization of cost and maximization of pulse energy and beam intensity). They have begun the process of designing, simulating, and optimizing the next major heavy-ion induction accelerator, the IRE. This accelerator facility will, in turn, help provide the basis to proceed to the next step in the development of IFE as an attractive source of fusion energy

  18. An innovative methodology for the transmission of information, using Sensor Web Enablement, from ongoing research vessels.

    Science.gov (United States)

    Sorribas, Jordi; Sinquin, Jean Marc; Diviacco, Paolo; De Cauwer, Karien; Danobeitia, Juanjo; Olive, Joan; Bermudez, Luis

    2013-04-01

    Research vessels are sophisticated laboratories with complex data acquisition systems for a variety of instruments and sensors that acquire real-time information of many different parameters and disciplines. The overall data and metadata acquired commonly spread using well-established standards for data centers; however, the instruments and systems on board are not always well described and it may miss significant information. Thus, important information such as instrument calibration or operational data often does not reach to the data center. The OGC Sensor Web Enablement standards provide solutions to serve complex data along with the detailed description of the process used to obtain them. We show an innovative methodology on how to use Sensor Web Enablement standards to describe and serve information from the research vessels, the data acquisition systems used onboard, and data sets resulting from the onboard work. This methodology is designed to be used in research vessels, but also applies to data centers to avoid loss of information in between The proposed solution considers (I) the difficulty to describe a multidisciplinary and complex mobile sensor system, (II) it can be easily integrated with data acquisition systems onboard, (III) it uses the complex and incomplete typical vocabulary in marine disciplines, (IV) it provides contacts with the data and metadata services at the Data Centers, and (V) it manages the configuration changes with time of the instrument.

  19. Collaborative Web-Enabled GeoAnalytics Applied to OECD Regional Data

    Science.gov (United States)

    Jern, Mikael

    Recent advances in web-enabled graphics technologies have the potential to make a dramatic impact on developing collaborative geovisual analytics (GeoAnalytics). In this paper, tools are introduced that help establish progress initiatives at international and sub-national levels aimed at measuring and collaborating, through statistical indicators, economic, social and environmental developments and to engage both statisticians and the public in such activities. Given this global dimension of such a task, the “dream” of building a repository of progress indicators, where experts and public users can use GeoAnalytics collaborative tools to compare situations for two or more countries, regions or local communities, could be accomplished. While the benefits of GeoAnalytics tools are many, it remains a challenge to adapt these dynamic visual tools to the Internet. For example, dynamic web-enabled animation that enables statisticians to explore temporal, spatial and multivariate demographics data from multiple perspectives, discover interesting relationships, share their incremental discoveries with colleagues and finally communicate selected relevant knowledge to the public. These discoveries often emerge through the diverse backgrounds and experiences of expert domains and are precious in a creative analytics reasoning process. In this context, we introduce a demonstrator “OECD eXplorer”, a customized tool for interactively analyzing, and collaborating gained insights and discoveries based on a novel story mechanism that capture, re-use and share task-related explorative events.

  20. Fundamental Research Applied To Enable Hardware Performance in Microgravity

    Science.gov (United States)

    Sheredy, William A.

    2005-01-01

    NASA sponsors microgravity research to generate knowledge in physical sciences. In some cases, that knowledge must be applied to enable future research. This article describes one such example. The Dust and Aerosol measurement Feasibility Test (DAFT) is a risk-mitigation experiment developed at the NASA Glenn Research Center by NASA and ZIN Technologies, Inc., in support of the Smoke Aerosol Measurement Experiment (SAME). SAME is an investigation that is being designed for operation in the Microgravity Science Glovebox aboard the International Space Station (ISS). The purpose of DAFT is to evaluate the performance of P-Trak (TSI Incorporated, Shoreview, MN)--a commercially available condensation nuclei counter and a key SAME diagnostic- -in long-duration microgravity because of concerns about its ability to operate properly in that environment. If its microgravity performance is proven, this device will advance the state of the art in particle measurement capabilities for space vehicles and facilities, such as aboard the ISS. The P-Trak, a hand-held instrument, can count individual particles as small as 20 nm in diameter in an aerosol stream. Particles are drawn into the device by a built-in suction pump. Upon entering the instrument, these particles pass through a saturator tube where they mix with an alcohol vapor (see the following figure). This mixture then flows through a cooled condenser tube where some of the alcohol condenses onto the sample particles, and the droplets grow in a controlled fashion until they are large enough to be counted. These larger droplets pass through an internal nozzle and past a focused laser beam, producing flashes of light that are sensed by a photodetector and then counted to determine particle number concentration. The operation of the instrument depends on the proper internal flow and recycling of isopropyl alcohol in both the vapor and liquid phases.

  1. Collaborative mining and interpretation of large-scale data for biomedical research insights.

    Directory of Open Access Journals (Sweden)

    Georgia Tsiliki

    Full Text Available Biomedical research becomes increasingly interdisciplinary and collaborative in nature. Researchers need to efficiently and effectively collaborate and make decisions by meaningfully assembling, mining and analyzing available large-scale volumes of complex multi-faceted data residing in different sources. In line with related research directives revealing that, in spite of the recent advances in data mining and computational analysis, humans can easily detect patterns which computer algorithms may have difficulty in finding, this paper reports on the practical use of an innovative web-based collaboration support platform in a biomedical research context. Arguing that dealing with data-intensive and cognitively complex settings is not a technical problem alone, the proposed platform adopts a hybrid approach that builds on the synergy between machine and human intelligence to facilitate the underlying sense-making and decision making processes. User experience shows that the platform enables more informed and quicker decisions, by displaying the aggregated information according to their needs, while also exploiting the associated human intelligence.

  2. Linked Data Applications Through Ontology Based Data Access in Clinical Research.

    Science.gov (United States)

    Kock-Schoppenhauer, Ann-Kristin; Kamann, Christian; Ulrich, Hannes; Duhm-Harbeck, Petra; Ingenerf, Josef

    2017-01-01

    Clinical care and research data are widely dispersed in isolated systems based on heterogeneous data models. Biomedicine predominantly makes use of connected datasets based on the Semantic Web paradigm. Initiatives like Bio2RDF created Resource Description Framework (RDF) versions of Omics resources, enabling sophisticated Linked Data applications. In contrast, electronic healthcare records (EHR) data are generated and processed in diverse clinical subsystems within hospital information systems (HIS). Usually, each of them utilizes a relational database system with a different proprietary schema. Semantic integration and access to the data is hardly possible. This paper describes ways of using Ontology Based Data Access (OBDA) for bridging the semantic gap between existing raw data and user-oriented views supported by ontology-based queries. Based on mappings between entities of data schemas and ontologies data can be made available as materialized or virtualized RDF triples ready for querying and processing. Our experiments based on CentraXX for biobank and study management demonstrate the advantages of abstracting away from low level details and semantic mediation. Furthermore, it becomes clear that using a professional platform for Linked Data applications is recommended due to the inherent complexity, the inconvenience to confront end users with SPARQL, and scalability and performance issues.

  3. Enabling search services on outsourced private spatial data

    KAUST Repository

    Yiu, Man Lung; Ghinita, Gabriel; Jensen, Christian Sø ndergaard; Kalnis, Panos

    2009-01-01

    Cloud computing services enable organizations and individuals to outsource the management of their data to a service provider in order to save on hardware investments and reduce maintenance costs. Only authorized users are allowed to access the data

  4. Toward genome-enabled mycology.

    Science.gov (United States)

    Hibbett, David S; Stajich, Jason E; Spatafora, Joseph W

    2013-01-01

    Genome-enabled mycology is a rapidly expanding field that is characterized by the pervasive use of genome-scale data and associated computational tools in all aspects of fungal biology. Genome-enabled mycology is integrative and often requires teams of researchers with diverse skills in organismal mycology, bioinformatics and molecular biology. This issue of Mycologia presents the first complete fungal genomes in the history of the journal, reflecting the ongoing transformation of mycology into a genome-enabled science. Here, we consider the prospects for genome-enabled mycology and the technical and social challenges that will need to be overcome to grow the database of complete fungal genomes and enable all fungal biologists to make use of the new data.

  5. A federated semantic metadata registry framework for enabling interoperability across clinical research and care domains.

    Science.gov (United States)

    Sinaci, A Anil; Laleci Erturkmen, Gokce B

    2013-10-01

    In order to enable secondary use of Electronic Health Records (EHRs) by bridging the interoperability gap between clinical care and research domains, in this paper, a unified methodology and the supporting framework is introduced which brings together the power of metadata registries (MDR) and semantic web technologies. We introduce a federated semantic metadata registry framework by extending the ISO/IEC 11179 standard, and enable integration of data element registries through Linked Open Data (LOD) principles where each Common Data Element (CDE) can be uniquely referenced, queried and processed to enable the syntactic and semantic interoperability. Each CDE and their components are maintained as LOD resources enabling semantic links with other CDEs, terminology systems and with implementation dependent content models; hence facilitating semantic search, much effective reuse and semantic interoperability across different application domains. There are several important efforts addressing the semantic interoperability in healthcare domain such as IHE DEX profile proposal, CDISC SHARE and CDISC2RDF. Our architecture complements these by providing a framework to interlink existing data element registries and repositories for multiplying their potential for semantic interoperability to a greater extent. Open source implementation of the federated semantic MDR framework presented in this paper is the core of the semantic interoperability layer of the SALUS project which enables the execution of the post marketing safety analysis studies on top of existing EHR systems. Copyright © 2013 Elsevier Inc. All rights reserved.

  6. Geo-Enabled, Mobile Services

    DEFF Research Database (Denmark)

    Jensen, Christian Søndergaard

    2006-01-01

    We are witnessing the emergence of a global infrastructure that enables the widespread deployment of geo-enabled, mobile services in practice. At the same time, the research community has also paid increasing attention to data management aspects of mobile services. This paper offers me...

  7. Interoperable Access to NCAR Research Data Archive Collections

    Science.gov (United States)

    Schuster, D.; Ji, Z.; Worley, S. J.; Manross, K.

    2014-12-01

    The National Center for Atmospheric Research (NCAR) Research Data Archive (RDA) provides free access to 600+ observational and gridded dataset collections. The RDA is designed to support atmospheric and related sciences research, updated frequently where datasets have ongoing production, and serves data to 10,000 unique users annually. The traditional data access options include web-based direct archive file downloads, user selected data subsets and format conversions produced by server-side computations, and client and cURL-based APIs for routine scripted data retrieval. To enhance user experience and utility, the RDA now also offers THREDDS Data Server (TDS) access for many highly valued dataset collections. TDS offered datasets are presented as aggregations, enabling users to access an entire dataset collection, that can be comprised of 1000's of files, through a single virtual file. The OPeNDAP protocol, supported by the TDS, allows compatible tools to open and access these virtual files remotely, and make the native data file format transparent to the end user. The combined functionality (TDS/OPeNDAP) gives users the ability to browse, select, visualize, and download data from a complete dataset collection without having to transfer archive files to a local host. This presentation will review the TDS basics and describe the specific TDS implementation on the RDA's diverse archive of GRIB-1, GRIB-2, and gridded NetCDF formatted dataset collections. Potential future TDS implementation on in-situ observational dataset collections will be discussed. Illustrative sample cases will be used to highlight the end users benefits from this interoperable data access to the RDA.

  8. Enabling Data-Driven Methodologies Across the Data Lifecycle and Ecosystem

    Science.gov (United States)

    Doyle, R. J.; Crichton, D.

    2017-12-01

    NASA has unlocked unprecedented scientific knowledge through exploration of the Earth, our solar system, and the larger universe. NASA is generating enormous amounts of data that are challenging traditional approaches to capturing, managing, analyzing and ultimately gaining scientific understanding from science data. New architectures, capabilities and methodologies are needed to span the entire observing system, from spacecraft to archive, while integrating data-driven discovery and analytic capabilities. NASA data have a definable lifecycle, from remote collection point to validated accessibility in multiple archives. Data challenges must be addressed across this lifecycle, to capture opportunities and avoid decisions that may limit or compromise what is achievable once data arrives at the archive. Data triage may be necessary when the collection capacity of the sensor or instrument overwhelms data transport or storage capacity. By migrating computational and analytic capability to the point of data collection, informed decisions can be made about which data to keep; in some cases, to close observational decision loops onboard, to enable attending to unexpected or transient phenomena. Along a different dimension than the data lifecycle, scientists and other end-users must work across an increasingly complex data ecosystem, where the range of relevant data is rarely owned by a single institution. To operate effectively, scalable data architectures and community-owned information models become essential. NASA's Planetary Data System is having success with this approach. Finally, there is the difficult challenge of reproducibility and trust. While data provenance techniques will be part of the solution, future interactive analytics environments must support an ability to provide a basis for a result: relevant data source and algorithms, uncertainty tracking, etc., to assure scientific integrity and to enable confident decision making. Advances in data science offer

  9. An overview of enabling technology research in the United States

    International Nuclear Information System (INIS)

    Baker, Charles C.

    2002-01-01

    The mission of the US Fusion Energy Sciences Program is to advance plasma science, fusion science, and fusion technology--the knowledge base needed for an economically and environmentally attractive fusion energy source. In support of this overall mission, the Enabling Technology Program in the US incorporates both near and long term R and D, contributes to material and engineering sciences as well as technology development, contributes to spin-off applications, and performs global systems assessments and focused design studies. This work supports both magnetic and inertial fusion energy (IFE) concepts. The Enabling Technology research mission is to contribute to the national science and technology base by developing the enabling technology for existing and next-step experimental devices, by exploring and understanding key materials and technology feasibility issues for attractive fusion power sources, by conducting advanced design studies that integrate the wealth of our understanding to guide R and D priorities and by developing design solutions for next-step and future devices. The Enabling Technology Program Plan is organized around five elements: plasma technologies, fusion (chamber) technologies, materials sciences, advanced design, and IFE chamber and target technologies. The principal technical features and research objectives are described for each element

  10. Basic Research on Selecting ISDC Activity for Decommissioning Costing in KRR-2 Decommissioning Project Experience Data

    Energy Technology Data Exchange (ETDEWEB)

    Song, Chan-Ho; Park, Hee-Seong; Jin, Hyung-Gon; Park, Seung-Kook [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

    2015-10-15

    KAERI is performing research for calculation of expected time of a decommissioning work and evaluation of decommissioning cost and this research calculate a decommissioning work unit productivity based on the experience data of decommissioning activity for KRR-2. The KAERI be used to calculate the decommissioning cost and manage the experience data from the decommissioning activity through the Decommissioning Information Management System (DECOMMIS), Decommissioning Facility Characterization DB System (DEFACS), and Decommissioning Work-unit Productivity Calculation System (DEWOCS). In this paper, the methodology was presented how select the ISDC activities in dismantling work procedures of a 'removal of radioactive concrete'. The reason to select the 'removal of radioactive concrete' is main key activity and generates the amount of radioactive waste. This data will take advantage of the cost estimation after the code for the selected items derived ISDC. There are various efforts for decommissioning costing in each country. In particular, OECD/NEA recommends decommissioning cost estimation using the ISDC and IAEA provides for Cost Estimation for Research Reactors in Excel (CERREX) program that anyone is easy to use the cost evaluation from a limited decommissioning experience in domestic. In the future, for the decommissioning cost evaluation, the ISDC will be used more widely in a strong position. This paper has described a method for selecting the ISDC item from the actual dismantling work procedures.

  11. Males in Enabling: Painting a portrait through narrative

    Directory of Open Access Journals (Sweden)

    Frank Armstrong

    2018-02-01

    Full Text Available The number of males entering higher education via an enabling pathway is slowly increasing; yet, males still battle with the anti-intellectual attitude that is prevalent in regional areas of Australia. Previous research undertaken by the authors began exploring the factors that inhibited or enhanced the male experience within an enabling course. This paper expands upon this research with a deeper focus on the male experience through personalised accounts derived from individual interviews. Using qualitative methodology and narrative inquiry, the findings provide a deeper understanding of the issues that males of different ages face when creating a new identity as a university student. This paper shares insights into what motivated the male students to enter university via an enabling pathway; the actual personal experiences both positive and negative during this time; and the effect that this commitment to study had on them personally and the people around them. The lens of transformative theory underpins this research through exploring frames of reference that align with the students’ experiences. Portraiture prose shares the individual stories which are analysed and the key findings extrapolated.

  12. Structuring the Environmental Experience Design Research Framework through Selected Aged Care Facility Data Analyses in Victoria

    Directory of Open Access Journals (Sweden)

    Nan Ma

    2017-11-01

    Full Text Available Humans relate to the living environment physically and psychologically. Environmental psychology has a rich developed history while experience design emerged recently in the industrial design domain. Nonetheless, these approaches have barely been merged, understood or implemented in architectural design practices. This study explored the correlation between experience design and environmental psychology. Moreover, it conducted literature reviews on theories about emotion, user experience design, experience design and environmental psychology, followed by the analyses of spatial settings and environmental quality data of a selected aged care facility in Victoria, Australia, as a case study. Accordingly, this study led to proposing a research framework on environmental experience design (EXD. It can be defined as a deliberate attempt that affiliates experience design and environmental psychology with creation of the built environment that should accommodate user needs and demands. The EXD research framework proposed in this study was tailored for transforming related design functions into the solutions that contribute to improving the built environment for user health and wellbeing.

  13. Collaborating and sharing data in epilepsy research.

    Science.gov (United States)

    Wagenaar, Joost B; Worrell, Gregory A; Ives, Zachary; Dümpelmann, Matthias; Matthias, Dümpelmann; Litt, Brian; Schulze-Bonhage, Andreas

    2015-06-01

    Technological advances are dramatically advancing translational research in Epilepsy. Neurophysiology, imaging, and metadata are now recorded digitally in most centers, enabling quantitative analysis. Basic and translational research opportunities to use these data are exploding, but academic and funding cultures prevent this potential from being realized. Research on epileptogenic networks, antiepileptic devices, and biomarkers could progress rapidly if collaborative efforts to digest this "big neuro data" could be organized. Higher temporal and spatial resolution data are driving the need for novel multidimensional visualization and analysis tools. Crowd-sourced science, the same that drives innovation in computer science, could easily be mobilized for these tasks, were it not for competition for funding, attribution, and lack of standard data formats and platforms. As these efforts mature, there is a great opportunity to advance Epilepsy research through data sharing and increase collaboration between the international research community.

  14. The influence of authentic scientific research experiences on teachers' conceptions of the nature of science (NOS) and their NOS teaching practices

    Science.gov (United States)

    Moriarty, Meghan A.

    This study explored the influence of teachers' authentic scientific research experiences (ASREs) on teachers' conceptions of the nature of science (NOS) and teachers' NOS instruction. Twelve high school biology teachers participated in this study. Six of the participants had authentic scientific research experience (ASRE) and six had not participated in authentic scientific research. Data included background surveys, modified Views of the Nature of Science (VNOS) questionnaires, interviews, and teaching observations. Data was coded based on the eight NOS understandings outlined in 2013 in the Next Generation Science Standards (NGSS). Evidence from this study indicates participating in authentic scientific research as a member of a scientific community has dual benefits of enabling high school science teachers with informed understandings of the NOS and positioning them to teach with the NOS. However, these benefits do not always result from an ASRE. If the nature of the ASRE is limited, then it may limit teachers' NOS understandings and their NOS teaching practices. The results of this study suggest that participation in ASREs may be one way to improve teachers' NOS understandings and teaching practices if the experiences themselves offer a comprehensive view of the NOS. Because ASREs and other science learning experiences do not always offer such experiences, pre-service teacher education and professional development opportunities may engage science teachers in two ways: (1) becoming part of a scientific community may enable them to teach with NOS and (2) being reflective about what being a scientist means may improve teachers' NOS understandings and better position them to teach about NOS.. Keywords: nature of science, authentic scientific research experiences, Next Generation Science Standards, teaching about NOS, teaching with NOS.

  15. Developing a national dental education research strategy: priorities, barriers and enablers.

    Science.gov (United States)

    Ajjawi, Rola; Barton, Karen L; Dennis, Ashley A; Rees, Charlotte E

    2017-03-29

    This study aimed to identify national dental education research (DER) priorities for the next 3-5 years and to identify barriers and enablers to DER. Scotland. In this two-stage online questionnaire study, we collected data with multiple dental professions (eg, dentistry, dental nursing and dental hygiene) and stakeholder groups (eg, learners, clinicians, educators, managers, researchers and academics). Eighty-five participants completed the Stage 1 qualitative questionnaire and 649 participants the Stage 2 quantitative questionnaire. Eight themes were identified at Stage 1. Of the 24 DER priorities identified, the top three were: role of assessments in identifying competence; undergraduate curriculum prepares for practice and promoting teamwork. Following exploratory factor analysis, the 24 items loaded onto four factors: teamwork and professionalism, measuring and enhancing performance, dental workforce issues and curriculum integration and innovation. Barriers and enablers existed at multiple levels: individual, interpersonal, institutional structures and cultures and technology. This priority setting exercise provides a necessary first step to developing a national DER strategy capturing multiple perspectives. Promoting DER requires improved resourcing alongside efforts to overcome peer stigma and lack of valuing and motivation. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  16. Seeking help for obsessive compulsive disorder (OCD): a qualitative study of the enablers and barriers conducted by a researcher with personal experience of OCD.

    Science.gov (United States)

    Robinson, Karen J; Rose, Diana; Salkovskis, Paul M

    2017-06-01

    Obsessive compulsive disorder (OCD) can be hugely disabling. Although very effective psychological treatments exist, many people delay years before seeking help or never seek treatment. There have been clinical observation and short questionnaire studies on why people delay, but little qualitative research exists on this complex subject. The present qualitative study aimed to identify the barriers to seeking treatment and the factors that encourage or push people to seek help for their OCD (positive and negative enablers). A qualitative, exploratory study using in-depth, individual, semi-structured interviews was conducted by a researcher with personal experience of OCD. Seventeen people with OCD, contacted through the charity OCD-UK, were interviewed about the factors that impacted on their decision to seek help or not. The interviews were analysed using thematic analysis. Barriers identified were stigma, 'internal / cognitive' factors, not knowing what their problem was, factors relating to their GP or treatment, and fear of criminalisation. Positive enablers identified were being supported to seek help, information and personal accounts of OCD in the media, and confidence in their GP. Negative enablers were reaching a crisis point and for some participants (whose intrusive thoughts were about harming children) feeling driven to seek treatment because of the nature of the thoughts, that is, seeking help to prevent the 'harm' they feared they were capable of doing. Participants identified a range of barriers and enablers that impacted on their decision to seek help or not. These give important indicators about the likely causes for delayed help seeking in OCD and ways in which people might be encouraged to seek help earlier. People with OCD may face a wide range of barriers to seeking help, including concern about the reaction of health professionals. The level of awareness, kindness, and understanding shown by first-line practitioners can be very important to

  17. Federated health information architecture: Enabling healthcare providers and policymakers to use data for decision-making.

    Science.gov (United States)

    Kumar, Manish; Mostafa, Javed; Ramaswamy, Rohit

    2018-05-01

    Health information systems (HIS) in India, as in most other developing countries, support public health management but fail to enable healthcare providers to use data for delivering quality services. Such a failure is surprising, given that the population healthcare data that the system collects are aggregated from patient records. An important reason for this failure is that the health information architecture (HIA) of the HIS is designed primarily to serve the information needs of policymakers and program managers. India has recognised the architectural gaps in its HIS and proposes to develop an integrated HIA. An enabling HIA that attempts to balance the autonomy of local systems with the requirements of a centralised monitoring agency could meet the diverse information needs of various stakeholders. Given the lack of in-country knowledge and experience in designing such an HIA, this case study was undertaken to analyse HIS in the Bihar state of India and to understand whether it would enable healthcare providers, program managers and policymakers to use data for decision-making. Based on a literature review and data collected from interviews with key informants, this article proposes a federated HIA, which has the potential to improve HIS efficiency; provide flexibility for local innovation; cater to the diverse information needs of healthcare providers, program managers and policymakers; and encourage data-based decision-making.

  18. A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience.

    Science.gov (United States)

    Corradi, Luca; Porro, Ivan; Schenone, Andrea; Momeni, Parastoo; Ferrari, Raffaele; Nobili, Flavio; Ferrara, Michela; Arnulfo, Gabriele; Fato, Marco M

    2012-10-08

    Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i) supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii) handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii) providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of "meta" data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach. Finally, data integration aspects have been

  19. A repository based on a dynamically extensible data model supporting multidisciplinary research in neuroscience

    Directory of Open Access Journals (Sweden)

    Corradi Luca

    2012-10-01

    Full Text Available Abstract Background Robust, extensible and distributed databases integrating clinical, imaging and molecular data represent a substantial challenge for modern neuroscience. It is even more difficult to provide extensible software environments able to effectively target the rapidly changing data requirements and structures of research experiments. There is an increasing request from the neuroscience community for software tools addressing technical challenges about: (i supporting researchers in the medical field to carry out data analysis using integrated bioinformatics services and tools; (ii handling multimodal/multiscale data and metadata, enabling the injection of several different data types according to structured schemas; (iii providing high extensibility, in order to address different requirements deriving from a large variety of applications simply through a user runtime configuration. Methods A dynamically extensible data structure supporting collaborative multidisciplinary research projects in neuroscience has been defined and implemented. We have considered extensibility issues from two different points of view. First, the improvement of data flexibility has been taken into account. This has been done through the development of a methodology for the dynamic creation and use of data types and related metadata, based on the definition of “meta” data model. This way, users are not constrainted to a set of predefined data and the model can be easily extensible and applicable to different contexts. Second, users have been enabled to easily customize and extend the experimental procedures in order to track each step of acquisition or analysis. This has been achieved through a process-event data structure, a multipurpose taxonomic schema composed by two generic main objects: events and processes. Then, a repository has been built based on such data model and structure, and deployed on distributed resources thanks to a Grid-based approach

  20. Researching experiences of cancer: the importance of methodology.

    Science.gov (United States)

    Entwistle, V; Tritter, J Q; Calnan, M

    2002-09-01

    This paper draws on contributions to and discussions at a recent MRC HSRC-sponsored workshop 'Researching users' experiences of health care: the case of cancer'. We focus on the methodological and ethical challenges that currently face researchers who use self-report methods to investigate experiences of cancer and cancer care. These challenges relate to: the theoretical and conceptual underpinnings of research; participation rates and participant profiles; data collection methods (the retrospective nature of accounts, description and measurement, and data collection as intervention); social desirability considerations; relationship considerations; the experiences of contributing to research; and the synthesis and presentation of findings. We suggest that methodological research to tackle these challenges should be integrated into substantive research projects to promote the development of a strong knowledge base about experiences of cancer and cancer care.

  1. CERN Analysis Preservation: A Novel Digital Library Service to Enable Reusable and Reproducible Research

    CERN Document Server

    AUTHOR|(CDS)2079501; Chen, Xiaoli; Dani, Anxhela; Dasler, Robin Lynnette; Delgado Fernandez, Javier; Fokianos, Pamfilos; Herterich, Patricia Sigrid; Simko, Tibor

    2016-01-01

    The latest policy developments require immediate action for data preservation, as well as reproducible and Open Science. To address this, an unprecedented digital library service is presented to enable the High-Energy Physics community to preserve and share their research objects (such as data, code, documentation, notes) throughout their research process. While facing the challenges of a “big data” community, the internal service builds on existing internal databases to make the process as easy and intrinsic as possible for researchers. Given the “work in progress” nature of the objects preserved, versioning is supported. It is expected that the service will not only facilitate better preservation techniques in the community, but will foremost make collaborative research easier as detailed metadata and novel retrieval functionality provide better access to ongoing works. This new type of e-infrastructure, fully integrated into the research workflow, could help in fostering Open Science practices acro...

  2. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows.

    Science.gov (United States)

    Sztromwasser, Pawel; Puntervoll, Pål; Petersen, Kjell

    2011-07-26

    Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  3. Data partitioning enables the use of standard SOAP Web Services in genome-scale workflows

    Directory of Open Access Journals (Sweden)

    Sztromwasser Paweł

    2011-06-01

    Full Text Available Biological databases and computational biology tools are provided by research groups around the world, and made accessible on the Web. Combining these resources is a common practice in bioinformatics, but integration of heterogeneous and often distributed tools and datasets can be challenging. To date, this challenge has been commonly addressed in a pragmatic way, by tedious and error-prone scripting. Recently however a more reliable technique has been identified and proposed as the platform that would tie together bioinformatics resources, namely Web Services. In the last decade the Web Services have spread wide in bioinformatics, and earned the title of recommended technology. However, in the era of high-throughput experimentation, a major concern regarding Web Services is their ability to handle large-scale data traffic. We propose a stream-like communication pattern for standard SOAP Web Services, that enables efficient flow of large data traffic between a workflow orchestrator and Web Services. We evaluated the data-partitioning strategy by comparing it with typical communication patterns on an example pipeline for genomic sequence annotation. The results show that data-partitioning lowers resource demands of services and increases their throughput, which in consequence allows to execute in-silico experiments on genome-scale, using standard SOAP Web Services and workflows. As a proof-of-principle we annotated an RNA-seq dataset using a plain BPEL workflow engine.

  4. MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science through Cloud-Enabled Climate Analytics-as-a-Service

    Science.gov (United States)

    Schnase, J. L.; Duffy, D.; Tamkin, G. S.; Nadeau, D.; Thompson, J. H.; Grieg, C. M.; McInerney, M.; Webster, W. P.

    2013-12-01

    Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRA/AS) is an example of cloud-enabled CAaaS built on this principle. MERRA/AS enables MapReduce analytics over NASA's Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRA/AS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRA/AS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to

  5. MERRA Analytic Services: Meeting the Big Data Challenges of Climate Science Through Cloud-enabled Climate Analytics-as-a-service

    Science.gov (United States)

    Schnase, John L.; Duffy, Daniel Quinn; Tamkin, Glenn S.; Nadeau, Denis; Thompson, John H.; Grieg, Christina M.; McInerney, Mark A.; Webster, William P.

    2014-01-01

    Climate science is a Big Data domain that is experiencing unprecedented growth. In our efforts to address the Big Data challenges of climate science, we are moving toward a notion of Climate Analytics-as-a-Service (CAaaS). We focus on analytics, because it is the knowledge gained from our interactions with Big Data that ultimately produce societal benefits. We focus on CAaaS because we believe it provides a useful way of thinking about the problem: a specialization of the concept of business process-as-a-service, which is an evolving extension of IaaS, PaaS, and SaaS enabled by Cloud Computing. Within this framework, Cloud Computing plays an important role; however, we it see it as only one element in a constellation of capabilities that are essential to delivering climate analytics as a service. These elements are essential because in the aggregate they lead to generativity, a capacity for self-assembly that we feel is the key to solving many of the Big Data challenges in this domain. MERRA Analytic Services (MERRAAS) is an example of cloud-enabled CAaaS built on this principle. MERRAAS enables MapReduce analytics over NASAs Modern-Era Retrospective Analysis for Research and Applications (MERRA) data collection. The MERRA reanalysis integrates observational data with numerical models to produce a global temporally and spatially consistent synthesis of 26 key climate variables. It represents a type of data product that is of growing importance to scientists doing climate change research and a wide range of decision support applications. MERRAAS brings together the following generative elements in a full, end-to-end demonstration of CAaaS capabilities: (1) high-performance, data proximal analytics, (2) scalable data management, (3) software appliance virtualization, (4) adaptive analytics, and (5) a domain-harmonized API. The effectiveness of MERRAAS has been demonstrated in several applications. In our experience, Cloud Computing lowers the barriers and risk to

  6. Enabling spaces in education research: an agenda for impactful ...

    African Journals Online (AJOL)

    An enabling schools research agenda could intentionally guide inquiry into that which supports education, where chronic poverty renders society as characteristically less equal. Keywords: barriers to education; buffers in education; egalitarian political philosophy; equality of opportunity; global South education; high risk ...

  7. Opening Up Climate Research: A Linked Data Approach to Publishing Data Provenance

    Directory of Open Access Journals (Sweden)

    Arif Shaon

    2012-03-01

    Full Text Available Traditionally, the formal scientific output in most fields of natural science has been limited to peer-reviewed academic journal publications, with less attention paid to the chain of intermediate data results and their associated metadata, including provenance. In effect, this has constrained the representation and verification of the data provenance to the confines of the related publications. Detailed knowledge of a dataset’s provenance is essential to establish the pedigree of the data for its effective re-use, and to avoid redundant re-enactment of the experiment or computation involved. It is increasingly important for open-access data to determine their authenticity and quality, especially considering the growing volumes of datasets appearing in the public domain. To address these issues, we present an approach that combines the Digital Object Identifier (DOI – a widely adopted citation technique – with existing, widely adopted climate science data standards to formally publish detailed provenance of a climate research dataset as an associated scientific workflow. This is integrated with linked-data compliant data re-use standards (e.g. OAI-ORE to enable a seamless link between a publication and the complete trail of lineage of the corresponding dataset, including the dataset itself.

  8. Exploring perceptions and experiences of Bolivian health researchers with research ethics.

    Science.gov (United States)

    Sullivan, Sarah; Aalborg, Annette; Basagoitia, Armando; Cortes, Jacqueline; Lanza, Oscar; Schwind, Jessica S

    2015-04-01

    In Bolivia, there is increasing interest in incorporating research ethics into study procedures, but there have been inconsistent application of research ethics practices. Minimal data exist regarding the experiences of researchers concerning the ethical conduct of research. A cross-sectional study was administered to Bolivian health leaders with research experience (n = 82) to document their knowledge, perceptions, and experiences of research ethics committees and infrastructure support for research ethics. Results showed that 16% of respondents reported not using ethical guidelines to conduct their research and 66% indicated their institutions did not consistently require ethics approval for research. Barriers and facilitators to incorporate research ethics into practice were outlined. These findings will help inform a comprehensive rights-based research ethics education program in Bolivia. © The Author(s) 2015.

  9. Multi-omic data integration enables discovery of hidden biological regularities

    DEFF Research Database (Denmark)

    Ebrahim, Ali; Brunk, Elizabeth; Tan, Justin

    2016-01-01

    Rapid growth in size and complexity of biological data sets has led to the 'Big Data to Knowledge' challenge. We develop advanced data integration methods for multi- level analysis of genomic, transcriptomic, ribosomal profiling, proteomic and fluxomic data. First, we show that pairwise integration...... of primary omics data reveals regularities that tie cellular processes together in Escherichia coli: the number of protein molecules made per mRNA transcript and the number of ribosomes required per translated protein molecule. Second, we show that genome- scale models, based on genomic and bibliomic data......, enable quantitative synchronization of disparate data types. Integrating omics data with models enabled the discovery of two novel regularities: condition invariant in vivo turnover rates of enzymes and the correlation of protein structural motifs and translational pausing. These regularities can...

  10. Quality of research results in agro-economy by data mining

    Directory of Open Access Journals (Sweden)

    Vukelić Gordana

    2015-01-01

    Full Text Available Data Mining (DM through data in agroeconomy is a scientific method that enables researchers not to go through set research scenarioes that are predetermined assumptions and hypotheses on the basis of insignificant atributes. On the contrary, by data mining detection of these atributes is made possible, in general, those hiden facts that enable setting a hypothesis. The DM method does this by an iterative way, including key atributes and factors and their influence on the quality of agro-resources. The research was conducted on a random sample, by analyzing the quality of eggs. The research subject is the posibility of classifying and predicting significant variablesatributes that determine the level of egg quality. The research starts from the use of Data Mining, as an area of machine studies, which significantly helps researchers in optimizing research. The applied methodology during research includes analyticalsintetic procedures and methods of Data Mining, with a special focus on using Supervised linear discrimination analysis and the Decision Tree. The results indicate significant posibilities of using DM as an additional analytical procedure in performing agroresearch and it can be concluded that it contributes to an improvement in effectiveness and validity of process in performing these researches.

  11. Data management in a fusion energy research experiment

    International Nuclear Information System (INIS)

    Glad, A.; Drobnis, D.; McHarg, B.

    1981-07-01

    Present-day fusion research requires extensive support for the large amount of scientific data generated, bringing about three distinct problems computer systems must solve: (1) the processing of large amounts of data in very small time frames; (2) the archiving, analyzing and managing of the entire data output for the project's lifetime; (3) the standardization of data for the exchange of information between laboratories. The computer system supporting General Atomic's Doublet III tokamak, a project funded by the United States Department of Energy, is the first to encounter and address these problems through a system-wide data base structure

  12. Leveling up: enabling diverse users to locate and effectively use unfamiliar data sets through NCAR's Research Data Archive

    Science.gov (United States)

    Peng, G. S.

    2016-12-01

    Research necessarily expands upon the volume and variety of data used in prior work. Increasingly, investigators look outside their primary areas of expertise for data to incorporate into their research. Locating and using the data that they need, which may be described in terminology from other fields of science or be encoded in unfamiliar data formats, present often insurmountable barriers for potential users. As a data provider of a diverse collection of over 600 atmospheric and oceanic data sets (DS) (http://rda.ucar.edu), we seek to reduce or remove those barriers. Serving a broadening and increasing user base with fixed and finite resources requires automation. Our software harvests metadata descriptors about the data from the data files themselves. Data curators/subject matter experts augment the machine-generated metadata as needed. Metadata powers our data search tools. Users may search for data in a myriad of ways ranging from free text queries to GCMD keywords to faceted searches capable of narrowing down selections by specific criteria. Users are offered customized lists of DSs fitting their criteria with links to DS main information pages that provide detailed information about each DS. Where appropriate, they link to the NCAR Climate Data Guide for expert guidance about strengths and weaknesses of that particular DS. Once users find the data sets they need, we provide modular lessons for common data tasks. The lessons may be data tool install guides, data recipes, blog posts, or short YouTube videos. Rather than overloading users with reams of information, we provide targeted lessons when the user is most receptive, e.g. when they want to use data in an unfamiliar format. We add new material when we discover common points of confusion. Each educational resource is tagged with DS ID numbers so that they are automatically linked with the relevant DSs. How can data providers leverage the work of other data providers? Can a common tagging scheme for data

  13. Cyber-Enabled Scientific Discovery

    International Nuclear Information System (INIS)

    Chan, Tony; Jameson, Leland

    2007-01-01

    It is often said that numerical simulation is third in the group of three ways to explore modern science: theory, experiment and simulation. Carefully executed modern numerical simulations can, however, be considered at least as relevant as experiment and theory. In comparison to physical experimentation, with numerical simulation one has the numerically simulated values of every field variable at every grid point in space and time. In comparison to theory, with numerical simulation one can explore sets of very complex non-linear equations such as the Einstein equations that are very difficult to investigate theoretically. Cyber-enabled scientific discovery is not just about numerical simulation but about every possible issue related to scientific discovery by utilizing cyberinfrastructure such as the analysis and storage of large data sets, the creation of tools that can be used by broad classes of researchers and, above all, the education and training of a cyber-literate workforce

  14. Enabling Higher Data Rates for Planetary Science Missions

    Science.gov (United States)

    Deutsch, L. J.; Townes, S. A.; Lazio, J.; Bell, D. J.; Chahat, N. E.; Kovalik, J. M.; Kuperman, I.; Sauder, J.; Liebrecht, P. E.

    2017-12-01

    The data rate from deep space spacecraft has increased by more than 10 orders of magnitude since the first lunar missions in the 1960s. The demand for increased data rates has stemmed from the increasing sophistication of the science questions being addressed and the concomitant increase in the complexity of the missions themselves (from fly-by to orbit to land and rove). Projections for the next few decades suggest the demand for data rates for deep space missions will continue to increase by approximately one order of magnitude every decade, driven by these same factors. Achieving higher data rates requires a partnership between the spacecraft and the ground system. We describe a series of technology developments for flight telecommunications systems, both at radio frequency (RF) and optical, to enable spacecraft to transmit and receive larger data volumes. These technology developments include deployable high gain antennas for small spacecraft, re-programmable software-defined radios, and optical communication packages designed for CubeSat form factors. The intent is that these developments would provide enhancements in capability for both spacecraft-Earth and spacecraft-spacecraft telecommunications. We also describe the future planning for NASA's Deep Space Network (DSN), which remains the prime conduit for data from all planetary science missions. Through a combination of new antennas and backends being installed over the next five years and incorporation of optical communications, the DSN aims to ensure that the historical improvements in data rates and volumes will continue for many decades. Part of this research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration.

  15. Providing Data Access for Interdisciplinary Research

    Science.gov (United States)

    Hooper, R. P.; Couch, A.

    2012-12-01

    Developing an interdisciplinary understanding of human and environmental interactions with water requires access to a variety of data kinds collected by various organizations. The CUAHSI Hydrologic Information System (HIS) is a standards-based, services-oriented architecture designed for time-series data. Such data represents an important type of data in water studies. Through the efforts of HIS, a standard transmission language, WaterML2, has been adopted by the Open Geospatial Consortium and is under consideration by the World Meteorologic Organization as an international standards. Web services have also been developed to retrieve data and metadata. HIS is completed with a metadata catalog, hosted by San Diego Supercomputing Center, which indexes more than 20 million time series provided from over 90 different services. This catalog is supported through a hierarchically organized controlled vocabulary that is open for community input and mediation. Data publishers include federal agencies, universities, state agencies, and non-profit organizations such as watershed associations. Accessing data from such a broad spectrum of sources through a uniform service standard promises to truly transform the way in which hydrologic research is done. CUAHSI HIS is a large-scale prototype at this time, but a proposal is under consideration by the National Science Foundation to operationalize HIS through a data facility, tentatively called the CUAHSI Water Data Center. Establishing HIS is an important step to enable research into human-environment interactions with water, but it is only one step. Other data structures will need to be made accessible and interoperable to support this research. Some data—such as two-dimensional GIS coverages—already have widely used standards for transmission and sharing. The US Federal government has long operated a clearinghouse for federal geographic data that is now being augmented with other services such as ArcGIS OnLine. Other data

  16. Access and preservation of digital research content: Linked open data services - A research library perspective

    Science.gov (United States)

    Kraft, Angelina; Sens, Irina; Löwe, Peter; Dreyer, Britta

    2016-04-01

    Globally resolvable, persistent digital identifiers have become an essential tool to enable unambiguous links between published research results and their underlying digital resources. In addition, this unambiguous identification allows citation. In an ideal research world, any scientific content should be citable and the coherent content, as well as the citation itself, should be persistent. However, today's scientists do not just produce traditional research papers - they produce comprehensive digital collections of objects which, alongside digital texts, include digital resources such as research data, audiovisual media, digital lab journals, images, statistics and software code. Researchers start to look for services which allow management of these digital resources with minimum time investment. In light of this, we show how the German National Library of Science and Technology (TIB) develops supportive frameworks to accompany the life cycle of scientific knowledge generation and transfer. This includes technical infrastructures for • indexing, cataloguing, digital preservation, DOI names and licencing for text and digital objects (the TIB DOI registration, active since 2004) and • a digital repository for the deposition and provision of accessible, traceable and citeable research data (RADAR). One particular problem for the management of data originating from (collaborating) research infrastructures is their dynamic nature in terms of growth, access rights and quality. On a global scale, systems for access and preservation are in place for the big data domains (e.g. environmental sciences, space, climate). However, the stewardship for disciplines without a tradition of data sharing, including the fields of the so-called long tail, remains uncertain. The RADAR - Research Data Repository - project establishes a generic end-point data repository, which can be used in a collaborative way. RADAR enables clients to upload, edit, structure and describe their

  17. KNMI DataLab experiences in serving data-driven innovations

    Science.gov (United States)

    Noteboom, Jan Willem; Sluiter, Raymond

    2016-04-01

    Climate change research and innovations in weather forecasting rely more and more on (Big) data. Besides increasing data from traditional sources (such as observation networks, radars and satellites), the use of open data, crowd sourced data and the Internet of Things (IoT) is emerging. To deploy these sources of data optimally in our services and products, KNMI has established a DataLab to serve data-driven innovations in collaboration with public and private sector partners. Big data management, data integration, data analytics including machine learning and data visualization techniques are playing an important role in the DataLab. Cross-domain data-driven innovations that arise from public-private collaborative projects and research programmes can be explored, experimented and/or piloted by the KNMI DataLab. Furthermore, advice can be requested on (Big) data techniques and data sources. In support of collaborative (Big) data science activities, scalable environments are offered with facilities for data integration, data analysis and visualization. In addition, Data Science expertise is provided directly or from a pool of internal and external experts. At the EGU conference, gained experiences and best practices are presented in operating the KNMI DataLab to serve data-driven innovations for weather and climate applications optimally.

  18. Stranger to friend enabler: creating a community of caring in African American research using ethnonursing methods.

    Science.gov (United States)

    Plowden, K O; Wenger, A F

    2001-01-01

    African Americans are facing a serious health crisis. They are disproportionately affected by most chronic illnesses. The disparity among ethic groups as it relates to health and illness is related to psychosocial and biological factors within the African American culture. Many African Americans are sometimes reluctant to participate in studies. This article discusses the process of creating a caring community when conducting research within an African American community based on the experience of the authors with two faith communities in a southern metropolitan area in the United States. The process is identified as unknowing, reflection, presence, and knowing. The process is based on Leininger's theory of culture care diversity and universality and her stranger to friend enabler. When the theory and method are used, the investigator moves from a stranger within the community to a trusted friend and begins to collect rich and valuable data for analysis from the informants' point of view.

  19. Peer-To-Peer Architectures in Distributed Data Management Systems for Large Hadron Collider Experiments

    CERN Document Server

    Lo Presti, Giuseppe; Lo Re, G; Orsini, L

    2005-01-01

    The main goal of the presented research is to investigate Peer-to-Peer architectures and to leverage distributed services to support networked autonomous systems. The research work focuses on development and demonstration of technologies suitable for providing autonomy and flexibility in the context of distributed network management and distributed data acquisition. A network management system enables the network administrator to monitor a computer network and properly handle any failure that can arise within the network. An online data acquisition (DAQ) system for high-energy physics experiments has to collect, combine, filter, and store for later analysis a huge amount of data, describing subatomic particles collision events. Both domains have tight constraints which are discussed and tackled in this work. New emerging paradigms have been investigated to design novel middleware architectures for such distributed systems, particularly the Active Networks paradigm and the Peer-to-Peer paradigm. A network man...

  20. Bringing Health and Fitness Data Together for Connected Health Care: Mobile Apps as Enablers of Interoperability.

    Science.gov (United States)

    Gay, Valerie; Leijdekkers, Peter

    2015-11-18

    A transformation is underway regarding how we deal with our health. Mobile devices make it possible to have continuous access to personal health information. Wearable devices, such as Fitbit and Apple's smartwatch, can collect data continuously and provide insights into our health and fitness. However, lack of interoperability and the presence of data silos prevent users and health professionals from getting an integrated view of health and fitness data. To provide better health outcomes, a complete picture is needed which combines informal health and fitness data collected by the user together with official health records collected by health professionals. Mobile apps are well positioned to play an important role in the aggregation since they can tap into these official and informal health and data silos. The objective of this paper is to demonstrate that a mobile app can be used to aggregate health and fitness data and can enable interoperability. It discusses various technical interoperability challenges encountered while integrating data into one place. For 8 years, we have worked with third-party partners, including wearable device manufacturers, electronic health record providers, and app developers, to connect an Android app to their (wearable) devices, back-end servers, and systems. The result of this research is a health and fitness app called myFitnessCompanion, which enables users to aggregate their data in one place. Over 6000 users use the app worldwide to aggregate their health and fitness data. It demonstrates that mobile apps can be used to enable interoperability. Challenges encountered in the research process included the different wireless protocols and standards used to communicate with wireless devices, the diversity of security and authorization protocols used to be able to exchange data with servers, and lack of standards usage, such as Health Level Seven, for medical information exchange. By limiting the negative effects of health data silos

  1. The Mason Water Data Information System (MWDIS): Enabling data sharing and discovery at George Mason University

    Science.gov (United States)

    Ferreira, C.; Da Silva, A. L.; Nunes, A.; Haddad, J.; Lawler, S.

    2014-12-01

    Enabling effective data use and re-use in scientific investigations relies heavily not only on data availability but also on efficient data sharing discovery. The CUAHSI led Hydrological Information Systems (HIS) and supporting products have paved the way to efficient data sharing and discovery in the hydrological sciences. Based on the CUAHSI-HIS framework concepts for hydrologic data sharing we developed a unique system devoted to the George Mason University scientific community to support university wide data sharing and discovery as well as real time data access for extreme events situational awareness. The internet-based system will provide an interface where the researchers will input data collected from the measurement stations and present them to the public in form of charts, tables, maps, and documents. Moreover, the system is developed in ASP.NET MVC 4 using as Database Management System, Microsoft SQL Server 2008 R2, and hosted by Amazon Web Services. Currently the system is supporting the Mason Watershed Project providing historical hydrological, atmospheric and water quality data for the campus watershed and real time flood conditions in the campus. The system is also a gateway for unprecedented data collection of hurricane storm surge hydrodynamics in coastal wetlands in the Chesapeake Bay providing not only access to historical data but recent storms such as Hurricane Arthur. Future research includes coupling the system to a real-time flood alert system on campus, and besides providing data on the World Wide Web, to foment and provide a venue for interdisciplinary collaboration within the water scientists in the region.

  2. Introduction to stream: An Extensible Framework for Data Stream Clustering Research with R

    Directory of Open Access Journals (Sweden)

    Michael Hahsler

    2017-02-01

    Full Text Available In recent years, data streams have become an increasingly important area of research for the computer science, database and statistics communities. Data streams are ordered and potentially unbounded sequences of data points created by a typically non-stationary data generating process. Common data mining tasks associated with data streams include clustering, classification and frequent pattern mining. New algorithms for these types of data are proposed regularly and it is important to evaluate them thoroughly under standardized conditions. In this paper we introduce stream, a research tool that includes modeling and simulating data streams as well as an extensible framework for implementing, interfacing and experimenting with algorithms for various data stream mining tasks. The main advantage of stream is that it seamlessly integrates with the large existing infrastructure provided by R. In addition to data handling, plotting and easy scripting capabilities, R also provides many existing algorithms and enables users to interface code written in many programming languages popular among data mining researchers (e.g., C/C++, Java and Python. In this paper we describe the architecture of stream and focus on its use for data stream clustering research. stream was implemented with extensibility in mind and will be extended in the future to cover additional data stream mining tasks like classification and frequent pattern mining.

  3. The Research Portfolio: Educating Teacher Researchers in Data Analysis

    Science.gov (United States)

    Bates, Alisa J.; Bryant, Jill D.

    2013-01-01

    This paper describes research on a course assignment, the research portfolio, designed for a two-course teacher research experience in a Masters of Arts in Teaching program. The focus of the assignment is the process of data collection and analysis that is critical to the success of teacher research. We sought a way to help our teacher candidates…

  4. An XML-Enabled Data Mining Query Language XML-DMQL

    NARCIS (Netherlands)

    Feng, L.; Dillon, T.

    2005-01-01

    Inspired by the good work of Han et al. (1996) and Elfeky et al. (2001) on the design of data mining query languages for relational and object-oriented databases, in this paper, we develop an expressive XML-enabled data mining query language by extension of XQuery. We first describe some

  5. Digital curation of research data experiences of a baseline study in Germany

    CERN Document Server

    Strathmann, Stefan; Oßwald, Achim; Ludwig, Jens

    2013-01-01

    The relevance of research data today and for the future is well documented and discussed, in Germany as well as internationally. Ensuring that research data are accessible, sharable, and re-usable over time is increasingly becoming an essential task for researchers and research infrastructure institutions. Some reasons for this development include the following: - research data are documented and could therefore be validated - research data could be the basis for new research questions - research data could be re-analyzed by using innovative digital methods - research data could be used by other disciplines Therefore, it is essential that research data are curated, which means they are kept accessible and interpretable over time. In Germany, a baseline study was undertaken analyzing the situation in eleven research disciplines in 2012. The results were then published in a German-language edition. To address an international audience, the German-language edition of the study has been translated and abridged. T...

  6. Enabling sustainable uranium production: The Inter-regional Technical Cooperation experience

    International Nuclear Information System (INIS)

    Tulsidas, H.; Zhang, J.

    2014-01-01

    Uranium production cycle activities are increasing worldwide, often in countries with little or no previous experience in such activities. Initial efforts in uranium exploration and mining were limited to a few countries, which progressed through a painful learning curve often associated with high socioeconomic costs. With time, good practices for the sustainable conduct of operations became well established, but new projects in different regional contexts continue to face challenges. Moreover, there have been highs and lows in the levels of activities and operations in the uranium industry, which has disrupted the stabilizing of the experiences and lessons learned, into a coherent body of knowledge. This collective experience, assimilated over time, has to be transferred to a new generation of experts, who have to be enabled to use this knowledge effectively in their local contexts in order to increase efficiency and reduce the footprint of the operations. This makes it sustainable and socially acceptable to local communities, as well as in the global context. IAEA has implemented several projects in the last five years to address gaps in transferring a coherent body of knowledge on sustainable uranium production from a well experienced generation of experts to a new generation facing similar challenges in different geographical, technological, economic and social contexts. These projects focused on enabling the new practitioners in the uranium production industry to avoid the mistakes of the past and to apply good practices established elsewhere, adapted to local needs. The approach was intended to bring considerable cost savings while attracting elevated levels of social acceptance. These projects were effective in introducing experts from different areas of the uranium production cycle and with different levels of experience to the availability of advanced tools that can make operations more efficient and productive, reduce footprint, increase competencies in

  7. Collection of measurement data from in-situ experiment for performance confirmation of engineered barrier system at Horonobe Underground Research Laboratory. FY2015

    International Nuclear Information System (INIS)

    Nakayama, Masashi; Ohno, Hirokazu; Nakayama, Mariko; Kobayashi, Masato

    2016-07-01

    The Horonobe Underground Research Laboratory (URL) Project has being pursued by Japan Atomic Energy Agency to enhance the reliability of relevant disposal technologies through investigations of the deep geological environment within the host sedimentary formation at Horonobe, northern Hokkaido. The URL Project consists of two major research areas, 'Geoscientific Research' and 'Research and Development on Geological Disposal Technologies', and proceeds in three overlapping phases, 'Phase I: Surface-based investigations', 'Phase II: Investigations during tunnel excavation' and 'Phase III: Investigations in the underground facilities', over a period of around 20 years. Phase III investigation was started in 2010 fiscal year. The in-situ experiment for performance confirmation of engineered barrier system (EBS experiment) had been prepared from 2013 to 2014 fiscal year at G.L.-350m gallery, and heating by electric heater in simulated overpack had started in January, 2015. One of objectives of the experiment is acquiring data concerned with Thermal - Hydrological - Mechanical - Chemical (THMC) coupled behavior. These data will be used in order to confirm the performance of engineered barrier system. This report summarizes the measurement data acquired from the EBS experiment from December, 2014 to March, 2016. The summarized data of the EBS experiment will be published periodically. A CD-ROM is attached as an appendix. (J.P.N)

  8. Strategic research roadmap on ICT-enabled energy efficiency in buildings

    Energy Technology Data Exchange (ETDEWEB)

    Kazi, A.S., Email: sami.kazi@vtt.fi

    2012-06-15

    The REEB Project (The European strategic research Roadmap to ICT-enabled Energy- Efficiency in Buildings and construction projects) was a Coordination Action project funded under the European Commission's Seventh Framework Programme. Its main purpose was to provide a strategic research roadmap on information and communications technology (ICT) support for energy efficiency in the built environment and a collection of implementation actions supporting the realisation of the roadmap. (orig.)

  9. Data integration in biological research: an overview.

    Science.gov (United States)

    Lapatas, Vasileios; Stefanidakis, Michalis; Jimenez, Rafael C; Via, Allegra; Schneider, Maria Victoria

    2015-12-01

    Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.

  10. Data exploration, quality control and statistical analysis of ChIP-exo/nexus experiments.

    Science.gov (United States)

    Welch, Rene; Chung, Dongjun; Grass, Jeffrey; Landick, Robert; Keles, Sündüz

    2017-09-06

    ChIP-exo/nexus experiments rely on innovative modifications of the commonly used ChIP-seq protocol for high resolution mapping of transcription factor binding sites. Although many aspects of the ChIP-exo data analysis are similar to those of ChIP-seq, these high throughput experiments pose a number of unique quality control and analysis challenges. We develop a novel statistical quality control pipeline and accompanying R/Bioconductor package, ChIPexoQual, to enable exploration and analysis of ChIP-exo and related experiments. ChIPexoQual evaluates a number of key issues including strand imbalance, library complexity, and signal enrichment of data. Assessment of these features are facilitated through diagnostic plots and summary statistics computed over regions of the genome with varying levels of coverage. We evaluated our QC pipeline with both large collections of public ChIP-exo/nexus data and multiple, new ChIP-exo datasets from Escherichia coli. ChIPexoQual analysis of these datasets resulted in guidelines for using these QC metrics across a wide range of sequencing depths and provided further insights for modelling ChIP-exo data. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  11. Unifying Water Data Sources: How the CUAHSI Water Data Center is Enabling and Improving Access to a Growing Catalog of over 100 Data Providers

    Science.gov (United States)

    Pollak, J.; Berry, K.; Couch, A.; Arrigo, J.; Hooper, R. P.

    2013-12-01

    Scientific data about water are collected and distributed by numerous sources which can differ tremendously in scale. As competition for water resources increases, increasing access to and understanding of information about water will be critical. The mission of the new CUAHSI Water Data Center (WDC) is to provide those researchers who collect data a medium to publish their datasets and give those wanting to discover data the proper tools to efficiently find the data that they seek. These tools include standards-based data publication, data discovery tools based upon faceted and telescoping search, and a data analysis tool HydroDesktop that downloads and unifies data in standardized formats. The CUAHSI Hydrologic Information System (HIS) is a community developed and open source system for sharing water data. As a federated, web service oriented system it enables data publication for a diverse user population including scientific investigators (Research Coordination Networks, Critical Zone Observatories), government agencies (USGS, NASA, EPA), and citizen scientists (watershed associations). HydroDesktop is an end user application for data consumption in this system that the WDC supports. This application can be used for finding, downloading, and analyzing data from the HIS. It provides a GIS interface that allows users to incorporate spatial data that are not accessible via HIS, simple analysis tools to facilitate graphing and visualization, tools to export data to common file types, and provides an extensible architecture that developers can build upon. HydroDesktop, however, is just one example of a data access client for HIS. The web service oriented architecture enables data access by an unlimited number of clients provided they can consume the web services used in HIS. One such example developed at the WDC is the 'Faceted Search Client', which capitalizes upon exploratory search concepts to improve accuracy and precision during search. We highlight such

  12. Automating data citation: the eagle-i experience.

    Science.gov (United States)

    Alawini, Abdussalam; Chen, Leshang; Davidson, Susan B; Da Silva, Natan Portilho; Silvello, Gianmaria

    2017-06-01

    Data citation is of growing concern for owners of curated databases, who wish to give credit to the contributors and curators responsible for portions of the dataset and enable the data retrieved by a query to be later examined. While several databases specify how data should be cited, they leave it to users to manually construct the citations and do not generate them automatically. We report our experiences in automating data citation for an RDF dataset called eagle-i, and discuss how to generalize this to a citation framework that can work across a variety of different types of databases (e.g. relational, XML, and RDF). We also describe how a database administrator would use this framework to automate citation for a particular dataset.

  13. Encouraging engagement in enabling programs: The students’ perspective

    Directory of Open Access Journals (Sweden)

    Suzi Hellmundt

    2017-03-01

    Full Text Available Student retention is a key concern in tertiary education enabling programs with research showing that early engagement leads to higher completion rates (Hodges et al., 2013. But how do students new to university education learn how to engage effectively? This article outlines an engagement framework that foregrounds Guidance, Encouragement, Modelling and Structure (GEMS as a holistic approach to facilitating effective student engagement. This framework was developed from qualitative data gleaned from students enrolled in the Preparing for Success Program at Southern Cross University, New South Wales, Australia. The findings from the students indicate that the GEMS framework activates student potential and enables them to use existing knowledge and experience to not only deepen and broaden their learning but also successfully prepare for further study.

  14. Standardized acquisition, storing and provision of 3D enabled spatial data

    Science.gov (United States)

    Wagner, B.; Maier, S.; Peinsipp-Byma, E.

    2017-05-01

    In the area of working with spatial data, in addition to the classic, two-dimensional geometrical data (maps, aerial images, etc.), the needs for three-dimensional spatial data (city models, digital elevation models, etc.) is increasing. Due to this increased demand the acquiring, storing and provision of 3D enabled spatial data in Geographic Information Systems (GIS) is more and more important. Existing proprietary solutions quickly reaches their limits during data exchange and data delivery to other systems. They generate a large workload, which will be very costly. However, it is noticeable that these expenses and costs can generally be significantly reduced using standards. The aim of this research is therefore to develop a concept in the field of three-dimensional spatial data that runs on existing standards whenever possible. In this research, the military image analysts are the preferred user group of the system. To achieve the objective of the widest possible use of standards in spatial 3D data, existing standards, proprietary interfaces and standards under discussion have been analyzed. Since the here used GIS of the Fraunhofer IOSB is already using and supporting OGC (Open Geospatial Consortium) and NATO-STANAG (NATO-Standardization Agreement) standards for the most part of it, a special attention for possible use was laid on their standards. The most promising standard is the OGC standard 3DPS (3D Portrayal Service) with its occurrences W3DS (Web 3D Service) and WVS (Web View Service). A demo system was created, using a standardized workflow from the data acquiring, storing and provision and showing the benefit of our approach.

  15. The Dutch Techcentre for Life Sciences: Enabling data-intensive life science research in the Netherlands [version 2; referees: 1 approved, 2 approved with reservations

    Directory of Open Access Journals (Sweden)

    Lars Eijssen

    2016-01-01

    Full Text Available We describe the Data programme of the Dutch Techcentre for Life Sciences (DTL, www.dtls.nl. DTL is a new national organisation in scientific research that facilitates life scientists with technologies and technological expertise in an era where new projects often are data-intensive, multi-disciplinary, and multi-site. It is run as a lean not-for-profit organisation with research organisations (both academic and industrial as paying members. The small staff of the organisation undertakes a variety of tasks that are necessary to perform or support modern academic research, but that are not easily undertaken in a purely academic setting. DTL Data takes care of such tasks related to data stewardship, facilitating exchange of knowledge and expertise, and brokering access to e-infrastructure. DTL also represents the Netherlands in ELIXIR, the European infrastructure for life science data. The organisation is still being fine-tuned and this will continue over time, as it is crucial for this kind of organisation to adapt to a constantly changing environment. However, already being underway for several years, our experiences can benefit researchers in other fields or other countries setting up similar initiatives.

  16. Sharing Privacy Protected and Statistically Sound Clinical Research Data Using Outsourced Data Storage

    Directory of Open Access Journals (Sweden)

    Geontae Noh

    2014-01-01

    Full Text Available It is critical to scientific progress to share clinical research data stored in outsourced generally available cloud computing services. Researchers are able to obtain valuable information that they would not otherwise be able to access; however, privacy concerns arise when sharing clinical data in these outsourced publicly available data storage services. HIPAA requires researchers to deidentify private information when disclosing clinical data for research purposes and describes two available methods for doing so. Unfortunately, both techniques degrade statistical accuracy. Therefore, the need to protect privacy presents a significant problem for data sharing between hospitals and researchers. In this paper, we propose a controlled secure aggregation protocol to secure both privacy and accuracy when researchers outsource their clinical research data for sharing. Since clinical data must remain private beyond a patient’s lifetime, we take advantage of lattice-based homomorphic encryption to guarantee long-term security against quantum computing attacks. Using lattice-based homomorphic encryption, we design an aggregation protocol that aggregates outsourced ciphertexts under distinct public keys. It enables researchers to get aggregated results from outsourced ciphertexts of distinct researchers. To the best of our knowledge, our protocol is the first aggregation protocol which can aggregate ciphertexts which are encrypted with distinct public keys.

  17. Experience-Sampling Research Methods and Their Potential for Education Research

    Science.gov (United States)

    Zirkel, Sabrina; Garcia, Julie A.; Murphy, Mary C.

    2015-01-01

    Experience-sampling methods (ESM) enable us to learn about individuals' lives in context by measuring participants' feelings, thoughts, actions, context, and/or activities as they go about their daily lives. By capturing experience, affect, and action "in the moment" and with repeated measures, ESM approaches allow researchers…

  18. Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.

    Science.gov (United States)

    Jacquez, Geoffrey M; Essex, Aleksander; Curtis, Andrew; Kohler, Betsy; Sherman, Recinda; Emam, Khaled El; Shi, Chen; Kaufmann, Andy; Beale, Linda; Cusick, Thomas; Goldberg, Daniel; Goovaerts, Pierre

    2017-07-01

    As the volume, accuracy and precision of digital geographic information have increased, concerns regarding individual privacy and confidentiality have come to the forefront. Not only do these challenge a basic tenet underlying the advancement of science by posing substantial obstacles to the sharing of data to validate research results, but they are obstacles to conducting certain research projects in the first place. Geospatial cryptography involves the specification, design, implementation and application of cryptographic techniques to address privacy, confidentiality and security concerns for geographically referenced data. This article defines geospatial cryptography and demonstrates its application in cancer control and surveillance. Four use cases are considered: (1) national-level de-duplication among state or province-based cancer registries; (2) sharing of confidential data across cancer registries to support case aggregation across administrative geographies; (3) secure data linkage; and (4) cancer cluster investigation and surveillance. A secure multi-party system for geospatial cryptography is developed. Solutions under geospatial cryptography are presented and computation time is calculated. As services provided by cancer registries to the research community, de-duplication, case aggregation across administrative geographies and secure data linkage are often time-consuming and in some instances precluded by confidentiality and security concerns. Geospatial cryptography provides secure solutions that hold significant promise for addressing these concerns and for accelerating the pace of research with human subjects data residing in our nation's cancer registries. Pursuit of the research directions posed herein conceivably would lead to a geospatially encrypted geographic information system (GEGIS) designed specifically to promote the sharing and spatial analysis of confidential data. Geospatial cryptography holds substantial promise for accelerating the

  19. DEVELOPING THE TRANSDISCIPLINARY AGING RESEARCH AGENDA: NEW DEVELOPMENTS IN BIG DATA.

    Science.gov (United States)

    Callaghan, Christian William

    2017-07-19

    In light of dramatic advances in big data analytics and the application of these advances in certain scientific fields, new potentialities exist for breakthroughs in aging research. Translating these new potentialities to research outcomes for aging populations, however, remains a challenge, as underlying technologies which have enabled exponential increases in 'big data' have not yet enabled a commensurate era of 'big knowledge,' or similarly exponential increases in biomedical breakthroughs. Debates also reveal differences in the literature, with some arguing big data analytics heralds a new era associated with the 'end of theory' or which makes the scientific method obsolete, where correlation supercedes causation, whereby science can advance without theory and hypotheses testing. On the other hand, others argue theory cannot be subordinate to data, no matter how comprehensive data coverage can ultimately become. Given these two tensions, namely between exponential increases in data absent exponential increases in biomedical research outputs, and between the promise of comprehensive data coverage and data-driven inductive versus theory-driven deductive modes of enquiry, this paper seeks to provide a critical review of certain theory and literature that offers useful perspectives of certain developments in big data analytics and their theoretical implications for aging research. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  20. Architectural Strategies for Enabling Data-Driven Science at Scale

    Science.gov (United States)

    Crichton, D. J.; Law, E. S.; Doyle, R. J.; Little, M. M.

    2017-12-01

    The analysis of large data collections from NASA or other agencies is often executed through traditional computational and data analysis approaches, which require users to bring data to their desktops and perform local data analysis. Alternatively, data are hauled to large computational environments that provide centralized data analysis via traditional High Performance Computing (HPC). Scientific data archives, however, are not only growing massive, but are also becoming highly distributed. Neither traditional approach provides a good solution for optimizing analysis into the future. Assumptions across the NASA mission and science data lifecycle, which historically assume that all data can be collected, transmitted, processed, and archived, will not scale as more capable instruments stress legacy-based systems. New paradigms are needed to increase the productivity and effectiveness of scientific data analysis. This paradigm must recognize that architectural and analytical choices are interrelated, and must be carefully coordinated in any system that aims to allow efficient, interactive scientific exploration and discovery to exploit massive data collections, from point of collection (e.g., onboard) to analysis and decision support. The most effective approach to analyzing a distributed set of massive data may involve some exploration and iteration, putting a premium on the flexibility afforded by the architectural framework. The framework should enable scientist users to assemble workflows efficiently, manage the uncertainties related to data analysis and inference, and optimize deep-dive analytics to enhance scalability. In many cases, this "data ecosystem" needs to be able to integrate multiple observing assets, ground environments, archives, and analytics, evolving from stewardship of measurements of data to using computational methodologies to better derive insight from the data that may be fused with other sets of data. This presentation will discuss

  1. RCSB Protein Data Bank: Sustaining a living digital data resource that enables breakthroughs in scientific research and biomedical education.

    Science.gov (United States)

    Burley, Stephen K; Berman, Helen M; Christie, Cole; Duarte, Jose M; Feng, Zukang; Westbrook, John; Young, Jasmine; Zardecki, Christine

    2018-01-01

    The Protein Data Bank (PDB) is one of two archival resources for experimental data central to biomedical research and education worldwide (the other key Primary Data Archive in biology being the International Nucleotide Sequence Database Collaboration). The PDB currently houses >134,000 atomic level biomolecular structures determined by crystallography, NMR spectroscopy, and 3D electron microscopy. It was established in 1971 as the first open-access, digital-data resource in biology, and is managed by the Worldwide Protein Data Bank partnership (wwPDB; wwpdb.org). US PDB operations are conducted by the RCSB Protein Data Bank (RCSB PDB; RCSB.org; Rutgers University and UC San Diego) and funded by NSF, NIH, and DoE. The RCSB PDB serves as the global Archive Keeper for the wwPDB. During calendar 2016, >591 million structure data files were downloaded from the PDB by Data Consumers working in every sovereign nation recognized by the United Nations. During this same period, the RCSB PDB processed >5300 new atomic level biomolecular structures plus experimental data and metadata coming into the archive from Data Depositors working in the Americas and Oceania. In addition, RCSB PDB served >1 million RCSB.org users worldwide with PDB data integrated with ∼40 external data resources providing rich structural views of fundamental biology, biomedicine, and energy sciences, and >600,000 PDB101.rcsb.org educational website users around the globe. RCSB PDB resources are described in detail together with metrics documenting the impact of access to PDB data on basic and applied research, clinical medicine, education, and the economy. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

  2. Enabling a new Paradigm to Address Big Data and Open Science Challenges

    Science.gov (United States)

    Ramamurthy, Mohan; Fisher, Ward

    2017-04-01

    Data are not only the lifeblood of the geosciences but they have become the currency of the modern world in science and society. Rapid advances in computing, communi¬cations, and observational technologies — along with concomitant advances in high-resolution modeling, ensemble and coupled-systems predictions of the Earth system — are revolutionizing nearly every aspect of our field. Modern data volumes from high-resolution ensemble prediction/projection/simulation systems and next-generation remote-sensing systems like hyper-spectral satellite sensors and phased-array radars are staggering. For example, CMIP efforts alone will generate many petabytes of climate projection data for use in assessments of climate change. And NOAA's National Climatic Data Center projects that it will archive over 350 petabytes by 2030. For researchers and educators, this deluge and the increasing complexity of data brings challenges along with the opportunities for discovery and scientific breakthroughs. The potential for big data to transform the geosciences is enormous, but realizing the next frontier depends on effectively managing, analyzing, and exploiting these heterogeneous data sources, extracting knowledge and useful information from heterogeneous data sources in ways that were previously impossible, to enable discoveries and gain new insights. At the same time, there is a growing focus on the area of "Reproducibility or Replicability in Science" that has implications for Open Science. The advent of cloud computing has opened new avenues for not only addressing both big data and Open Science challenges to accelerate scientific discoveries. However, to successfully leverage the enormous potential of cloud technologies, it will require the data providers and the scientific communities to develop new paradigms to enable next-generation workflows and transform the conduct of science. Making data readily available is a necessary but not a sufficient condition. Data providers

  3. Research Experiences in Community College Science Programs

    Science.gov (United States)

    Beauregard, A.

    2011-12-01

    The benefits of student access to scientific research opportunities and the use of data in curriculum and student inquiry-driven approaches to teaching as effective tools in science instruction are compelling (i.e., Ledley, et al., 2008; Gawel & Greengrove, 2005; Macdonald, et al., 2005; Harnik & Ross. 2003). Unfortunately, these experiences are traditionally limited at community colleges due to heavy faculty teaching loads, a focus on teaching over research, and scarce departmental funds. Without such hands-on learning activities, instructors may find it difficult to stimulate excitement about science in their students, who are typically non-major and nontraditional. I present two different approaches for effectively incorporating research into the community college setting that each rely on partnerships with other institutions. The first of these is a more traditional approach for providing research experiences to undergraduate students, though such experiences are limited at community colleges, and involves student interns working on a research project under the supervision of a faculty member. Specifically, students participate in a water quality assessment study of two local bayous. Students work on different aspects of the project, including water sample collection, bio-assay incubation experiments, water quality sample analysis, and collection and identification of phytoplankton. Over the past four years, nine community college students, as well as two undergraduate students and four graduate students from the local four-year university have participated in this research project. Aligning student and faculty research provides community college students with the unique opportunity to participate in the process of active science and contribute to "real" scientific research. Because students are working in a local watershed, these field experiences provide a valuable "place-based" educational opportunity. The second approach links cutting-edge oceanographic

  4. Art experience in research with children

    DEFF Research Database (Denmark)

    Nielsen, Anne Maj

    In art and drawing children can visually articulate pre-reflexive phenomena such as feelings, emotions, experiences, intentions and engagement. Research can include children’s art and drawings to study such phenomena and how they can be articulated and thematized in non-verbal/visual articulation...... and discuss how the construct ‘aesthetic object’ may offer researchers an approach to non-verbal/visual articulation that can explicitly include the researcher’s sensory and aesthetic experiences as knowledge. Examples from studies including children’s art and drawings are part of the presentation. The paper....... The researcher’s pre-reflexive sensory and aesthetic experiences often contribute to the immediate interpretations of such data. It is a challenge to make the ways in which art and drawings in specific ways contribute to interpretation and knowledge transparent in research. The aim of this paper is to describe...

  5. Data quality can make or break a research infrastructure

    Science.gov (United States)

    Pastorello, G.; Gunter, D.; Chu, H.; Christianson, D. S.; Trotta, C.; Canfora, E.; Faybishenko, B.; Cheah, Y. W.; Beekwilder, N.; Chan, S.; Dengel, S.; Keenan, T. F.; O'Brien, F.; Elbashandy, A.; Poindexter, C.; Humphrey, M.; Papale, D.; Agarwal, D.

    2017-12-01

    Research infrastructures (RIs) commonly support observational data provided by multiple, independent sources. Uniformity in the data distributed by such RIs is important in most applications, e.g., in comparative studies using data from two or more sources. Achieving uniformity in terms of data quality is challenging, especially considering that many data issues are unpredictable and cannot be detected until a first occurrence of the issue. With that, many data quality control activities within RIs require a manual, human-in-the-loop element, making it an expensive activity. Our motivating example is the FLUXNET2015 dataset - a collection of ecosystem-level carbon, water, and energy fluxes between land and atmosphere from over 200 sites around the world, some sites with over 20 years of data. About 90% of the human effort to create the dataset was spent in data quality related activities. Based on this experience, we have been working on solutions to increase the automation of data quality control procedures. Since it is nearly impossible to fully automate all quality related checks, we have been drawing from the experience with techniques used in software development, which shares a few common constraints. In both managing scientific data and writing software, human time is a precious resource; code bases, as Science datasets, can be large, complex, and full of errors; both scientific and software endeavors can be pursued by individuals, but collaborative teams can accomplish a lot more. The lucrative and fast-paced nature of the software industry fueled the creation of methods and tools to increase automation and productivity within these constraints. Issue tracking systems, methods for translating problems into automated tests, powerful version control tools are a few examples. Terrestrial and aquatic ecosystems research relies heavily on many types of observational data. As volumes of data collection increases, ensuring data quality is becoming an unwieldy

  6. Exploring factors related to the translation of collaborative research learning experiences into clinical practice: Opportunities and tensions.

    Science.gov (United States)

    Fletcher, Simon; Whiting, Cheryl; Boaz, Annette; Reeves, Scott

    2017-07-01

    Providing training opportunities to develop research skills for clinical staff has been prioritised in response to the need for improving the evidence base underpinning the delivery of care. By exploring the experiences of a number of former participants of a multidisciplinary postgraduate research course, this article explores the factors that have enabled and impeded staff to translate their learnt research skills into clinical practice. Adopting an exploratory case study approach, 16 interviews with 5 cohorts of Masters by Research in Clinical Practice (MResCP) graduates were undertaken. The interviews explored graduates' course experiences and their subsequent attempts to undertake clinical research. Analysis of the data indicated that although participants valued their interactions with colleagues from different professions and felt they gained useful research skills/knowledge, upon returning to clinical practice, they encountered a number of barriers which restricted their ability to apply their research expertise. Professional isolation, issues of hierarchy, and a lack of organisational support were key to limiting their ability to undertake clinical research. Further work is needed to explore in more depth how (i) these barriers can be overcome and (ii) how taught collaborative research skills can be more effectively translated into practice.

  7. Common data elements for spinal cord injury clinical research

    DEFF Research Database (Denmark)

    Biering-Sørensen, F; Alai, S; Anderson, K.

    2015-01-01

    Institutes of Health. SETTING: International Working Groups. METHODS: Nine working groups composed of international experts reviewed existing CDEs and instruments, created new elements when needed and provided recommendations for SCI clinical research. The project was carried out in collaboration...... of CDEs can facilitate SCI clinical research and trial design, data sharing and retrospective analyses. Continued international collaboration will enable consistent data collection and reporting, and will help ensure that the data elements are updated, reviewed and broadcast as additional evidence......OBJECTIVES: To develop a comprehensive set of common data elements (CDEs), data definitions, case report forms and guidelines for use in spinal cord injury (SCI) clinical research, as part of the CDE project at the National Institute of Neurological Disorders and Stroke (NINDS) of the US National...

  8. Development of Data Acquisition Set-up for Steady-state Experiments

    Science.gov (United States)

    Srivastava, Amit K.; Gupta, Arnab D.; Sunil, S.; Khan, Ziauddin

    2017-04-01

    For short duration experiments, generally digitized data is transferred for processing and storage after the experiment whereas in case of steady-state experiment the data is acquired, processed, displayed and stored continuously in pipelined manner. This requires acquiring data through special techniques for storage and on-the-go viewing data to display the current data trends for various physical parameters. A small data acquisition set-up is developed for continuously acquiring signals from various physical parameters at different sampling rate for long duration experiment. This includes the hardware set-up for signal digitization, Field Programmable Gate Arrays (FPGA) based timing system for clock synchronization and event/trigger distribution, time slicing of data streams for storage of data chunks to enable viewing of data during acquisition and channel profile display through down sampling etc. In order to store a long data stream of indefinite/long time duration, the data stream is divided into data slices/chunks of user defined time duration. Data chunks avoid the problem of non-access of server data until the channel data file is closed at the end of the long duration experiment. A graphical user interface has been developed in Lab VIEW application development environment for configuring the data acquisition hardware and storing data chunks on local machine as well as at remote data server through Python for further data access. The data plotting and analysis utilities have been developed with Python software, which provides tools for further data processing. This paper describes the development and implementation of data acquisition for steady-state experiment.

  9. Consistent data recording across a health system and web-enablement allow service quality comparisons: online data for commissioning dermatology services.

    Science.gov (United States)

    Dmitrieva, Olga; Michalakidis, Georgios; Mason, Aaron; Jones, Simon; Chan, Tom; de Lusignan, Simon

    2012-01-01

    A new distributed model of health care management is being introduced in England. Family practitioners have new responsibilities for the management of health care budgets and commissioning of services. There are national datasets available about health care providers and the geographical areas they serve. These data could be better used to assist the family practitioner turned health service commissioners. Unfortunately these data are not in a form that is readily usable by these fledgling family commissioning groups. We therefore Web enabled all the national hospital dermatology treatment data in England combining it with locality data to provide a smart commissioning tool for local communities. We used open-source software including the Ruby on Rails Web framework and MySQL. The system has a Web front-end, which uses hypertext markup language cascading style sheets (HTML/CSS) and JavaScript to deliver and present data provided by the database. A combination of advanced caching and schema structures allows for faster data retrieval on every execution. The system provides an intuitive environment for data analysis and processing across a large health system dataset. Web-enablement has enabled data about in patients, day cases and outpatients to be readily grouped, viewed, and linked to other data. The combination of web-enablement, consistent data collection from all providers; readily available locality data; and a registration based primary system enables the creation of data, which can be used to commission dermatology services in small areas. Standardized datasets collected across large health enterprises when web enabled can readily benchmark local services and inform commissioning decisions.

  10. A Cyber-Based Data-Enabled Virtual Organization for Wind Load Effects on Civil Infrastructures: VORTEX-Winds

    Directory of Open Access Journals (Sweden)

    Ahsan Kareem

    2017-08-01

    Full Text Available Despite many advances in the area of wind effects on structures in recent decades, research has been traditionally conducted within limited resources scattered geographically. With the trend toward increasingly complex designs of civil infrastructure combined with the escalating potential for losses by extreme wind events, a new culture of research needs to be established based on innovative and collaborative solutions for better management of the impact of extreme wind events. To address this change, this paper presents a new paradigm of a multiscale cyber-based laboratory framework for the analysis/design, modeling, and simulation of wind load effects based on an ongoing collaborative cyberinfrastructure-based platform, Virtual Organization for Reducing the Toll of EXtreme Winds (VORTEX-Winds, https://vortex-winds.org, and discusses its current status since its inception in 2007 and ongoing developments. This collaborative framework as it evolves would enable a paradigm shift by offering advanced cyber-enabled modules (e-modules for accelerating advances in research and education to achieve improved understanding and better modeling of wind effects on structures. Accordingly, it will enhance wind community’s analysis and design capabilities to address next-generation challenges posed by wind. Through empowering those without computational or experimental resources, the e-modules will encompass a large set of subject areas and topics categorized as Database-enabled design, Full-scale/Field site data repository, Statistical/Stochastic toolboxes, Tele-experimentation, Uncertainty modeling, Damage assessment, and Computational platforms. This prototype will allow access to the individual e-module, while it is envisaged that next level of development in VORTEX-Winds will have the capability for an automated and integrated analysis/design through a nexus of e-modules. A highlight of the e-modules currently completed or in development is presented

  11. The Stanford Automated Mounter: Enabling High-Throughput Protein Crystal Screening at SSRL

    International Nuclear Information System (INIS)

    Smith, C.A.; Cohen, A.E.

    2009-01-01

    The macromolecular crystallography experiment lends itself perfectly to high-throughput technologies. The initial steps including the expression, purification, and crystallization of protein crystals, along with some of the later steps involving data processing and structure determination have all been automated to the point where some of the last remaining bottlenecks in the process have been crystal mounting, crystal screening, and data collection. At the Stanford Synchrotron Radiation Laboratory, a National User Facility that provides extremely brilliant X-ray photon beams for use in materials science, environmental science, and structural biology research, the incorporation of advanced robotics has enabled crystals to be screened in a true high-throughput fashion, thus dramatically accelerating the final steps. Up to 288 frozen crystals can be mounted by the beamline robot (the Stanford Auto-Mounting System) and screened for diffraction quality in a matter of hours without intervention. The best quality crystals can then be remounted for the collection of complete X-ray diffraction data sets. Furthermore, the entire screening and data collection experiment can be controlled from the experimenter's home laboratory by means of advanced software tools that enable network-based control of the highly automated beamlines.

  12. Enabling analytics on sensitive medical data with secure multi-party computation

    NARCIS (Netherlands)

    M. Veeningen (Meilof); S. Chatterjea (Supriyo); A.Z. Horváth (Anna Zsófia); G. Spindler (Gerald); E. Boersma (Eric); P. van der Spek (Peter); O. van der Galiën (Onno); J. Gutteling (Job); W. Kraaij (Wessel); P.J.M. Veugen (Thijs)

    2018-01-01

    textabstractWhile there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multiparty computation can enable such data

  13. Big biomedical data and cardiovascular disease research: opportunities and challenges.

    Science.gov (United States)

    Denaxas, Spiros C; Morley, Katherine I

    2015-07-01

    Electronic health records (EHRs), data generated and collected during normal clinical care, are increasingly being linked and used for translational cardiovascular disease research. Electronic health record data can be structured (e.g. coded diagnoses) or unstructured (e.g. clinical notes) and increasingly encapsulate medical imaging, genomic and patient-generated information. Large-scale EHR linkages enable researchers to conduct high-resolution observational and interventional clinical research at an unprecedented scale. A significant amount of preparatory work and research, however, is required to identify, obtain, and transform raw EHR data into research-ready variables that can be statistically analysed. This study critically reviews the opportunities and challenges that EHR data present in the field of cardiovascular disease clinical research and provides a series of recommendations for advancing and facilitating EHR research.

  14. A cloud-based data network approach for translational cancer research.

    Science.gov (United States)

    Xing, Wei; Tsoumakos, Dimitrios; Ghanem, Moustafa

    2015-01-01

    We develop a new model and associated technology for constructing and managing self-organizing data to support translational cancer research studies. We employ a semantic content network approach to address the challenges of managing cancer research data. Such data is heterogeneous, large, decentralized, growing and continually being updated. Moreover, the data originates from different information sources that may be partially overlapping, creating redundancies as well as contradictions and inconsistencies. Building on the advantages of elasticity of cloud computing, we deploy the cancer data networks on top of the CELAR Cloud platform to enable more effective processing and analysis of Big cancer data.

  15. Collection of measurement data from in-situ experiment for performance confirmation of engineered barrier system at Horonobe Underground Research Laboratory. FY2014

    International Nuclear Information System (INIS)

    Nakayama, Masashi; Ohno, Hirokazu; Nakayama, Mariko; Kobayashi, Masato

    2015-09-01

    The Horonobe Underground Research Laboratory (URL) Project has being pursued by Japan Atomic Energy Agency (JAEA) to enhance the reliability of relevant disposal technologies through investigations of the deep geological environment within the host sedimentary formation at Horonobe, northern Hokkaido. The URL Project consists of two major research areas, “Geoscientific Research” and “Research and Development on Geological Disposal Technologies”, and proceeds in three overlapping phases, “Phase I: Surface-based investigations”, “Phase II: Investigations during tunnel excavation” and “Phase III: Investigations in the underground facilities”, over a period of around 20 years. Phase III investigation was started in 2010 fiscal year. The in-situ experiment for performance confirmation of engineered barrier system (EBS experiment) had been prepared from 2013 to 2014 fiscal year at G.L.-350m gallery, and heating by electric heater in simulated overpack had started in January, 2015. One of objectives of the experiment is acquiring data concerned with Thermal – Hydrological – Mechanical – Chemical (THMC) coupled behavior. These data will be used in order to confirm the performance of engineered barrier system. This report summarizes the measurement data acquired from the EBS experiment from December, 2014 to March, 2015. The summarized data of the EBS experiment will be published periodically. A CD-ROM is attached as an appendix. (J.P.N)

  16. Creativity and Innovation in Health Care: Tapping Into Organizational Enablers Through Human-Centered Design.

    Science.gov (United States)

    Zuber, Christi Dining; Moody, Louise

    There is an increasing drive in health care for creativity and innovation to tackle key health challenges, improve quality and access, and reduce harm and costs. Human-centered design (HCD) is a potential approach to achieving organizational innovation. However, research suggests the nursing workforce feels unsupported to take the risks needed for innovation, and leaders may not understand the conditions required to fully support them. The aim of this study was to identify enabling conditions that support frontline nurses in their attempts to behave as champions of innovation and change. An HCD workshop was undertaken with 125 nurses employed in clinical practice at Kaiser Permanente. The workshop included empathy mapping and semistructured questions that probed participant experiences with innovation and change. The data were collated and thematic analysis undertaken through a Grounded Theory approach. The data were analyzed to identify key enabling conditions. Seven enablers emerged: personal need for a solution; challenges that have meaningful purpose; clarity of goal and control of resources; active experimentation; experiences indicating progress; positive encouragement and confidence; and provision of psychological safety. These enablers were then translated into pragmatic guidelines for leaders on how the tools of HCD may be leveraged for innovation and change in health care.

  17. Reliability data bank in electronics: ITALTEL experience over 10 years of operation

    International Nuclear Information System (INIS)

    Turconi, G.

    1986-01-01

    The purpose of this paper is to show the Italtel Reliability Data Bank experience in electronics after ten years from data bank creation. Technological evolution on systems and equipment have originated a reliability data bank evolution in order to maintain and improve its performances. This paper will describe the concepts employed to design the today data bank features enabling it to be an important Company tool for reliability activities. (orig.)

  18. Enabling Data Access for Environmental Monitoring: SERVIR West Africa

    Science.gov (United States)

    Yetman, G.; de Sherbinin, A. M.

    2017-12-01

    SERVIR is a join effort between NASA and the U.S. Agency for International Development to form regional partnerships and bring satellite-based earth monitoring and geographic information technologies to bear on environmental issues. The recently established SERVIR node for West Africa aims to "connect space to villages" and enable response to environmental change at the national and local level through partnering with a network of organizations in the region. Comprehensive services—data streams, analysis methods and algorithms, and information products for decision making—to support environmental monitoring of five critical issues identified by West African network members are being designed and developed: ephemeral water, charcoal production, locusts, groundwater, and land use/land cover change. Additionally, climate change information is critical for planning and context in each of these issues. The selection of data and methods is a collaborative effort, with experts in the region working with experts at NASA and the scientific community to best meet information monitoring requirements. Design and delivery of these services requires capacity development in a number of areas, including best practices in data management, analysis methods for combining multiple data streams, and information technology infrastructure. Two research centers at Columbia University are implementing partners for SERVIR West Africa, acting to support capacity development in network members through a combination of workshops, training, and implementation of technologies in the region. The presentation will focus on efforts by these centers to assess current capabilities and improve capacity through gathering requirements, system design, technology selection, technology deployment, training, and workshops.

  19. Active Provenance in Data-intensive Research

    Science.gov (United States)

    Spinuso, Alessandro; Mihajlovski, Andrej; Filgueira, Rosa; Atkinson, Malcolm

    2017-04-01

    Scientific communities are building platforms where the usage of data-intensive workflows is crucial to conduct their research campaigns. However managing and effectively support the understanding of the 'live' processes, fostering computational steering, sharing and re-use of data and methods, present several bottlenecks. These are often caused by the poor level of documentation on the methods and the data and how users interact with it. This work wants to explore how in such systems, flexibility in the management of the provenance and its adaptation to the different users and application contexts can lead to new opportunities for its exploitation, improving productivity. In particular, this work illustrates a conceptual and technical framework enabling tunable and actionable provenance in data-intensive workflow systems in support of reproducible science. It introduces the concept of Agile data-intensive systems to define the characteristic of our target platform. It shows a novel approach to the integration of provenance mechanisms, offering flexibility in the scale and in the precision of the provenance data collected, ensuring its relevance to the domain of the data-intensive task, fostering its rapid exploitation. The contributions address aspects of the scale of the provenance records, their usability and active role in the research life-cycle. We will discuss the use of dynamically generated provenance types as the approach for the integration of provenance mechanisms into a data-intensive workflow system. Enabling provenance can be transparent to the workflow user and developer, as well as fully controllable and customisable, depending from their expertise and the application's reproducibility, monitoring and validation requirements. The API that allows the realisation and adoption of a provenance type is presented, especially for what concerns the support of provenance profiling, contextualisation and precision. An actionable approach to provenance

  20. Archiving Data from New Survey Technologies: Lessons Learned on Enabling Research with High-Precision Data While Preserving Participant Privacy: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Gonder, J.; Burton, E.; Murakami, E.

    2014-11-01

    During the past 15 years, increasing numbers of organizations and planning agencies have begun collecting high-resolution Global Positioning System (GPS) travel data. Despite the significant effort and expense to collect it, privacy concerns often lead to underutilization of the data. To address this dilemma of providing data access while preserving privacy, the National Renewable Energy Laboratory, with support from the U.S. Department of Transportation and U.S. Department of Energy, established the Transportation Secure Data Center (TSDC). Lessons drawn from best-practice examples from other data centers have helped shape the structure and operating procedures for the TSDC, which functions under the philosophy of first and foremost preserving privacy, but doing so in a way that balances security with accessibility and usability of the data for legitimate research. This paper provides details about the TSDC approach toward achieving these goals, which has included creating a secure enclave with no external access for backing up and processing raw data, a publicly accessible website for downloading cleansed data, and a secure portal environment through which approved users can work with detailed spatial data using a variety of tools and reference information. This paper also describes lessons learned from operating the TSDC with respect to improvements in GPS data handling, processing, and user support, along with plans for continual enhancements to better support the needs of both data providers and users and to thus advance the research value derived from such valuable data.

  1. Enabling Interoperable and Selective Data Sharing among Social Networking Sites

    Science.gov (United States)

    Shin, Dongwan; Lopes, Rodrigo

    With the widespread use of social networking (SN) sites and even introduction of a social component in non-social oriented services, there is a growing concern over user privacy in general, how to handle and share user profiles across SN sites in particular. Although there have been several proprietary or open source-based approaches to unifying the creation of third party applications, the availability and retrieval of user profile information are still limited to the site where the third party application is run, mostly devoid of the support for data interoperability. In this paper we propose an approach to enabling interopearable and selective data sharing among SN sites. To support selective data sharing, we discuss an authenticated dictionary (ADT)-based credential which enables a user to share only a subset of her information certified by external SN sites with applications running on an SN site. For interoperable data sharing, we propose an extension to the OpenSocial API so that it can provide an open source-based framework for allowing the ADT-based credential to be used seamlessly among different SN sites.

  2. Linguistic analysis of project ownership for undergraduate research experiences.

    Science.gov (United States)

    Hanauer, D I; Frederick, J; Fotinakes, B; Strobel, S A

    2012-01-01

    We used computational linguistic and content analyses to explore the concept of project ownership for undergraduate research. We used linguistic analysis of student interview data to develop a quantitative methodology for assessing project ownership and applied this method to measure degrees of project ownership expressed by students in relation to different types of educational research experiences. The results of the study suggest that the design of a research experience significantly influences the degree of project ownership expressed by students when they describe those experiences. The analysis identified both positive and negative aspects of project ownership and provided a working definition for how a student experiences his or her research opportunity. These elements suggest several features that could be incorporated into an undergraduate research experience to foster a student's sense of project ownership.

  3. NATO Advanced Study Institute on Nano-Optics : Principles Enabling Basic Research and Applications

    CERN Document Server

    Collins, John; Silvestri, Luciano

    2017-01-01

    This book provides a comprehensive overview of nano-optics, including basic theory, experiment and applications, particularly in nanofabrication and optical characterization. The contributions clearly demonstrate how advances in nano-optics and photonics have stimulated progress in nanoscience and -fabrication, and vice versa. Their expert authors address topics such as three-dimensional optical lithography and microscopy beyond the Abbe diffraction limit, optical diagnostics and sensing, optical data- and telecommunications, energy-efficient lighting, and efficient solar energy conversion. Nano-optics emerges as a key enabling technology of the 21st century. This work will appeal to a wide readership, from physics through chemistry, to biology and engineering. The contributions that appear in this volume were presented at a NATO Advanced Study Institute held in Erice, 4-19 July, 2015.

  4. The Undergraduate Teaching Assistant Experience Offers Opportunities Similar to the Undergraduate Research Experience

    Directory of Open Access Journals (Sweden)

    Kelly A. Schalk

    2009-12-01

    Full Text Available There has been a growing concern in higher education about our failure to produce scientifically trained workers and scientifically literate citizens. Active-learning and research-oriented activities are posited as ways to give students a deeper understanding of science. We report on an undergraduate teaching assistant (UTA experience and suggest that students who participate as a UTA obtain benefits analogous to those who participate as an undergraduate research assistant (URA. We examined the experiences of 24 undergraduates acting as UTAs in a general microbiology course. Self-reported gains by the UTAs were supported by observational data from undergraduates in the course who were mentored by the UTAs and by the graduate teaching assistants (GTAs with whom the UTAs worked. Specifically, data from the UTAs’ journals and self-reported Likert scales and rubrics indicated that our teaching assistants developed professional characteristics such as self-confidence and communication and leadership skills, while they acquired knowledge of microbiology content and laboratory skills. Data from the undergraduate Likert scale as well as the pre- and post-GTA rubrics further confirmed our UTA’s data interpretations. These findings are significant because they offer empirical data to support the suggestion that the UTA experience is an effective option for developing skills and knowledge in undergraduates that are essential for careers in science. The UTA experience provides a valuable alternative to the URA experience.

  5. Longitudinal research and data collection in primary care.

    Science.gov (United States)

    van Weel, Chris

    2005-01-01

    This article reviews examples of and experience with longitudinal research in family medicine. The objective is to use this empirical information to formulate recommendations for improving longitudinal research. The article discusses 3 longitudinal studies from the Nijmegen academic family practice research network: 1 on the prognosis of depression and 1 each on the prognosis of and outcomes of care for type 2 diabetes mellitus. The Nijmegen network has recorded all episodes of morbidity encountered in Dutch family medicine since 1971 in a stable practice population. This network's experience is evaluated to identify lessons that may help other practice-based research networks (PBRNs) in pursuing longitudinal research. In terms of external conditions (conditions related to the general setting), the stability of a population and a high level of continuity of care substantially enhance the ability to perform longitudinal research. In terms of internal conditions (conditions related to the PBRN), motivation of family physicians and their staff to conduct ongoing data collection, and their ownership of the data are key for success. Other critical internal conditions include standardization of data; collection of data by clinician-friendly means; training of family physicians and their staff in data collection, as well as meetings for discussion of this task; provision of feedback to practices on the research findings; use of standard procedures to promote adherence to data collection; availability of facilities for regular measurement of patients' health status or chart review; and use of mechanisms for tracking patients who leave the practice area. Insight from existing experience suggests that longitudinal research can be enhanced in PBRNs. The best way forward is to build longitudinal data collection by drawing on lessons from successful studies. Primary care research policy should advocate for a role of longitudinal research and stimulate its development in PBRNs

  6. Research experience in Maine leads to teacher and student success in Texas

    Science.gov (United States)

    Slade-Redden, D.; Incze, L.; Census Of Marine Life-Maine

    2010-12-01

    As a High School science teacher it is my responsibility to present curriculum, to create enthusiasm for science, and to instill a passion and love for science in my students. Through a research experience as an ARMADA master teacher my passion and enthusiasm for the ocean was rekindled in the Gulf of Maine. Topics I had taught for years came alive in front of my eyes, and I was able to experience science to its fullest. I brought home many photographs, valuable information, and new enthusiasm to my students. I began a program called S.A.N.D. (Students As Nature Directors). In this program my students teach 3rd graders about the oceans and its many wonders. Also, I have incorporated hands-on research based projects. The research experience has enabled my students to become more scientifically literate and capable of sharing scientific knowledge with others. This presentation will show how research/teacher partnerships benefit students as well as teachers and how my students and district have benefited from my experience as an ARMADA master teacher. Author: Debra Slade-Redden Author #2: Lew Incze

  7. Ensuring VGI Credibility in Urban-Community Data Generation: A Methodological Research Design

    Directory of Open Access Journals (Sweden)

    Jamie O'Brien

    2016-06-01

    Full Text Available In this paper we outline the methodological development of current research into urban community formations based on combinations of qualitative (volunteered and quantitative (spatial analytical and geo-statistical data. We outline a research design that addresses problems of data quality relating to credibility in volunteered geographic information (VGI intended for Web-enabled participatory planning. Here we have drawn on a dual notion of credibility in VGI data, and propose a methodological workflow to address its criteria. We propose a ‘super-positional’ model of urban community formations, and report on the combination of quantitative and participatory methods employed to underpin its integration. The objective of this methodological phase of study is to enhance confidence in the quality of data for Web-enabled participatory planning. Our participatory method has been supported by rigorous quantification of area characteristics, including participant communities’ demographic and socio-economic contexts. This participatory method provided participants with a ready and accessible format for observing and mark-making, which allowed the investigators to iterate rapidly a system design based on participants’ responses to the workshop tasks. Participatory workshops have involved secondary school-age children in socio-economically contrasting areas of Liverpool (Merseyside, UK, which offers a test-bed for comparing communities’ formations in comparative contexts, while bringing an under-represented section of the population into a planning domain, whose experience may stem from public and non-motorised transport modalities. Data has been gathered through one-day participatory workshops, featuring questionnaire surveys, local site analysis, perception mapping and brief, textual descriptions. This innovative approach will support Web-based participation among stakeholding planners, who may benefit from well-structured, community

  8. DOE High Performance Computing Operational Review (HPCOR): Enabling Data-Driven Scientific Discovery at HPC Facilities

    Energy Technology Data Exchange (ETDEWEB)

    Gerber, Richard; Allcock, William; Beggio, Chris; Campbell, Stuart; Cherry, Andrew; Cholia, Shreyas; Dart, Eli; England, Clay; Fahey, Tim; Foertter, Fernanda; Goldstone, Robin; Hick, Jason; Karelitz, David; Kelly, Kaki; Monroe, Laura; Prabhat,; Skinner, David; White, Julia

    2014-10-17

    U.S. Department of Energy (DOE) High Performance Computing (HPC) facilities are on the verge of a paradigm shift in the way they deliver systems and services to science and engineering teams. Research projects are producing a wide variety of data at unprecedented scale and level of complexity, with community-specific services that are part of the data collection and analysis workflow. On June 18-19, 2014 representatives from six DOE HPC centers met in Oakland, CA at the DOE High Performance Operational Review (HPCOR) to discuss how they can best provide facilities and services to enable large-scale data-driven scientific discovery at the DOE national laboratories. The report contains findings from that review.

  9. Enabling the Public to Experience Science from Beginning to End (Invited)

    Science.gov (United States)

    Trouille, L.; Chen, Y.; Lintott, C.; Lynn, S.; Simmons, B.; Smith, A.; Tremonti, C.; Whyte, L.; Willett, K.; Zevin, M.; Science Team; Moderator Team, G.

    2013-12-01

    In this talk we present the results of an experiment in collaborative research and article writing within the citizen science context. During July-September 2013, astronomers and the Zooniverse team ran Galaxy Zoo Quench (quench.galaxyzoo.org), investigating the mechanism(s) that recently and abruptly shut off star formation in a sample of post-quenched galaxies. Through this project, the public had the opportunity to experience the entire process of science, including galaxy classification, reading background literature, data analysis, discussion, debate, drawing conclusions, and writing an article to submit to a professional journal. The context was galaxy evolution, however, the lessons learned are applicable across the disciplines. The discussion will focus on how to leverage online tools to authentically engage the public in the entire process of science.

  10. TSTA piping and flame arrestor operating experience data

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, Lee C., E-mail: Lee.Cadwallader@inl.gov [Idaho National Laboratory, Idaho Falls, ID (United States); Willms, R. Scott [ITER International Organization, Cadarache (France)

    2015-10-15

    Highlights: • Experiences from the Tritium Systems Test Assembly were examined. • Failure rates of copper piping and a flame arrestor were calculated. • The calculated failure rates compared well to similar data from the literature. • Tritium component failure rate data support fusion safety assessment. - Abstract: The Tritium Systems Test Assembly (TSTA) was a facility dedicated to tritium handling technology and experiment research at the Los Alamos National Laboratory. The facility was operated with tritium for its research and development program from 1984 to 2001, running a prototype fusion fuel processing loop with ∼100 g of tritium as well as small experiments. There have been several operating experience reports written on this facility's operation and maintenance experience. This paper describes reliability analysis of two additional components from TSTA, small diameter copper gas piping that handled tritium in a nitrogen carrier gas, and the flame arrestor used in this piping system. The component failure rates for these components are discussed in this paper. Comparison data from other applications are also presented.

  11. Researching Human Experience: video intervention/prevention assessment (VIA

    Directory of Open Access Journals (Sweden)

    Jennifer Patashnick

    2005-05-01

    Full Text Available Human experience is a critical subject for research. By discussing Video Intervention/Prevention Assessment (VIA, a patient-centered health research method where patients teach their clinicians about living with a chronic condition through the creation of visual illness narratives, this paper examines the value of qualitative inquiry and why human experience rarely is investigated directly. An analysis of a sample VIA data is presented to demonstrate how, by utilizing grounded theory and qualitative analysis, one can derive rich and unique information from human experience.

  12. Reflecting on Collaborative Research into the Sustainability of Mediterranean Agriculture: A Case Study Using a Systematization of Experiences Approach

    Science.gov (United States)

    Guimarães, Helena; Fonseca, Cecília; Gonzalez, Carla; Pinto-Correia, Teresa

    2017-01-01

    This article describes how a research institute went about reviewing the relationship between its members and external research partners in engaging in collaborative research. A systematization of experiences (SE) process was implemented to enable such review and draw implications for the institute's strategy regarding research into the…

  13. J-TEXT WebScope: An efficient data access and visualization system for long pulse fusion experiment

    Energy Technology Data Exchange (ETDEWEB)

    Zheng, Wei, E-mail: zhenghaku@gmail.com [State Key Laboratory of Advanced Electromagnetic Engineering and Technology in Huazhong University of Science and Technology, Wuhan 430074 (China); School of Electrical and Electronic Engineering in Huazhong University of Science and Technology, Wuhan 430074 (China); Wan, Kuanhong; Chen, Zhi; Hu, Feiran; Liu, Qiang [State Key Laboratory of Advanced Electromagnetic Engineering and Technology in Huazhong University of Science and Technology, Wuhan 430074 (China); School of Electrical and Electronic Engineering in Huazhong University of Science and Technology, Wuhan 430074 (China)

    2016-11-15

    Highlights: • No matter how large the data is, the response time is always less than 500 milliseconds. • It is intelligent and just gives you the data you want. • It can be accessed directly over the Internet without installing special client software if you already have a browser. • Adopt scale and segment technology to organize data. • To support a new database for the WebScope is quite easy. • With the configuration stored in user’s profile, you have your own portable WebScope. - Abstract: Fusion research is an international collaboration work. To enable researchers across the world to visualize and analyze the experiment data, a web based data access and visualization tool is quite important [1]. Now, a new WebScope based on RIA (Rich Internet Application) is designed and implemented to meet these requirements. On the browser side, a fluent and intuitive interface is provided for researchers at J-TEXT laboratory and collaborators from all over the world to view experiment data and related metadata. The fusion experiments will feature long pulse and high sampling rate in the future. The data access and visualization system in this work has adopted segment and scale concept. Large data samples are re-sampled in different scales and then split into segments for instant response. It allows users to view extremely large data on the web browser efficiently, without worrying about the limitation on the size of the data. The HTML5 and JavaScript based web front-end can provide intuitive and fluent user experience. On the server side, a RESTful (Representational State Transfer) web API, which is based on ASP.NET MVC (Model View Controller), allows users to access the data and its metadata through HTTP (HyperText Transfer Protocol). An interface to the database has been designed to decouple the data access and visualization system from the data storage. It can be applied upon any data storage system like MDSplus or JTEXTDB, and this system is very easy to

  14. J-TEXT WebScope: An efficient data access and visualization system for long pulse fusion experiment

    International Nuclear Information System (INIS)

    Zheng, Wei; Wan, Kuanhong; Chen, Zhi; Hu, Feiran; Liu, Qiang

    2016-01-01

    Highlights: • No matter how large the data is, the response time is always less than 500 milliseconds. • It is intelligent and just gives you the data you want. • It can be accessed directly over the Internet without installing special client software if you already have a browser. • Adopt scale and segment technology to organize data. • To support a new database for the WebScope is quite easy. • With the configuration stored in user’s profile, you have your own portable WebScope. - Abstract: Fusion research is an international collaboration work. To enable researchers across the world to visualize and analyze the experiment data, a web based data access and visualization tool is quite important [1]. Now, a new WebScope based on RIA (Rich Internet Application) is designed and implemented to meet these requirements. On the browser side, a fluent and intuitive interface is provided for researchers at J-TEXT laboratory and collaborators from all over the world to view experiment data and related metadata. The fusion experiments will feature long pulse and high sampling rate in the future. The data access and visualization system in this work has adopted segment and scale concept. Large data samples are re-sampled in different scales and then split into segments for instant response. It allows users to view extremely large data on the web browser efficiently, without worrying about the limitation on the size of the data. The HTML5 and JavaScript based web front-end can provide intuitive and fluent user experience. On the server side, a RESTful (Representational State Transfer) web API, which is based on ASP.NET MVC (Model View Controller), allows users to access the data and its metadata through HTTP (HyperText Transfer Protocol). An interface to the database has been designed to decouple the data access and visualization system from the data storage. It can be applied upon any data storage system like MDSplus or JTEXTDB, and this system is very easy to

  15. A course-based research experience: how benefits change with increased investment in instructional time.

    Science.gov (United States)

    Shaffer, Christopher D; Alvarez, Consuelo J; Bednarski, April E; Dunbar, David; Goodman, Anya L; Reinke, Catherine; Rosenwald, Anne G; Wolyniak, Michael J; Bailey, Cheryl; Barnard, Daron; Bazinet, Christopher; Beach, Dale L; Bedard, James E J; Bhalla, Satish; Braverman, John; Burg, Martin; Chandrasekaran, Vidya; Chung, Hui-Min; Clase, Kari; Dejong, Randall J; Diangelo, Justin R; Du, Chunguang; Eckdahl, Todd T; Eisler, Heather; Emerson, Julia A; Frary, Amy; Frohlich, Donald; Gosser, Yuying; Govind, Shubha; Haberman, Adam; Hark, Amy T; Hauser, Charles; Hoogewerf, Arlene; Hoopes, Laura L M; Howell, Carina E; Johnson, Diana; Jones, Christopher J; Kadlec, Lisa; Kaehler, Marian; Silver Key, S Catherine; Kleinschmit, Adam; Kokan, Nighat P; Kopp, Olga; Kuleck, Gary; Leatherman, Judith; Lopilato, Jane; Mackinnon, Christy; Martinez-Cruzado, Juan Carlos; McNeil, Gerard; Mel, Stephanie; Mistry, Hemlata; Nagengast, Alexis; Overvoorde, Paul; Paetkau, Don W; Parrish, Susan; Peterson, Celeste N; Preuss, Mary; Reed, Laura K; Revie, Dennis; Robic, Srebrenka; Roecklein-Canfield, Jennifer; Rubin, Michael R; Saville, Kenneth; Schroeder, Stephanie; Sharif, Karim; Shaw, Mary; Skuse, Gary; Smith, Christopher D; Smith, Mary A; Smith, Sheryl T; Spana, Eric; Spratt, Mary; Sreenivasan, Aparna; Stamm, Joyce; Szauter, Paul; Thompson, Jeffrey S; Wawersik, Matthew; Youngblom, James; Zhou, Leming; Mardis, Elaine R; Buhler, Jeremy; Leung, Wilson; Lopatto, David; Elgin, Sarah C R

    2014-01-01

    There is widespread agreement that science, technology, engineering, and mathematics programs should provide undergraduates with research experience. Practical issues and limited resources, however, make this a challenge. We have developed a bioinformatics project that provides a course-based research experience for students at a diverse group of schools and offers the opportunity to tailor this experience to local curriculum and institution-specific student needs. We assessed both attitude and knowledge gains, looking for insights into how students respond given this wide range of curricular and institutional variables. While different approaches all appear to result in learning gains, we find that a significant investment of course time is required to enable students to show gains commensurate to a summer research experience. An alumni survey revealed that time spent on a research project is also a significant factor in the value former students assign to the experience one or more years later. We conclude: 1) implementation of a bioinformatics project within the biology curriculum provides a mechanism for successfully engaging large numbers of students in undergraduate research; 2) benefits to students are achievable at a wide variety of academic institutions; and 3) successful implementation of course-based research experiences requires significant investment of instructional time for students to gain full benefit.

  16. Enabling European Archaeological Research: The ARIADNE E-Infrastructure

    NARCIS (Netherlands)

    Hollander, H.S.; Aloia, Nicola; Binding, Ceri; Cuy, Sebastian; Doerr, Martin; Fanini, Bruno; Felicetti, Achille; Fihn, Johan; Gavrilis, Dimitris; Geser, Guntram; Meghini, Carlo; Niccolucci, Franco; Nurra, Federico; Papatheodorou, Christos; Richards, Julian; Ronzino, Paola; Scopigno, Roberto; Theodoridou, Maria; Theodoridou, Maria; Tudhope, Douglas; Vlachidis, Andreas; Wright, Holly

    2017-01-01

    Research e-infrastructures, digital archives and data services have become important pillars of scientific enterprise that in recent decades has become ever more collaborative, distributed and data-intensive. The archaeological research community has been an early adopter of digital tools for data

  17. Danish heathland manipulation experiment data in Model-Data-Fusion

    Science.gov (United States)

    Thum, Tea; Peylin, Philippe; Ibrom, Andreas; Van Der Linden, Leon; Beier, Claus; Bacour, Cédric; Santaren, Diego; Ciais, Philippe

    2013-04-01

    In ecosystem manipulation experiments (EMEs) the ecosystem is artificially exposed to different environmental conditions that aim to simulate circumstances in future climate. At Danish EME site Brandbjerg the responses of a heathland to drought, warming and increased atmospheric CO2 concentration are studied. The warming manipulation is realized by passive nighttime warming. The measurements include control plots as well as replicates for each three treatment separately and in combination. The Brandbjerg heathland ecosystem is dominated by heather and wavy hairgrass. These experiments provide excellent data for validation and development of ecosystem models. In this work we used a generic vegetation model ORCHIDEE with Model-Data-Fusion (MDF) approach. ORCHIDEE model is a process-based model that describes the exchanges of carbon, water and energy between the atmosphere and the vegetation. It can be run at different spatial scales from global to site level. Different vegetation types are described in ORCHIDEE as plant functional types. In MDF we are using observations from the site to optimize the model parameters. This enables us to assess the modelling errors and the performance of the model for different manipulation treatments. This insight will inform us whether the different processes are adequately modelled or if the model is missing some important processes. We used a genetic algorithm in the MDF. The data available from the site included measurements of aboveground biomass, heterotrophic soil respiration and total ecosystem respiration from years 2006-2008. The biomass was measured six times doing this period. The respiration measurements were done with manual chamber measurements. For the soil respiration we used results from an empirical model that has been developed for the site. This enabled us to have more data for the MDF. Before the MDF we performed a sensitivity analysis of the model parameters to different data streams. Fifteen most influential

  18. The EGS Data Collaboration Platform: Enabling Scientific Discovery

    Energy Technology Data Exchange (ETDEWEB)

    Weers, Jonathan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Johnston, Henry [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Huggins, Jay V [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-02-14

    Collaboration in the digital age has been stifled in recent years. Reasonable responses to legitimate security concerns have created a virtual landscape of silos and fortified castles incapable of sharing information efficiently. This trend is unfortunately opposed to the geothermal scientific community's migration toward larger, more collaborative projects. To facilitate efficient sharing of information between team members from multiple national labs, universities, and private organizations, the 'EGS Collab' team has developed a universally accessible, secure data collaboration platform and has fully integrated it with the U.S. Department of Energy's (DOE) Geothermal Data Repository (GDR) and the National Geothermal Data System (NGDS). This paper will explore some of the challenges of collaboration in the modern digital age, highlight strategies for active data management, and discuss the integration of the EGS Collab data management platform with the GDR to enable scientific discovery through the timely dissemination of information.

  19. A framework for smartphone-enabled, patient-generated health data analysis

    Directory of Open Access Journals (Sweden)

    Shreya S. Gollamudi

    2016-08-01

    Full Text Available Background: Digital medicine and smartphone-enabled health technologies provide a novel source of human health and human biology data. However, in part due to its intricacies, few methods have been established to analyze and interpret data in this domain. We previously conducted a six-month interventional trial examining the efficacy of a comprehensive smartphone-based health monitoring program for individuals with chronic disease. This included 38 individuals with hypertension who recorded 6,290 blood pressure readings over the trial. Methods: In the present study, we provide a hypothesis testing framework for unstructured time series data, typical of patient-generated mobile device data. We used a mixed model approach for unequally spaced repeated measures using autoregressive and generalized autoregressive models, and applied this to the blood pressure data generated in this trial. Results: We were able to detect, roughly, a 2 mmHg decrease in both systolic and diastolic blood pressure over the course of the trial despite considerable intra- and inter-individual variation. Furthermore, by supplementing this finding by using a sequential analysis approach, we observed this result over three months prior to the official study end—highlighting the effectiveness of leveraging the digital nature of this data source to form timely conclusions. Conclusions: Health data generated through the use of smartphones and other mobile devices allow individuals the opportunity to make informed health decisions, and provide researchers the opportunity to address innovative health and biology questions. The hypothesis testing framework we present can be applied in future studies utilizing digital medicine technology or implemented in the technology itself to support the quantified self.

  20. Dissemination or publication? Some consequences from smudging the boundaries between research data and research papers

    CERN Multimedia

    CERN. Geneva

    2007-01-01

    Project StORe’s repository middleware will enable researchers to move seamlessly between the research data environment and its outputs, passing directly from an electronic article to the data from which it was developed, or linking instantly to all the publications that have resulted from a particular research dataset. Originally conceived as a means of improving information discovery and data curation, it may also be claimed that this enhancement to the functionality of repositories has significantly broadened the meaning of the terms publish and publication. By publishing data that may not have been through a process of peer review, and by making data public before a scholarly article is approved and printed, are we introducing new risks? Is the scholarly article invalidated as a first publication of research results? The process is regulated, including a mechanism for access control and user authentication, and may not therefore be described as open access in the truest sense, but by making source or...

  1. Researching experiences

    DEFF Research Database (Denmark)

    Gjedde, Lisa; Ingemann, Bruno

    In the beginning was - not the word - but the experience. This phenomenological approach provides the basis for this book, which focuses on how a person-in-situation experiences and constructs meaning from a variety of cultural visual events. This book presents video-based processual methods......, dialogue, moods, values and narratives have been investigated qualitatively with more than sixty informants in a range of projects. The processual methodological insights are put into a theoretical perspective and also presented as pragmatic dilemmas. Researching Experiences is relevant not only...

  2. Distilling data – A flexible method for producing research-ready Electronic Health Records

    Directory of Open Access Journals (Sweden)

    Alex Hacker

    2017-04-01

    This methodology facilitates validation, comparison and combination of data sources. It enables us to present complex EHR data in a clear and flexible form, allowing researchers to analyse it with ease and confidence.

  3. Open Data in Global Environmental Research: The Belmont Forum’s Open Data Survey

    Science.gov (United States)

    Schmidt, Birgit; Gemeinholzer, Birgit; Treloar, Andrew

    2016-01-01

    This paper presents the findings of the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community. It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing. PMID:26771577

  4. Ames Culture Chamber System: Enabling Model Organism Research Aboard the international Space Station

    Science.gov (United States)

    Steele, Marianne

    2014-01-01

    Understanding the genetic, physiological, and behavioral effects of spaceflight on living organisms and elucidating the molecular mechanisms that underlie these effects are high priorities for NASA. Certain organisms, known as model organisms, are widely studied to help researchers better understand how all biological systems function. Small model organisms such as nem-atodes, slime mold, bacteria, green algae, yeast, and moss can be used to study the effects of micro- and reduced gravity at both the cellular and systems level over multiple generations. Many model organisms have sequenced genomes and published data sets on their transcriptomes and proteomes that enable scientific investigations of the molecular mechanisms underlying the adaptations of these organisms to space flight.

  5. Research Problems in Data Curation: Outcomes from the Data Curation Education in Research Centers Program

    Science.gov (United States)

    Palmer, C. L.; Mayernik, M. S.; Weber, N.; Baker, K. S.; Kelly, K.; Marlino, M. R.; Thompson, C. A.

    2013-12-01

    The need for data curation is being recognized in numerous institutional settings as national research funding agencies extend data archiving mandates to cover more types of research grants. Data curation, however, is not only a practical challenge. It presents many conceptual and theoretical challenges that must be investigated to design appropriate technical systems, social practices and institutions, policies, and services. This presentation reports on outcomes from an investigation of research problems in data curation conducted as part of the Data Curation Education in Research Centers (DCERC) program. DCERC is developing a new model for educating data professionals to contribute to scientific research. The program is organized around foundational courses and field experiences in research and data centers for both master's and doctoral students. The initiative is led by the Graduate School of Library and Information Science at the University of Illinois at Urbana-Champaign, in collaboration with the School of Information Sciences at the University of Tennessee, and library and data professionals at the National Center for Atmospheric Research (NCAR). At the doctoral level DCERC is educating future faculty and researchers in data curation and establishing a research agenda to advance the field. The doctoral seminar, Research Problems in Data Curation, was developed and taught in 2012 by the DCERC principal investigator and two doctoral fellows at the University of Illinois. It was designed to define the problem space of data curation, examine relevant concepts and theories related to both technical and social perspectives, and articulate research questions that are either unexplored or under theorized in the current literature. There was a particular emphasis on the Earth and environmental sciences, with guest speakers brought in from NCAR, National Snow and Ice Data Center (NSIDC), and Rensselaer Polytechnic Institute. Through the assignments, students

  6. Growing the Next Generation of Data Professionals at the National Center for Atmospheric Research

    Science.gov (United States)

    Hou, C. Y.; Worley, S. J.; Mayernik, M. S.

    2017-12-01

    As a federally funded research and development center by the National Science Foundation, being able to provide education in order to advance scientific research is a top priority at the National Center for Atmospheric Research (NCAR). Among the various education programs available at the NCAR, the Data Stewardship Engineering Team (DSET) is working with students and early career professionals from the Library and Information Science (LIS) discipline. This LIS group is passionate about learning more about how to optimize the value of research information and often have innovative ideas regarding how to meet current as well as emerging information needs. As a new data initiative that focuses on developing the next generation data services, the NCAR DSET and its Digital Asset Services Hub is a rich, practical environment that provides opportunities for attaining experience and growing dedicated data stewards for the atmospheric and geosciences. In this presentation, the authors will describe the NCAR DSET's new outreach program. We will highlight the process that we are using to engage students and early career information scientists/librarians. This process allows them to acquire practical, hands-on data management and curation skills specific to the Earth sciences by enabling them to participate in an interdisciplinary environment as well as contribute to collaborative activities. We will also discuss the factors that influenced the structuring of the program, and share the current results and lessons learned. Ultimately, we aim to strengthen the NCAR's educational contribution to and collaboration with the LIS discipline by: 1) documenting the experience and soliciting feedback regarding the ways in which we could further expand the mutual interests of Earth sciences and LIS education curricula, and 2) sharing the findings and impacts of the outreach program at NCAR with the education community.

  7. Development and successful operation of the enhanced-interlink system of experiment data and numerical simulation in LHD

    International Nuclear Information System (INIS)

    Emoto, M.; Suzuki, C.; Suzuki, Y.; Yokoyama, M.; Seki, R.; Ida, K.

    2014-10-01

    The enhanced-interlink system of experiment data and numerical simulation has been developed, and successfully operated routinely in the Large Helical Device (LHD). This system consists of analyzed diagnostic data, real-time coordinate mapping, and automatic data processing. It has enabled automated data handling/transferring between experiment and numerical simulation, to extensively perform experiment analyses. It can be considered as one of the prototypes for a seamless data-centric approach for integrating experiment data and numerical simulation/modellings in fusion experiments. Utilizing this system, experimental analyses by numerical simulations have extensively progressed. The authors believe this data-centric approach for integrating experiment data and numerical simulation/modellings will contribute to not only the LHD but to other plasma fusion projects including DEMO reactor in the future. (author)

  8. OpenTopography: Enabling Online Access to High-Resolution Lidar Topography Data and Processing Tools

    Science.gov (United States)

    Crosby, Christopher; Nandigam, Viswanath; Baru, Chaitan; Arrowsmith, J. Ramon

    2013-04-01

    resources. Datasets hosted by other organizations, as well as lidar-specific software, can be registered into the OpenTopography catalog, providing users a "one-stop shop" for such information. With several thousand active users, OpenTopography is an excellent example of a mature Spatial Data Infrastructure system that is enabling access to challenging data for research, education and outreach. Ongoing OpenTopography design and development work includes the archive and publication of datasets using digital object identifiers (DOIs); creation of a more flexible and scalable high-performance environment for processing of large datasets; expanded support for satellite and terrestrial lidar; and creation of a "pluggable" infrastructure for third-party programs and algorithms. OpenTopography has successfully created a facility for sharing lidar data. In the project's next phase, we are working to enable equally easy and successful sharing of services for processing and analysis of these data.

  9. A Semantically Enabled Metadata Repository for Solar Irradiance Data Products

    Science.gov (United States)

    Wilson, A.; Cox, M.; Lindholm, D. M.; Nadiadi, I.; Traver, T.

    2014-12-01

    The Laboratory for Atmospheric and Space Physics, LASP, has been conducting research in Atmospheric and Space science for over 60 years, and providing the associated data products to the public. LASP has a long history, in particular, of making space-based measurements of the solar irradiance, which serves as crucial input to several areas of scientific research, including solar-terrestrial interactions, atmospheric, and climate. LISIRD, the LASP Interactive Solar Irradiance Data Center, serves these datasets to the public, including solar spectral irradiance (SSI) and total solar irradiance (TSI) data. The LASP extended metadata repository, LEMR, is a database of information about the datasets served by LASP, such as parameters, uncertainties, temporal and spectral ranges, current version, alerts, etc. It serves as the definitive, single source of truth for that information. The database is populated with information garnered via web forms and automated processes. Dataset owners keep the information current and verified for datasets under their purview. This information can be pulled dynamically for many purposes. Web sites such as LISIRD can include this information in web page content as it is rendered, ensuring users get current, accurate information. It can also be pulled to create metadata records in various metadata formats, such as SPASE (for heliophysics) and ISO 19115. Once these records are be made available to the appropriate registries, our data will be discoverable by users coming in via those organizations. The database is implemented as a RDF triplestore, a collection of instances of subject-object-predicate data entities identifiable with a URI. This capability coupled with SPARQL over HTTP read access enables semantic queries over the repository contents. To create the repository we leveraged VIVO, an open source semantic web application, to manage and create new ontologies and populate repository content. A variety of ontologies were used in

  10. Research Administrator Salary: Association with Education, Experience, Credentials and Gender

    Science.gov (United States)

    Shambrook, Jennifer; Roberts, Thomas J.; Triscari, Robert

    2011-01-01

    The 2010 Research Administrators Stress Perception Survey (2010 RASPerS) collected data from 1,131 research administrators on salary, years experience, educational level, Certified Research Administrator (CRA) status, and gender. Using these data, comparisons were made to show how salary levels are associated with each of these variables. Using…

  11. Integrating authentic scientific research in a conservation course–based undergraduate research experience

    Science.gov (United States)

    Sorensen, Amanda E.; Corral, Lucia; Dauer, Jenny M.; Fontaine, Joseph J.

    2018-01-01

    Course-based undergraduate research experiences (CUREs) have been developed to overcome barriers including students in research. However, there are few examples of CUREs that take place in a conservation and natural resource context with students engaging in field research. Here, we highlight the development of a conservation-focused CURE integrated to a research program, research benefits, student self-assessment of learning, and perception of the CURE. With the additional data, researchers were able to refine species distribution models and facilitate management decisions. Most students reported gains in their scientific skills, felt they had engaged in meaningful, real-world research. In student reflections on how this experience helped clarify their professional intentions, many reported being more likely to enroll in graduate programs and seek employment related to science. Also interesting was all students reported being more likely to talk with friends, family, or the public about wildlife conservation issues after participating, indicating that courses like this can have effects beyond the classroom, empowering students to be advocates and translators of science. Field-based, conservation-focused CUREs can create meaningful conservation and natural resource experiences with authentic scientific teaching practices.

  12. CEOS Ocean Variables Enabling Research and Applications for Geo (COVERAGE)

    Science.gov (United States)

    Tsontos, V. M.; Vazquez, J.; Zlotnicki, V.

    2017-12-01

    The CEOS Ocean Variables Enabling Research and Applications for GEO (COVERAGE) initiative seeks to facilitate joint utilization of different satellite data streams on ocean physics, better integrated with biological and in situ observations, including near real-time data streams in support of oceanographic and decision support applications for societal benefit. COVERAGE aligns with programmatic objectives of CEOS (the Committee on Earth Observation Satellites) and the missions of GEO-MBON (Marine Biodiversity Observation Network) and GEO-Blue Planet, which are to advance and exploit synergies among the many observational programs devoted to ocean and coastal waters. COVERAGE is conceived of as 3 year pilot project involving international collaboration. It focuses on implementing technologies, including cloud based solutions, to provide a data rich, web-based platform for integrated ocean data delivery and access: multi-parameter observations, easily discoverable and usable, organized by disciplines, available in near real-time, collocated to a common grid and including climatologies. These will be complemented by a set of value-added data services available via the COVERAGE portal including an advanced Web-based visualization interface, subsetting/extraction, data collocation/matchup and other relevant on demand processing capabilities. COVERAGE development will be organized around priority use cases and applications identified by GEO and agency partners. The initial phase will be to develop co-located 25km products from the four Ocean Virtual Constellations (VCs), Sea Surface Temperature, Sea Level, Ocean Color, and Sea Surface Winds. This aims to stimulate work among the ocean VCs while developing products and system functionality based on community recommendations. Such products as anomalies from a time mean, would build on the theme of applications with a relevance to CEOS/GEO mission and vision. Here we provide an overview of the COVERAGE initiative with an

  13. Research data services in veterinary medicine libraries.

    Science.gov (United States)

    Kerby, Erin E

    2016-10-01

    The study investigated veterinary medicine librarians' experience with and perceptions of research data services. Many academic libraries have begun to offer research data services in response to researchers' increased need for data management support. To date, such services have typically been generic, rather than discipline-specific, to appeal to a wide variety of researchers. An online survey was deployed to identify trends regarding research data services in veterinary medicine libraries. Participants were identified from a list of contacts from the MLA Veterinary Medical Libraries Section. Although many respondents indicated that they have a professional interest in research data services, the majority of veterinary medicine librarians only rarely or occasionally provide data management support as part of their regular job responsibilities. There was little consensus as to whether research data services should be core to a library's mission despite their perceived importance to the advancement of veterinary research. Furthermore, most respondents stated that research data services are just as or somewhat less important than the other services that they provide and feel only slightly or somewhat prepared to offer such services. Lacking a standard definition of "research data" and a common understanding of precisely what research data services encompass, it is difficult for veterinary medicine librarians and libraries to define and understand their roles in research data services. Nonetheless, they appear to have an interest in learning more about and providing research data services.

  14. Managing and sharing research data a guide to good practice

    CERN Document Server

    Corti, Louise; Bishop, Libby; Woollard, Matthew

    2014-01-01

    Research funders in the UK, USA and across Europe are implementing data management and sharing policies to maximize openness of data, transparency and accountability of the research they support. Written by experts from the UK Data Archive with over 20 years experience, this book gives post-graduate students, researchers and research support staff the data management skills required in today’s changing research environment.

  15. TR32DB - Management of Research Data in a Collaborative, Interdisciplinary Research Project

    Science.gov (United States)

    Curdt, Constanze; Hoffmeister, Dirk; Waldhoff, Guido; Lang, Ulrich; Bareth, Georg

    2015-04-01

    The management of research data in a well-structured and documented manner is essential in the context of collaborative, interdisciplinary research environments (e.g. across various institutions). Consequently, set-up and use of a research data management (RDM) system like a data repository or project database is necessary. These systems should accompany and support scientists during the entire research life cycle (e.g. data collection, documentation, storage, archiving, sharing, publishing) and operate cross-disciplinary in interdisciplinary research projects. Challenges and problems of RDM are well-know. Consequently, the set-up of a user-friendly, well-documented, sustainable RDM system is essential, as well as user support and further assistance. In the framework of the Transregio Collaborative Research Centre 32 'Patterns in Soil-Vegetation-Atmosphere Systems: Monitoring, Modelling, and Data Assimilation' (CRC/TR32), funded by the German Research Foundation (DFG), a RDM system was self-designed and implemented. The CRC/TR32 project database (TR32DB, www.tr32db.de) is operating online since early 2008. The TR32DB handles all data, which are created by the involved project participants from several institutions (e.g. Universities of Cologne, Bonn, Aachen, and the Research Centre Jülich) and research fields (e.g. soil and plant sciences, hydrology, geography, geophysics, meteorology, remote sensing). Very heterogeneous research data are considered, which are resulting from field measurement campaigns, meteorological monitoring, remote sensing, laboratory studies and modelling approaches. Furthermore, outcomes like publications, conference contributions, PhD reports and corresponding images are regarded. The TR32DB project database is set-up in cooperation with the Regional Computing Centre of the University of Cologne (RRZK) and also located in this hardware environment. The TR32DB system architecture is composed of three main components: (i) a file-based data

  16. Open Access Data Sharing in Genomic Research

    Directory of Open Access Journals (Sweden)

    Stacey Pereira

    2014-08-01

    Full Text Available The current emphasis on broad sharing of human genomic data generated in research in order to maximize utility and public benefit is a significant legacy of the Human Genome Project. Concerns about privacy and discrimination have led to policy responses that restrict access to genomic data as the means for protecting research participants. Our research and experience show, however, that a considerable number of research participants agree to open access sharing of their genomic data when given the choice. General policies that limit access to all genomic data fail to respect the autonomy of these participants and, at the same time, unnecessarily limit the utility of the data. We advocate instead a more balanced approach that allows for individual choice and encourages informed decision making, while protecting against the misuse of genomic data through enhanced legislation.

  17. U.S. dental students' attitudes toward research and science: impact of research experience.

    Science.gov (United States)

    Holman, Shaina Devi; Wietecha, Mateusz S; Gullard, Angela; Peterson, Jon M B

    2014-03-01

    This study aimed to provide a first nationwide assessment of dental students' attitudes toward the importance of research and its integration into the dental curriculum. For this purpose, the American Association for Dental Research National Student Research Group developed an online survey that was distributed to 89 percent of U.S. dental students in May 2012. The survey consisted of twenty-one Likert-type items divided into three groups: importance of research in dentistry, barriers to research involvement, and exposure to research in the dental curriculum. There were 733 responses (3.9 percent response rate), including students in all stages of education representing fifty-eight out of sixty-one dental schools. Age and race/ethnic distributions corresponded with U.S. dental school enrollees. Results showed that 63 percent of respondents had conducted research before matriculation, and of the 34 percent that participated in research during dental school, only 27 percent were newcomers. Respondents strongly agreed that scientific research enabled their progress in dentistry. Inadequate time in the curriculum was an obstacle they perceived to research involvement during dental school. Respondents agreed that dental curricula emphasize evidence-based practices but may be inadequately teaching biostatistics and research methodologies. Students with research experience tended to have stronger positive opinions about the importance of research in dental education. Efforts to foster research in schools have been well received by students, but several issues remain for enriching dental education through greater involvement of students in research.

  18. Control and data acquisition system for versatile experiment spherical torus at SNU

    Energy Technology Data Exchange (ETDEWEB)

    An, YoungHwa [Department of Nuclear Engineering, Seoul National University, Seoul 151-742 (Korea, Republic of); Chung, Kyoung-Jae, E-mail: jkjlsh1@snu.ac.kr [Department of Nuclear Engineering, Seoul National University, Seoul 151-742 (Korea, Republic of); Na, DongHyeon; Hwang, Y.S. [Department of Nuclear Engineering, Seoul National University, Seoul 151-742 (Korea, Republic of)

    2013-10-15

    A control and data acquisition system for VEST (Versatile Experiment Spherical Torus) at Seoul National University (SNU) has been developed to enable remote operation from a central control room. The control and data acquisition system consists of three subsystems; a main control and data acquisition system that triggers each device at the preprogrammed timing and collects various diagnostic signals during discharges, a monitoring system that watches and logs the device status continuously, and a data storage and distribution system that stores collected data and provides data access layer via Ethernet. The system is designed to be cost-effective, extensible and easy to develop by using well-established standard technologies and solutions. Combining broad accessibility with modern information technology, alarm signal can be sent immediately to the registered cell phones when the abnormal status of devices is found, and the web data distribution system enables data access from almost everywhere using smart phones or tablet computers. Since December 2011, VEST is operational and the control and data acquisition system has been successfully used for remote operation of VEST.

  19. Control and data acquisition system for versatile experiment spherical torus at SNU

    International Nuclear Information System (INIS)

    An, YoungHwa; Chung, Kyoung-Jae; Na, DongHyeon; Hwang, Y.S.

    2013-01-01

    A control and data acquisition system for VEST (Versatile Experiment Spherical Torus) at Seoul National University (SNU) has been developed to enable remote operation from a central control room. The control and data acquisition system consists of three subsystems; a main control and data acquisition system that triggers each device at the preprogrammed timing and collects various diagnostic signals during discharges, a monitoring system that watches and logs the device status continuously, and a data storage and distribution system that stores collected data and provides data access layer via Ethernet. The system is designed to be cost-effective, extensible and easy to develop by using well-established standard technologies and solutions. Combining broad accessibility with modern information technology, alarm signal can be sent immediately to the registered cell phones when the abnormal status of devices is found, and the web data distribution system enables data access from almost everywhere using smart phones or tablet computers. Since December 2011, VEST is operational and the control and data acquisition system has been successfully used for remote operation of VEST

  20. Toolbox for Research, or how to facilitate a central data management in small-scale research projects.

    Science.gov (United States)

    Bialke, Martin; Rau, Henriette; Thamm, Oliver C; Schuldt, Ronny; Penndorf, Peter; Blumentritt, Arne; Gött, Robert; Piegsa, Jens; Bahls, Thomas; Hoffmann, Wolfgang

    2018-01-25

    In most research projects budget, staff and IT infrastructures are limiting resources. Especially for small-scale registries and cohort studies professional IT support and commercial electronic data capture systems are too expensive. Consequently, these projects use simple local approaches (e.g. Excel) for data capture instead of a central data management including web-based data capture and proper research databases. This leads to manual processes to merge, analyze and, if possible, pseudonymize research data of different study sites. To support multi-site data capture, storage and analyses in small-scall research projects, corresponding requirements were analyzed within the MOSAIC project. Based on the identified requirements, the Toolbox for Research was developed as a flexible software solution for various research scenarios. Additionally, the Toolbox facilitates data integration of research data as well as metadata by performing necessary procedures automatically. Also, Toolbox modules allow the integration of device data. Moreover, separation of personally identifiable information and medical data by using only pseudonyms for storing medical data ensures the compliance to data protection regulations. This pseudonymized data can then be exported in SPSS format in order to enable scientists to prepare reports and analyses. The Toolbox for Research was successfully piloted in the German Burn Registry in 2016 facilitating the documentation of 4350 burn cases at 54 study sites. The Toolbox for Research can be downloaded free of charge from the project website and automatically installed due to the use of Docker technology.

  1. Students' Perceptions of an Applied Research Experience in an Undergraduate Exercise Science Course.

    Science.gov (United States)

    Pearson, Regis C; Crandall, K Jason; Dispennette, Kathryn; Maples, Jill M

    2017-01-01

    Applied research experiences can provide numerous benefits to undergraduate students, however few studies have assessed the perceptions of Exercise Science (EXS) students to an applied research experience. The purpose of this study was two-fold: 1) to describe the rationale and implementation of an applied research experience into an EXS curriculum and 2) to evaluate EXS undergraduate students' perceptions of an applied research experience. An EXS measurement course was chosen for implementation of an applied research experience. The applied research experience required groups of students to design, implement, and evaluate a student-led research project. Fourteen questions were constructed, tailored to EXS undergraduate students, to assess students' perceptions of the experience. Qualitative analysis was used for all applicable data, with repeated trends noted; quantitative data were collapsed to determine frequencies. There was an overall positive student perception of the experience and 85.7% of students agreed an applied research experience should be continued. 84.7% of students perceived the experience as educationally enriching, while 92.8% reported the experience was academically challenging. This experience allowed students to develop comprehensive solutions to problems that arose throughout the semester; while facilitating communication, collaboration, and problem solving. Students believed research experiences were beneficial, but could be time consuming when paired with other responsibilities. Results suggest an applied research experience has the potential to help further the development of EXS undergraduate students. Understanding student perceptions of an applied research experience may prove useful to faculty interested in engaging students in the research process.

  2. Empowering Geoscience with Improved Data Assimilation Using the Data Assimilation Research Testbed "Manhattan" Release.

    Science.gov (United States)

    Raeder, K.; Hoar, T. J.; Anderson, J. L.; Collins, N.; Hendricks, J.; Kershaw, H.; Ha, S.; Snyder, C.; Skamarock, W. C.; Mizzi, A. P.; Liu, H.; Liu, J.; Pedatella, N. M.; Karspeck, A. R.; Karol, S. I.; Bitz, C. M.; Zhang, Y.

    2017-12-01

    The capabilities of the Data Assimilation Research Testbed (DART) at NCAR have been significantly expanded with the recent "Manhattan" release. DART is an ensemble Kalman filter based suite of tools, which enables researchers to use data assimilation (DA) without first becoming DA experts. Highlights: significant improvement in efficient ensemble DA for very large models on thousands of processors, direct read and write of model state files in parallel, more control of the DA output for finer-grained analysis, new model interfaces which are useful to a variety of geophysical researchers, new observation forward operators and the ability to use precomputed forward operators from the forecast model. The new model interfaces and example applications include the following: MPAS-A; Model for Prediction Across Scales - Atmosphere is a global, nonhydrostatic, variable-resolution mesh atmospheric model, which facilitates multi-scale analysis and forecasting. The absence of distinct subdomains eliminates problems associated with subdomain boundaries. It demonstrates the ability to consistently produce higher-quality analyses than coarse, uniform meshes do. WRF-Chem; Weather Research and Forecasting + (MOZART) Chemistry model assimilates observations from FRAPPÉ (Front Range Air Pollution and Photochemistry Experiment). WACCM-X; Whole Atmosphere Community Climate Model with thermosphere and ionosphere eXtension assimilates observations of electron density to investigate sudden stratospheric warming. CESM (weakly) coupled assimilation; NCAR's Community Earth System Model is used for assimilation of atmospheric and oceanic observations into their respective components using coupled atmosphere+land+ocean+sea+ice forecasts. CESM2.0; Assimilation in the atmospheric component (CAM, WACCM) of the newly released version is supported. This version contains new and extensively updated components and software environment. CICE; Los Alamos sea ice model (in CESM) is used to assimilate

  3. HydroShare for iUTAH: Collaborative Publication, Interoperability, and Reuse of Hydrologic Data and Models for a Large, Interdisciplinary Water Research Project

    Science.gov (United States)

    Horsburgh, J. S.; Jones, A. S.

    2016-12-01

    Data and models used within the hydrologic science community are diverse. New research data and model repositories have succeeded in making data and models more accessible, but have been, in most cases, limited to particular types or classes of data or models and also lack the type of collaborative, and iterative functionality needed to enable shared data collection and modeling workflows. File sharing systems currently used within many scientific communities for private sharing of preliminary and intermediate data and modeling products do not support collaborative data capture, description, visualization, and annotation. More recently, hydrologic datasets and models have been cast as "social objects" that can be published, collaborated around, annotated, discovered, and accessed. Yet it can be difficult using existing software tools to achieve the kind of collaborative workflows and data/model reuse that many envision. HydroShare is a new, web-based system for sharing hydrologic data and models with specific functionality aimed at making collaboration easier and achieving new levels of interactive functionality and interoperability. Within HydroShare, we have developed new functionality for creating datasets, describing them with metadata, and sharing them with collaborators. HydroShare is enabled by a generic data model and content packaging scheme that supports describing and sharing diverse hydrologic datasets and models. Interoperability among the diverse types of data and models used by hydrologic scientists is achieved through the use of consistent storage, management, sharing, publication, and annotation within HydroShare. In this presentation, we highlight and demonstrate how the flexibility of HydroShare's data model and packaging scheme, HydroShare's access control and sharing functionality, and versioning and publication capabilities have enabled the sharing and publication of research datasets for a large, interdisciplinary water research project

  4. In-Pile Experiment of a New Hafnium Aluminide Composite Material to Enable Fast Neutron Testing in the Advanced Test Reactor

    Energy Technology Data Exchange (ETDEWEB)

    Donna Post Guillen; Douglas L. Porter; James R. Parry; Heng Ban

    2010-06-01

    A new hafnium aluminide composite material is being developed as a key component in a Boosted Fast Flux Loop (BFFL) system designed to provide fast neutron flux test capability in the Advanced Test Reactor. An absorber block comprised of hafnium aluminide (Al3Hf) particles (~23% by volume) dispersed in an aluminum matrix can absorb thermal neutrons and transfer heat from the experiment to pressurized water cooling channels. However, the thermophysical properties, such as thermal conductivity, of this material and the effect of irradiation are not known. This paper describes the design of an in-pile experiment to obtain such data to enable design and optimization of the BFFL neutron filter.

  5. Integrating and accessing medical data resources within the ViroLab Virtual Laboratory

    NARCIS (Netherlands)

    Assel, M.; Nowakowski, P.; Bubak, M.

    2008-01-01

    This paper presents the data access solutions which have been developed in the ViroLab Virtual Laboratory infrastructure to enable medical researchers and practitioners to conduct experiments in the area of HIV treatment. Such experiments require access to a number of geographically distributed data

  6. The Indigenous Experience of Work in a Health Research Organisation: Are There Wider Inferences?

    Directory of Open Access Journals (Sweden)

    Sharon Chirgwin

    2017-08-01

    Full Text Available The purpose of this study was to identify the factors that positively and negatively impacted on the employment experiences and trajectories of Indigenous Australians who are currently or were formerly employed by a research organisation in both remote and urban settings. The study design was an embedded mixed-methods approach. The first phase quantified staff uptake, continued employment, and attrition. Then interviews were conducted with 42 former and 51 current Indigenous staff members to obtain qualitative data. The results showed that the quality of supervision, the work flexibility to enable employees to respond to family and community priorities, and training and other forms of career support were all identified as important factors in the workplace. The most common reasons for leaving were that research projects ended, or to pursue a career change or further study. The authors use the findings to make recommendations pertinent to policy formation for both government and organisations seeking to attract and nurture Indigenous staff.

  7. IT Enabled Agility in Organizational Ambidexterity

    OpenAIRE

    Röder, Nina; Schermann, Michael; Krcmar, Helmut

    2015-01-01

    The aim of ambidextrous organizations is to balance exploratory and exploitative learning concepts. They innovate through experiments and research, and capture the value of innovations through refinement and continuous improvement. In this paper, we study the relationship of organizational ambidexterity and IT enabled agility. Based on a case study with a German car manufacturer we find that (1) entrepreneurial agility impedes exploitative concepts, (2) adaptive agility impedes exploratory co...

  8. Finding, Browsing and Getting Data Easily Using SPDF Web Services

    Science.gov (United States)

    Candey, R.; Chimiak, R.; Harris, B.; Johnson, R.; Kovalick, T.; Lal, N.; Leckner, H.; Liu, M.; McGuire, R.; Papitashvili, N.; hide

    2010-01-01

    The NASA GSFC Space Physics Data Facility (5PDF) provides heliophysics science-enabling information services for enhancing scientific research and enabling integration of these services into the Heliophysics Data Environment paradigm, via standards-based approach (SOAP) and Representational State Transfer (REST) web services in addition to web browser, FTP, and OPeNDAP interfaces. We describe these interfaces and the philosophies behind these web services, and show how to call them from various languages, such as IDL and Perl. We are working towards a "one simple line to call" philosophy extolled in the recent VxO discussions. Combining data from many instruments and missions enables broad research analysis and correlation and coordination with other experiments and missions.

  9. Data assimilation and model evaluation experiment datasets

    Science.gov (United States)

    Lai, Chung-Cheng A.; Qian, Wen; Glenn, Scott M.

    1994-01-01

    The Institute for Naval Oceanography, in cooperation with Naval Research Laboratories and universities, executed the Data Assimilation and Model Evaluation Experiment (DAMEE) for the Gulf Stream region during fiscal years 1991-1993. Enormous effort has gone into the preparation of several high-quality and consistent datasets for model initialization and verification. This paper describes the preparation process, the temporal and spatial scopes, the contents, the structure, etc., of these datasets. The goal of DAMEE and the need of data for the four phases of experiment are briefly stated. The preparation of DAMEE datasets consisted of a series of processes: (1) collection of observational data; (2) analysis and interpretation; (3) interpolation using the Optimum Thermal Interpolation System package; (4) quality control and re-analysis; and (5) data archiving and software documentation. The data products from these processes included a time series of 3D fields of temperature and salinity, 2D fields of surface dynamic height and mixed-layer depth, analysis of the Gulf Stream and rings system, and bathythermograph profiles. To date, these are the most detailed and high-quality data for mesoscale ocean modeling, data assimilation, and forecasting research. Feedback from ocean modeling groups who tested this data was incorporated into its refinement. Suggestions for DAMEE data usages include (1) ocean modeling and data assimilation studies, (2) diagnosis and theoretical studies, and (3) comparisons with locally detailed observations.

  10. Research Data Management Training for Geographers: First Impressions

    Directory of Open Access Journals (Sweden)

    Kerstin Helbig

    2016-03-01

    Full Text Available Sharing and secondary analysis of data have become increasingly important for research. Especially in geography, the collection of digital data has grown due to technological changes. Responsible handling and proper documentation of research data have therefore become essential for funders, publishers and higher education institutions. To achieve this goal, universities offer support and training in research data management. This article presents the experiences of a pilot workshop in research data management, especially for geographers. A discipline-specific approach to research data management training is recommended. The focus of this approach increases researchers’ interest and allows for more specific guidance. The instructors identified problems and challenges of research data management for geographers. In regards to training, the communication of benefits and reaching the target groups seem to be the biggest challenges. Consequently, better incentive structures as well as communication channels have to be established.

  11. The X-Factor of Cultivating Successful Entrepreneurial Technology-Enabled Start-Ups

    Directory of Open Access Journals (Sweden)

    Elsje Scott

    2016-10-01

    Full Text Available In the fast changing global economic landscape, the cultivation of sustainable entrepreneurial ventures is seen as a vital mechanism that will enable businesses to introduce new innovative products to the market faster and more effectively than their competitors. This research paper investigated phenomena that may play a significant role when entrepreneurs implement creative ideas resulting in successful technology enabled start-ups within the South African market place. Constant and significant changes in technology provide several challenges for entrepreneurship. Various themes such as innovation, work experience, idea generation, education and partnership formation have been explored to assess their impact on entrepreneurship. Reflection and a design thinking approach underpinned a rigorous analysis process to distill themes from the data gathered through semi structured interviews. From the findings it was evident that the primary success influencers include the formation of partnership, iterative cycles, and certain types of education. The secondary influencers included the origination of an idea, the use of innovation. and organizational culture as well as work experience. This research illustrates how Informing Science as a transdisicpline can provide a philosophical underpinning to communicate and synthesise ideas from constituent disciplines in an attempt to create a more cohesive whole. This diverse environment, comprising people, technology, and business, requires blending different elements from across diverse fields to yield better science. With this backdrop, this preliminary study provides an important foundation for further research in the context of a developing country where entrepreneurial ventures may have a socio-economical impact. The themes that emerged through this study could provide avenues for further research.

  12. Working Towards New Transformative Geoscience Analytics Enabled by Petascale Computing

    Science.gov (United States)

    Woodcock, R.; Wyborn, L.

    2012-04-01

    Currently the top 10 supercomputers in the world are petascale and already exascale computers are being planned. Cloud computing facilities are becoming mainstream either as private or commercial investments. These computational developments will provide abundant opportunities for the earth science community to tackle the data deluge which has resulted from new instrumentation enabling data to be gathered at a greater rate and at higher resolution. Combined, the new computational environments should enable the earth sciences to be transformed. However, experience in Australia and elsewhere has shown that it is not easy to scale existing earth science methods, software and analytics to take advantage of the increased computational capacity that is now available. It is not simply a matter of 'transferring' current work practices to the new facilities: they have to be extensively 'transformed'. In particular new Geoscientific methods will need to be developed using advanced data mining, assimilation, machine learning and integration algorithms. Software will have to be capable of operating in highly parallelised environments, and will also need to be able to scale as the compute systems grow. Data access will have to improve and the earth science community needs to move from the file discovery, display and then locally download paradigm to self describing data cubes and data arrays that are available as online resources from either major data repositories or in the cloud. In the new transformed world, rather than analysing satellite data scene by scene, sensor agnostic data cubes of calibrated earth observation data will enable researchers to move across data from multiple sensors at varying spatial data resolutions. In using geophysics to characterise basement and cover, rather than analysing individual gridded airborne geophysical data sets, and then combining the results, petascale computing will enable analysis of multiple data types, collected at varying

  13. Understanding the burnout experience: recent research and its implications for psychiatry

    Science.gov (United States)

    Maslach, Christina; Leiter, Michael P.

    2016-01-01

    The experience of burnout has been the focus of much research during the past few decades. Measures have been developed, as have various theoretical models, and research studies from many countries have contributed to a better understanding of the causes and consequences of this occupationally‐specific dysphoria. The majority of this work has focused on human service occupations, and particularly health care. Research on the burnout experience for psychiatrists mirrors much of the broader literature, in terms of both sources and outcomes of burnout. But it has also identified some of the unique stressors that mental health professionals face when they are dealing with especially difficult or violent clients. Current issues of particular relevance for psychiatry include the links between burnout and mental illness, the attempts to redefine burnout as simply exhaustion, and the relative dearth of evaluative research on potential interventions to treat and/or prevent burnout. Given that the treatment goal for burnout is usually to enable people to return to their job, and to be successful in their work, psychiatry could make an important contribution by identifying the treatment strategies that would be most effective in achieving that goal. PMID:27265691

  14. A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogeneous clinical data

    Science.gov (United States)

    Sittig, Dean F.; Hazlehurst, Brian L.; Brown, Jeffrey; Murphy, Shawn; Rosenman, Marc; Tarczy-Hornoch, Peter; Wilcox, Adam B.

    2012-01-01

    Comparative Effectiveness Research (CER) has the potential to transform the current healthcare delivery system by identifying the most effective medical and surgical treatments, diagnostic tests, disease prevention methods and ways to deliver care for specific clinical conditions. To be successful, such research requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse representations of the relevant clinical events. In an effort to address these diverse demands, there have been multiple new designs and implementations of informatics platforms that provide access to electronic clinical data and the governance infrastructure required for inter-institutional CER. The goal of this manuscript is to help investigators understand why these informatics platforms are required and to compare and contrast six, large-scale, recently funded, CER-focused informatics platform development efforts. We utilized an 8-dimension, socio-technical model of health information technology use to help guide our work. We identified six generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination. We expect that over the next several years these projects will provide answers to many important, and heretofore unanswerable, clinical research questions. PMID:22692259

  15. A survey of informatics platforms that enable distributed comparative effectiveness research using multi-institutional heterogenous clinical data.

    Science.gov (United States)

    Sittig, Dean F; Hazlehurst, Brian L; Brown, Jeffrey; Murphy, Shawn; Rosenman, Marc; Tarczy-Hornoch, Peter; Wilcox, Adam B

    2012-07-01

    Comparative effectiveness research (CER) has the potential to transform the current health care delivery system by identifying the most effective medical and surgical treatments, diagnostic tests, disease prevention methods, and ways to deliver care for specific clinical conditions. To be successful, such research requires the identification, capture, aggregation, integration, and analysis of disparate data sources held by different institutions with diverse representations of the relevant clinical events. In an effort to address these diverse demands, there have been multiple new designs and implementations of informatics platforms that provide access to electronic clinical data and the governance infrastructure required for interinstitutional CER. The goal of this manuscript is to help investigators understand why these informatics platforms are required and to compare and contrast 6 large-scale, recently funded, CER-focused informatics platform development efforts. We utilized an 8-dimension, sociotechnical model of health information technology to help guide our work. We identified 6 generic steps that are necessary in any distributed, multi-institutional CER project: data identification, extraction, modeling, aggregation, analysis, and dissemination. We expect that over the next several years these projects will provide answers to many important, and heretofore unanswerable, clinical research questions.

  16. Pathology as the enabler of human research.

    Science.gov (United States)

    Crawford, James M; Tykocinski, Mark L

    2005-09-01

    Academic Pathology is a key player in human molecular science and in the powerful initiatives of the National Institutes of Health. Pathologists generate data crucial to virtually every molecular study of human tissue, and have the necessary skills and authority to oversee processing of human tissues for research analysis. We advocate that Academic Pathology is optimally positioned to drive the molecular revolution in study of human disease, through human tissue collection, analysis, and databasing. This can be achieved through playing a major role in human tissue procurement and management; establishing high-quality 'Pathology Resource Laboratories'; providing the scientific expertise for pathology data sharing; and recruiting and training physician scientists. Pathology should position itself to be the local institutional driver of technology implementation and development, by operating the resource laboratories, providing the expertise for technical and conceptual design of research projects, maintaining the databases that link molecular and morphological information on human tissues with the requisite clinical databases, providing education and mentorship of technology users, and nurturing new research through the development of preliminary data. We also consider that outstanding pathology journals are available for the publication of research emanating from such studies, to the benefit of the pathology profession as an academic enterprise. It is our earnest hope that Academic Pathology can play a leading role in the remarkable advances to be made as the 21st century unfolds.

  17. Improving the User Experience of Finding and Visualizing Oceanographic Data

    Science.gov (United States)

    Rauch, S.; Allison, M. D.; Groman, R. C.; Chandler, C. L.; Galvarino, C.; Gegg, S. R.; Kinkade, D.; Shepherd, A.; Wiebe, P. H.; Glover, D. M.

    2013-12-01

    Searching for and locating data of interest can be a challenge to researchers as increasing volumes of data are made available online through various data centers, repositories, and archives. The Biological and Chemical Oceanography Data Management Office (BCO-DMO) is keenly aware of this challenge and, as a result, has implemented features and technologies aimed at improving data discovery and enhancing the user experience. BCO-DMO was created in 2006 to manage and publish data from research projects funded by the Division of Ocean Sciences (OCE) Biological and Chemical Oceanography Sections and the Division of Polar Programs (PLR) Antarctic Sciences Organisms and Ecosystems Program (ANT) of the US National Science Foundation (NSF). The BCO-DMO text-based and geospatial-based data access systems provide users with tools to search, filter, and visualize data in order to efficiently find data of interest. The geospatial interface, developed using a suite of open-source software (including MapServer [1], OpenLayers [2], ExtJS [3], and MySQL [4]), allows users to search and filter/subset metadata based on program, project, or deployment, or by using a simple word search. The map responds based on user selections, presents options that allow the user to choose specific data parameters (e.g., a species or an individual drifter), and presents further options for visualizing those data on the map or in "quick-view" plots. The data managed and made available by BCO-DMO are very heterogeneous in nature, from in-situ biogeochemical, ecological, and physical data, to controlled laboratory experiments. Due to the heterogeneity of the data types, a 'one size fits all' approach to visualization cannot be applied. Datasets are visualized in a way that will best allow users to assess fitness for purpose. An advanced geospatial interface, which contains a semantically-enabled faceted search [5], is also available. These search facets are highly interactive and responsive, allowing

  18. Enabling Field Experiences in Introductory Geoscience Classes through the Use of Immersive Virtual Reality

    Science.gov (United States)

    Moysey, S. M.; Smith, E.; Sellers, V.; Wyant, P.; Boyer, D. M.; Mobley, C.; Brame, S.

    2015-12-01

    Although field experiences are an important aspect of geoscience education, the opportunity to provide physical world experiences to large groups of introductory students is often limited by access, logistical, and financial constraints. Our project (NSF IUSE 1504619) is investigating the use of immersive virtual reality (VR) technologies as a surrogate for real field experiences in introductory geosciences classes. We are developing a toolbox that leverages innovations in the field of VR, including the Oculus Rift and Google Cardboard, to enable every student in an introductory geology classroom the opportunity to have a first-person virtual field experience in the Grand Canyon. We have opted to structure our VR experience as an interactive game where students must explore the Canyon to accomplish a series of tasks designed to emphasize key aspects of geoscience learning. So far we have produced two demo products for the virtual field trip. The first is a standalone "Rock Box" app developed for the iPhone, which allows students to select different rock samples, examine them in 3D, and obtain basic information about the properties of each sample. The app can act as a supplement to the traditional rock box used in physical geology labs. The second product is a fully functioning VR environment for the Grand Canyon developed using satellite-based topographic and imagery data to retain real geologic features within the experience. Players can freely navigate to explore anywhere they desire within the Canyon, but are guided to points of interest where they are able to complete exercises that will be aligned with specific learning goals. To this point we have integrated elements of the "Rock Box" app within the VR environment, allowing players to examine 3D details of rock samples they encounter within the Grand Canyon. We plan to provide demos of both products and obtain user feedback during our presentation.

  19. Blue space geographies: Enabling health in place.

    Science.gov (United States)

    Foley, Ronan; Kistemann, Thomas

    2015-09-01

    Drawing from research on therapeutic landscapes and relationships between environment, health and wellbeing, we propose the idea of 'healthy blue space' as an important new development Complementing research on healthy green space, blue space is defined as; 'health-enabling places and spaces, where water is at the centre of a range of environments with identifiable potential for the promotion of human wellbeing'. Using theoretical ideas from emotional and relational geographies and critical understandings of salutogenesis, the value of blue space to health and wellbeing is recognised and evaluated. Six individual papers from five different countries consider how health can be enabled in mixed blue space settings. Four sub-themes; embodiment, inter-subjectivity, activity and meaning, document multiple experiences within a range of healthy blue spaces. Finally, we suggest a considerable research agenda - theoretical, methodological and applied - for future work within different forms of blue space. All are suggested as having public health policy relevance in social and public space. Copyright © 2015 Elsevier Ltd. All rights reserved.

  20. Enabling Analytics on Sensitive Medical Data with Secure Multi-Party Computation.

    Science.gov (United States)

    Veeningen, Meilof; Chatterjea, Supriyo; Horváth, Anna Zsófia; Spindler, Gerald; Boersma, Eric; van der Spek, Peter; van der Galiën, Onno; Gutteling, Job; Kraaij, Wessel; Veugen, Thijs

    2018-01-01

    While there is a clear need to apply data analytics in the healthcare sector, this is often difficult because it requires combining sensitive data from multiple data sources. In this paper, we show how the cryptographic technique of secure multi-party computation can enable such data analytics by performing analytics without the need to share the underlying data. We discuss the issue of compliance to European privacy legislation; report on three pilots bringing these techniques closer to practice; and discuss the main challenges ahead to make fully privacy-preserving data analytics in the medical sector commonplace.

  1. Data processing system for neutron experiments

    Energy Technology Data Exchange (ETDEWEB)

    Emoto, T; Yamamuro, N [Tokyo Inst. of Tech. (Japan). Research Lab. of Nuclear Reactor

    1979-03-01

    A data processing system for neutron experiments has been equipped at the Pelletron Laboratory of the Research Laboratory for Nuclear Reactors. The system comprises a Hewlett Packard 21 MX computer and a CAMAC standard. It can control two ADCs and some CAMAC modules. CAMAC control programs as well as data acquisition programs with high-level language can be readily developed. Terminals are well designed for man-machine interactions and program developments. To demonstrate the usefulness of the system, it was applied for the on-line data processing of neutron spectrum measurement.

  2. Enabling search services on outsourced private spatial data

    KAUST Repository

    Yiu, Man Lung

    2009-10-30

    Cloud computing services enable organizations and individuals to outsource the management of their data to a service provider in order to save on hardware investments and reduce maintenance costs. Only authorized users are allowed to access the data. Nobody else, including the service provider, should be able to view the data. For instance, a real-estate company that owns a large database of properties wants to allow its paying customers to query for houses according to location. On the other hand, the untrusted service provider should not be able to learn the property locations and, e. g., selling the information to a competitor. To tackle the problem, we propose to transform the location datasets before uploading them to the service provider. The paper develops a spatial transformation that re-distributes the locations in space, and it also proposes a cryptographic-based transformation. The data owner selects the transformation key and shares it with authorized users. Without the key, it is infeasible to reconstruct the original data points from the transformed points. The proposed transformations present distinct trade-offs between query efficiency and data confidentiality. In addition, we describe attack models for studying the security properties of the transformations. Empirical studies demonstrate that the proposed methods are efficient and applicable in practice. © 2009 Springer-Verlag.

  3. Hearing the voices of service user researchers in collaborative qualitative data analysis: the case for multiple coding.

    Science.gov (United States)

    Sweeney, Angela; Greenwood, Kathryn E; Williams, Sally; Wykes, Til; Rose, Diana S

    2013-12-01

    Health research is frequently conducted in multi-disciplinary teams, with these teams increasingly including service user researchers. Whilst it is common for service user researchers to be involved in data collection--most typically interviewing other service users--it is less common for service user researchers to be involved in data analysis and interpretation. This means that a unique and significant perspective on the data is absent. This study aims to use an empirical report of a study on Cognitive Behavioural Therapy for psychosis (CBTp) to demonstrate the value of multiple coding in enabling service users voices to be heard in team-based qualitative data analysis. The CBTp study employed multiple coding to analyse service users' discussions of CBT for psychosis (CBTp) from the perspectives of a service user researcher, clinical researcher and psychology assistant. Multiple coding was selected to enable multiple perspectives to analyse and interpret data, to understand and explore differences and to build multi-disciplinary consensus. Multiple coding enabled the team to understand where our views were commensurate and incommensurate and to discuss and debate differences. Through the process of multiple coding, we were able to build strong consensus about the data from multiple perspectives, including that of the service user researcher. Multiple coding is an important method for understanding and exploring multiple perspectives on data and building team consensus. This can be contrasted with inter-rater reliability which is only appropriate in limited circumstances. We conclude that multiple coding is an appropriate and important means of hearing service users' voices in qualitative data analysis. © 2012 John Wiley & Sons Ltd.

  4. Enabling healthy living: Experiences of people with severe mental illness in psychiatric outpatient services.

    Science.gov (United States)

    Blomqvist, Marjut; Sandgren, Anna; Carlsson, Ing-Marie; Jormfeldt, Henrika

    2018-02-01

    It is well known that people with severe mental illness have a reduced life expectancy and a greater risk of being affected by preventable physical illnesses such as metabolic syndrome, cardiovascular disease and type 2 diabetes. There are still, however, only a few published studies focusing on what enables healthy living for this group. This study thus aimed to describe what enables healthy living among people with severe mental illness in psychiatric outpatient services. The data were collected in qualitative interviews (n = 16) and content analysis was used to analyze the data. The interviews resulted in an overall theme "Being regarded as a whole human being by self and others", which showed the multidimensional nature of health and the issues that enable healthy living among people with severe mental illness. Three categories emerged: (i) everyday structure (ii), motivating life events and (iii) support from significant others. The results indicate that a person with severe mental illness needs to be encountered as a whole person if healthy living is to be enabled. Attaining healthy living requires collaboration between the providers of care, help and support. Health care organizations need to work together to develop and provide interventions to enable healthy living and to reduce poor physical health among people with severe mental illness. © 2017 Australian College of Mental Health Nurses Inc.

  5. Enabling and Encouraging Transparency in Earth Science Data for Decision Making

    Science.gov (United States)

    Abbott, S. B.

    2010-12-01

    Our ability to understand, respond, and make decisions about our changing planet hinges on timely scientific information and situational awareness. Information and understanding will continue to be the foundations of decision support in the face of uncertainty. Over the last 40 years, investments in Earth observations have brought remarkable achievements in weather prediction, disaster prediction and response, land management, and our broad base of Earth science knowledge. The only way to know what is happening to our planet and to manage our resources wisely is to measure it, This means tracking changes decade after decade and reanalyzing the record in light of new insights, technologies, and methodologies. In order to understand and respond to climate change and other global challenges, there is a need for a high degree of transparency in the publication, management, traceability, and citability of science data, and particularly for Earth science data. In addition, it is becoming increasingly important that free, open, and authoritative sources of quality data are available for peer review. One important focus is on applications and opportunities for enhancing data exchange standards for use with Earth science data. By increasing the transparency of scientific work and providing incentives for researchers and institutions to openly share data, we will more effectively leverage the scientific capacity of our Nation to address climate change and to meet future challenges. It is an enormous challenge to collect, organize, and communicate the vast stores of data maintained across the government. The Administration is committed to moving past these barriers in providing the American public with unprecedented access to useful government data, including an open architecture and making data available in multiple formats. The goal is to enable better decision-making, drive transparency, and to help power innovation for a stronger America. Whether for a research project

  6. Drawing as a user experience research tool

    DEFF Research Database (Denmark)

    Fleury, Alexandre

    2011-01-01

    such previous work, two case studies are presented, in which drawings helped investigate the relationship between media technology users and two specific devices, namely television and mobile phones. The experiment generated useful data and opened for further consideration of the method as an appropriate HCI...... research tool....

  7. Developing Effective Undergraduate Research Experience

    Science.gov (United States)

    Evans, Michael; Ilie, Carolina C.

    2011-03-01

    Undergraduate research is a valuable educational tool for students pursuing a degree in physics, but these experiences can become problematic and ineffective if not handled properly. Undergraduate research should be planned as an immersive learning experience in which the student has the opportunity to develop his/her skills in accordance with their interests. Effective undergraduate research experiences are marked by clear, measurable objectives and frequent student-professor collaboration. These objectives should reflect the long and short-term goals of the individual undergraduates, with a heightened focus on developing research skills for future use. 1. Seymour, E., Hunter, A.-B., Laursen, S. L. and DeAntoni, T. (2004), ``Establishing the benefits of research experiences for undergraduates in the sciences: First findings from a three-year study''. Science Education, 88: 493--534. 2. Behar-Horenstein, Linda S., Johnson, Melissa L. ``Enticing Students to Enter Into Undergraduate Research: The Instrumentality of an Undergraduate Course.'' Journal of College Science Teaching 39.3 (2010): 62-70.

  8. Clustered data acquisition for the CMS experiment

    International Nuclear Information System (INIS)

    Gutleber, J.; Antchev, G.; Cano, E.; Csilling, A.; Cittolin, S.; Gigi, D.; Gras, P.; Jacobs, C.; Meijers, F.; Meschi, E.; Oh, A.; Orsini, L.; Pollet, L.; Racz, A.; Samyn, D.; Schwick, C.; Zangrando, L.; Erhan, S.; Gulmini, M.; Sphicas, P.; Ninane, A.

    2001-01-01

    Powerful mainstream computing equipment and the advent of affordable multi-Gigabit communication technology allow us to tackle data acquisition problems with clusters of inexpensive computers. Such networks typically incorporate heterogeneous platforms, real-time partitions and custom devices. Therefore, one must strive for a software infrastructure that efficiently combines the nodes to a single, unified resource for the user. Overall requirements for such middleware are high efficiency and configuration flexibility. Intelligent I/O (I 2 O) is an industry specification that defines a uniform messaging format and executing model for processor-enabled communication equipment. Mapping this concept to a distributed computing environment and encapsulating the details of the specification into an application-programming framework allow us to provide run-time support for cluster operation. The authors give a brief overview of a framework, XDAQ that we designed and implemented at CERN for the Compact Muon Solenoid experiment's prototype data acquisition system

  9. Collaborative Research: Equipment for and Running of the PSI MUSE Experiment

    Energy Technology Data Exchange (ETDEWEB)

    Kohl, Michael [Thomas Jefferson National Accelerator Facility (TJNAF), Newport News, VA (United States)

    2016-10-01

    The R&D funding from this award has been a significant tool to move the Muon Scattering Experiment (MUSE) at the Paul Scherrer Institute in Switzerland forward to the stage of realization. Specifically, this award has enabled Dr. Michael Kohl and his working group at Hampton University to achieve substantial progress toward the goal of providing beam particle tracking with Gas Electron Multiplier (GEM) detectors for MUSE experiment. Establishing a particle detection system that is capable of operating in a high-intensity environment, with a data acquisition system capable of running at several kHz, combined with robust tracking software providing high efficiency for track reconstruction in the presence of noise and backgrounds will have immediate application in many other experiments.

  10. Collaborative Research: Equipment for and Running of the PSI MUSE Experiment

    International Nuclear Information System (INIS)

    Kohl, Michael

    2016-01-01

    The R&D funding from this award has been a significant tool to move the Muon Scattering Experiment (MUSE) at the Paul Scherrer Institute in Switzerland forward to the stage of realization. Specifically, this award has enabled Dr. Michael Kohl and his working group at Hampton University to achieve substantial progress toward the goal of providing beam particle tracking with Gas Electron Multiplier (GEM) detectors for MUSE experiment. Establishing a particle detection system that is capable of operating in a high-intensity environment, with a data acquisition system capable of running at several kHz, combined with robust tracking software providing high efficiency for track reconstruction in the presence of noise and backgrounds will have immediate application in many other experiments.

  11. Enablers and Inhibitors to English Language Learners' Research Process in a High School Setting

    Science.gov (United States)

    Kim, Sung Un

    2015-01-01

    This researcher sought to examine enablers and inhibitors to English language learner (ELL) students' research process within the framework of Carol C. Kuhlthau's Information Search Process (ISP). At a high school forty-eight ELL students in three classes, an English as a Second Language (ESL) teacher, and a biology teacher participated in the…

  12. DIaaS: Data-Intensive workflows as a service - Enabling easy composition and deployment of data-intensive workflows on Virtual Research Environments

    Science.gov (United States)

    Filgueira, R.; Ferreira da Silva, R.; Deelman, E.; Atkinson, M.

    2016-12-01

    We present the Data-Intensive workflows as a Service (DIaaS) model for enabling easy data-intensive workflow composition and deployment on clouds using containers. DIaaS model backbone is Asterism, an integrated solution for running data-intensive stream-based applications on heterogeneous systems, which combines the benefits of dispel4py with Pegasus workflow systems. The stream-based executions of an Asterism workflow are managed by dispel4py, while the data movement between different e-Infrastructures, and the coordination of the application execution are automatically managed by Pegasus. DIaaS combines Asterism framework with Docker containers to provide an integrated, complete, easy-to-use, portable approach to run data-intensive workflows on distributed platforms. Three containers integrate the DIaaS model: a Pegasus node, and an MPI and an Apache Storm clusters. Container images are described as Dockerfiles (available online at http://github.com/dispel4py/pegasus_dispel4py), linked to Docker Hub for providing continuous integration (automated image builds), and image storing and sharing. In this model, all required software (workflow systems and execution engines) for running scientific applications are packed into the containers, which significantly reduces the effort (and possible human errors) required by scientists or VRE administrators to build such systems. The most common use of DIaaS will be to act as a backend of VREs or Scientific Gateways to run data-intensive applications, deploying cloud resources upon request. We have demonstrated the feasibility of DIaaS using the data-intensive seismic ambient noise cross-correlation application (Figure 1). The application preprocesses (Phase1) and cross-correlates (Phase2) traces from several seismic stations. The application is submitted via Pegasus (Container1), and Phase1 and Phase2 are executed in the MPI (Container2) and Storm (Container3) clusters respectively. Although both phases could be executed

  13. Facilitating Data-Intensive Education and Research in Earth Science through Geospatial Web Services

    Science.gov (United States)

    Deng, Meixia

    2009-01-01

    The realm of Earth science (ES) is increasingly data-intensive. Geoinformatics research attempts to robustly smooth and accelerate the flow of data to information, information to knowledge, and knowledge to decisions and to supply necessary infrastructure and tools for advancing ES. Enabling easy access to and use of large volumes of ES data and…

  14. A Network Enabled Platform for Canadian Space Science Data

    Science.gov (United States)

    Rankin, R.; Boteler, D. R.; Jayachandran, T. P.; Mann, I. R.; Sofko, G.; Yau, A. W.

    2008-12-01

    The internet is an example of a pervasive disruptive technology that has transformed society on a global scale. The term "cyberinfrastructure" refers to technology underpinning the collaborative aspect of large science projects and is synonymous with terms such as e-Science, intelligent infrastructure, and/or e- infrastructure. In the context of space science, a significant challenge is to exploit the internet and cyberinfrastructure to form effective virtual organizations (VOs) of scientists that have common or agreed- upon objectives. A typical VO is likely to include universities and government agencies specializing in types of instrumentation (ground and/or space based), which in deployment produce large quantities of space data. Such data is most effectively described by metadata, which if defined in a standard way, facilitates discovery and retrieval of data over the internet by intelligent interfaces and cyberinfrastructure. One recent and significant approach is SPASE, which is being developed by NASA as a data-standard for its Virtual Observatories (VxOs) programs. The space science community in Canada has recently formed a VO designed to complement the e-POP microsatellite mission, and new ground-based observatories (GBOs) that collect data over a large fraction of the Canadian land-mass. The VO includes members of the CGSM community (www.cgsm.ca), which is funded operationally by the Canadian Space Agency. It also includes the UCLA VMO team, and scientists in the NASA THEMIS mission. CANARIE (www.canarie.ca), the federal agency responsible for management, design and operation of Canada's research internet, has recently recognized the value of cyberinfrastucture through the creation of a Network-Enabled-Platforms (NEPs) program. An NEP for space science was funded by CANARIE in its first competition. When fully implemented, the Space Science NEP will consist of a front-end portal providing access to CGSM data. It will utilize an adaptation of the SPASE

  15. RE Data Explorer: Supporting Renewable Energy Zones to Enable Low Emission Development

    Energy Technology Data Exchange (ETDEWEB)

    Cox, Sadie

    2016-10-01

    This fact sheet overviews the benefits of using the RE Data Explorer tool to analyze and develop renewable energy zones. Renewable energy zones are developed through a transmission planning and approval process customized for renewable energy. RE Data Explorer analysis can feed into broader stakeholder discussions and allow stakeholders to easily visualize potential zones. Stakeholders can access pertinent data to inform transmission planning and enable investment.

  16. Development of a research simulator for the study of human factors and experiments

    International Nuclear Information System (INIS)

    Kawano, R.; Shibuya, S.

    1999-01-01

    A research simulator of nuclear power plant for Human Factors was developed. It simulates the behaviors of the 1100MWe BWR nuclear power plant and has almost same functions ant scope of the simulation as a full-scope training simulator. Physical models installed in the system enable us to execute experiments with multi-malfunction scenario. A severe accident simulation package replaces the running simulation code when the maximum core temperature exceeds 1200 deg C and the core approaches meltdown conditions. The central control panel was simulated by soft panels, indicator and operational switches on the panels by computer graphics, displayed on 22 console boxes containing CRT. The introduction of soft panels and EWSs connected with LAN accomplished flexibility and extendibility. Some experiments by using the simulator were executed and the system has been improved based on the experience from the experiments. It is important to evaluate the effectiveness of any new system by using an actual plant size research simulator before its practical application to keep steady and safe operation of nuclear power plants. (author)

  17. Measurement experiment, using NI USB-6008 data acquisition

    Directory of Open Access Journals (Sweden)

    Mihai Bogdan

    2009-05-01

    Full Text Available Educators and researchers worldwide areusing National Instruments products to automateroutine tasks, accomplish new objectives, replaceoutdated and expensive equipment, and demonstratestudents the potential of high technology. Engineershave used virtual instrumentation for more than 25years to bring the power of flexible software and PCtechnology to test, control, and design applicationsmaking accurate analog and digital measurementsfrom DC to 2.7 GHz.The goal of this paper is to teach students basicconcepts of LabVIEW programming, that can be usedto easily integrate hardware and software to acquire,analyze, and present data. The block diagram of yourapplication enables you to define operations to beperformed on your data. The front panel allows theuser to interact with a program while running.

  18. Across the Arctic Teachers Experience Field Research

    Science.gov (United States)

    Warnick, W. K.; Warburton, J.; Wiggins, H. V.; Marshall, S. A.; Darby, D. A.

    2005-12-01

    From studying snow geese on the North Slope of Alaska to sediment coring aboard the U.S. Coast Guard Cutter Healy in the Arctic Ocean, K-12 teachers embark on scientific expeditions as part of a program that strives to make science in the Arctic a "virtual" reality. In the past two years, seventeen K-12 teachers have participated in Teachers and Researchers Exploring and Collaborating (TREC), a program that pairs teachers with researchers to improve science education through arctic field experiences. TREC builds on the scientific and cultural opportunities of the Arctic, linking research and education through topics that naturally engage students and the wider public. TREC includes expeditions as diverse as studying plants at Toolik Field Station, a research facility located 150 miles above the Arctic Circle; climate change studies in Norway's Svalbard archipelago; studying rivers in Siberia; or a trans-arctic expedition aboard the USCGC Healy collecting an integrated geophysical data set. Funded by the National Science Foundation Office of Polar Programs, TREC offers educators experiences in scientific inquiry while encouraging the public and students to become active participants in the scientific inquiry by engaging them virtually in arctic research. TREC uses online outreach elements to convey the research experience to a broad audience. While in remote field locations, teachers and researchers interact with students and the public through online seminars and live calls from the field, online journals with accompanying photos, and online bulletin boards. Since the program's inception in 2004, numerous visitors have posted questions or interacted with teachers, researchers, and students through the TREC website (http://www.arcus.org/trec). TREC teachers are required to transfer their experience of research and current science into their classroom through the development of relevant activities and resources. Teachers and researchers are encouraged to participate

  19. Data You May Like: A Recommender System for Research Data Discovery

    Science.gov (United States)

    Devaraju, A.; Davy, R.; Hogan, D.

    2016-12-01

    Various data portals been developed to facilitate access to research datasets from different sources. For example, the Data Publisher for Earth & Environmental Science (PANGAEA), the Registry of Research Data Repositories (re3data.org), and the National Geoscience Data Centre (NGDC). Due to data quantity and heterogeneity, finding relevant datasets on these portals may be difficult and tedious. Keyword searches based on specific metadata elements or multi-key indexes may return irrelevant results. Faceted searches may be unsatisfactory and time consuming, especially when facet values are exhaustive. We need a much more intelligent way to complement existing searching mechanisms in order to enhance user experiences of the data portals. We developed a recommender system that helps users to find the most relevant research datasets on the CSIRO's Data Access Portal (DAP). The system is based on content-based filtering. We computed the similarity of datasets based on data attributes (e.g., descriptions, fields of research, location, contributors, and provenance) and inference from transaction logs (e.g., the relations among datasets and between queries and datasets). We improved the recommendation quality by assigning weights to data similarities. The weight values are drawn from a survey involving data users. The recommender results for a given dataset are accessible programmatically via a web service. Taking both data attributes and user actions into account, the recommender system will make it easier for researchers to find and reuse data offered through the data portal.

  20. Structuring research methods and data with the research object model: genomics workflows as a case study.

    Science.gov (United States)

    Hettne, Kristina M; Dharuri, Harish; Zhao, Jun; Wolstencroft, Katherine; Belhajjame, Khalid; Soiland-Reyes, Stian; Mina, Eleni; Thompson, Mark; Cruickshank, Don; Verdes-Montenegro, Lourdes; Garrido, Julian; de Roure, David; Corcho, Oscar; Klyne, Graham; van Schouwen, Reinout; 't Hoen, Peter A C; Bechhofer, Sean; Goble, Carole; Roos, Marco

    2014-01-01

    One of the main challenges for biomedical research lies in the computer-assisted integrative study of large and increasingly complex combinations of data in order to understand molecular mechanisms. The preservation of the materials and methods of such computational experiments with clear annotations is essential for understanding an experiment, and this is increasingly recognized in the bioinformatics community. Our assumption is that offering means of digital, structured aggregation and annotation of the objects of an experiment will provide necessary meta-data for a scientist to understand and recreate the results of an experiment. To support this we explored a model for the semantic description of a workflow-centric Research Object (RO), where an RO is defined as a resource that aggregates other resources, e.g., datasets, software, spreadsheets, text, etc. We applied this model to a case study where we analysed human metabolite variation by workflows. We present the application of the workflow-centric RO model for our bioinformatics case study. Three workflows were produced following recently defined Best Practices for workflow design. By modelling the experiment as an RO, we were able to automatically query the experiment and answer questions such as "which particular data was input to a particular workflow to test a particular hypothesis?", and "which particular conclusions were drawn from a particular workflow?". Applying a workflow-centric RO model to aggregate and annotate the resources used in a bioinformatics experiment, allowed us to retrieve the conclusions of the experiment in the context of the driving hypothesis, the executed workflows and their input data. The RO model is an extendable reference model that can be used by other systems as well. The Research Object is available at http://www.myexperiment.org/packs/428 The Wf4Ever Research Object Model is available at http://wf4ever.github.io/ro.

  1. Scidac-Data: Enabling Data Driven Modeling of Exascale Computing

    Science.gov (United States)

    Mubarak, Misbah; Ding, Pengfei; Aliaga, Leo; Tsaris, Aristeidis; Norman, Andrew; Lyon, Adam; Ross, Robert

    2017-10-01

    The SciDAC-Data project is a DOE-funded initiative to analyze and exploit two decades of information and analytics that have been collected by the Fermilab data center on the organization, movement, and consumption of high energy physics (HEP) data. The project analyzes the analysis patterns and data organization that have been used by NOvA, MicroBooNE, MINERvA, CDF, D0, and other experiments to develop realistic models of HEP analysis workflows and data processing. The SciDAC-Data project aims to provide both realistic input vectors and corresponding output data that can be used to optimize and validate simulations of HEP analysis. These simulations are designed to address questions of data handling, cache optimization, and workflow structures that are the prerequisites for modern HEP analysis chains to be mapped and optimized to run on the next generation of leadership-class exascale computing facilities. We present the use of a subset of the SciDAC-Data distributions, acquired from analysis of approximately 71,000 HEP workflows run on the Fermilab data center and corresponding to over 9 million individual analysis jobs, as the input to detailed queuing simulations that model the expected data consumption and caching behaviors of the work running in high performance computing (HPC) and high throughput computing (HTC) environments. In particular we describe how the Sequential Access via Metadata (SAM) data-handling system in combination with the dCache/Enstore-based data archive facilities has been used to develop radically different models for analyzing the HEP data. We also show how the simulations may be used to assess the impact of design choices in archive facilities.

  2. The web-enabled database of JRC-EC: a useful tool for managing european gen 4 materials data

    International Nuclear Information System (INIS)

    Over, H.H.; Dietz, W.

    2008-01-01

    Materials and document databases are important tools to conserve knowledge and experimental materials data of European R and D projects. A web-enabled application guarantees a fast access to these data. In combination with analysis tools the experimental data are used for e.g. mechanical design, construction and lifetime predictions of complex components. The effective and efficient handling of large amounts of generic and detailed materials data with regard to properties related to e.g. fabrication processes, joining techniques, irradiation or aging is one of the basic elements of data management within ongoing nuclear safety and design related European research projects and networks. The paper describes the structure and functionality of Mat-DB and gives examples how these tools can be used for the management and evaluation of materials data for EURATOM FP7 Generation IV reactor types. (authors)

  3. Enabling Research without Geographical Boundaries via Collaborative Research Infrastructures

    Science.gov (United States)

    Gesing, S.

    2016-12-01

    Collaborative research infrastructures on global scale for earth and space sciences face a plethora of challenges from technical implementations to organizational aspects. Science gateways - also known as virtual research environments (VREs) or virtual laboratories - address part of such challenges by providing end-to-end solutions to aid researchers to focus on their specific research questions without the need to become acquainted with the technical details of the complex underlying infrastructures. In general, they provide a single point of entry to tools and data irrespective of organizational boundaries and thus make scientific discoveries easier and faster. The importance of science gateways has been recognized on national as well as on international level by funding bodies and by organizations. For example, the US NSF has just funded a Science Gateways Community Institute, which offers support, consultancy and open accessible software repositories for users and developers; Horizon 2020 provides funding for virtual research environments in Europe, which has led to projects such as VRE4EIC (A Europe-wide Interoperable Virtual Research Environment to Empower Multidisciplinary Research Communities and Accelerate Innovation and Collaboration); national or continental research infrastructures such as XSEDE in the USA, Nectar in Australia or EGI in Europe support the development and uptake of science gateways; the global initiatives International Coalition on Science Gateways, the RDA Virtual Research Environment Interest Group as well as the IEEE Technical Area on Science Gateways have been founded to provide global leadership on future directions for science gateways in general and facilitate awareness for science gateways. This presentation will give an overview on these projects and initiatives aiming at supporting domain researchers and developers with measures for the efficient creation of science gateways, for increasing their usability and sustainability

  4. ASTERIA: Arcsecond Space Telescope Enabling Research in Astrophysics

    Science.gov (United States)

    Knapp, M.; Seager, S.; Smith, M. W.; Pong, C. M.

    2017-12-01

    ASTERIA (Arcsecond Space Telescope Enabling Research in Astrophysics) is a technology demonstration and opportunistic science mission to advance the state of the art in CubeSat capabilities for astrophysical measurements. The goal of ASTERIA is to achieve arcsecond-level line of sight pointing error and highly stable focal plane temperature control. These technologies will enable precision photometry, i.e. the careful measurement of stellar brightness over time. This in turn provides a way to study stellar activity, transiting exoplanets, and other astrophysical phenomena, both during the ASTERIA mission and in future CubeSat constellations. ASTERIA is a 6U CubeSat (roughly 10 x 20 x 30 cm, 12 kg) that will operate in low-Earth orbit. The payload consists of a lens and baffle assembly, a CMOS imager, and a two-axis piezoelectric positioning stage on which the focal plane is mounted. A set of commercial reaction wheels provides coarse attitude control. Fine pointing control is achieved by tracking a set of guide stars on the CMOS sensor and moving the piezoelectric stage to compensate for residual pointing errors. Precision thermal control is achieved by isolating the payload from the spacecraft bus, passively cooling the detector, and using trim heaters to perform small temperature corrections over the course of an observation. The ASTERIA project is a collaboration with MIT and is funded at JPL through the Phaeton Program for training early career employees. Flight hardware was delivered in June 2017, with launch expected in August 2017 and deployment targeted for October 2017.

  5. Data Analysis in Experimental Biomedical Research

    DEFF Research Database (Denmark)

    Markovich, Dmitriy

    This thesis covers two non-related topics in experimental biomedical research: data analysis in thrombin generation experiments (collaboration with Novo Nordisk A/S), and analysis of images and physiological signals in the context of neurovascular signalling and blood flow regulation in the brain...... to critically assess and compare obtained results. We reverse engineered the data analysis performed by CAT, a de facto standard assay in the field. This revealed a number of possibilities to improve its methods of data analysis. We found that experimental calibration data is described well with textbook...

  6. AGC-3 Experiment Irradiation Monitoring Data Qualification Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Hull, Laurence C. [Idaho National Lab. (INL), Idaho Falls, ID (United States). VHTR Technology Development Office

    2014-08-01

    The Graphite Technology Development Program will run a series of six experiments to quantify the effects of irradiation on nuclear-grade graphite. The third experiment, Advanced Graphite Creep 3 (AGC-3), began with Advanced Test Reactor (ATR) Cycle 152B on November 27, 2012, and ended with ATR Cycle 155B on April 23, 2014. This report documents qualification of AGC-3 experiment irradiation monitoring data for use by the Very High Temperature Reactor (VHTR) Technology Development Office (TDO) Program for research and development activities required to design and license the first VHTR nuclear plant. Qualified data meet the requirements for data collection and use as described in the experiment planning and quality assurance documents. Failed data do not meet the requirements. Trend data may not meet the requirements, but may still provide some useable information. The report documents qualification of AGC-3 experiment irradiation monitoring data following MCP-2691. This report also documents whether AGC-3 experiment irradiation monitoring data meet the requirements for data collection as specified in technical and functional requirements documents and quality assurance (QA) plans. Data handling is described showing how data are passed from the data collection experiment to the Nuclear Data Management and Analysis System (NDMAS) team. The data structure is described, including data batches, components, attributes, and response variables. The description of the approach to data qualification includes the steps taken to qualify the data and the specific tests used to verify that the data meet requirements. Finally, the current status of the data received by NDMAS from the AGC-3 experiment is presented with summarized information on test results and resolutions. This report addresses all of the irradiation monitoring data collected during the AGC-3 experiment.

  7. Towards a comprehensive framework for reuse: A reuse-enabling software evolution environment

    Science.gov (United States)

    Basili, V. R.; Rombach, H. D.

    1988-01-01

    Reuse of products, processes and knowledge will be the key to enable the software industry to achieve the dramatic improvement in productivity and quality required to satisfy the anticipated growing demand. Although experience shows that certain kinds of reuse can be successful, general success has been elusive. A software life-cycle technology which allows broad and extensive reuse could provide the means to achieving the desired order-of-magnitude improvements. The scope of a comprehensive framework for understanding, planning, evaluating and motivating reuse practices and the necessary research activities is outlined. As a first step towards such a framework, a reuse-enabling software evolution environment model is introduced which provides a basis for the effective recording of experience, the generalization and tailoring of experience, the formalization of experience, and the (re-)use of experience.

  8. Authentic Astronomy Research Experiences for Teachers: The NASA/IPAC Teacher Archive Research Program (NITARP)

    OpenAIRE

    Rebull, L. M.; Gorjian, V.; Squires, G.

    2012-01-01

    How many times have you gotten a question from the general public, or read a news story, and concluded that “they just don’t understand how real science works?” One really good way to get the word out about how science works is to have more people experience the process of scientific research. Since 2004, the way we have chosen to do this is to provide authentic research experiences for teachers using real data (the program used to be called the Spitzer Teacher Program for Teachers and Stu...

  9. Mediator infrastructure for information integration and semantic data integration environment for biomedical research.

    Science.gov (United States)

    Grethe, Jeffrey S; Ross, Edward; Little, David; Sanders, Brian; Gupta, Amarnath; Astakhov, Vadim

    2009-01-01

    This paper presents current progress in the development of semantic data integration environment which is a part of the Biomedical Informatics Research Network (BIRN; http://www.nbirn.net) project. BIRN is sponsored by the National Center for Research Resources (NCRR), a component of the National Institutes of Health (NIH). A goal is the development of a cyberinfrastructure for biomedical research that supports advance data acquisition, data storage, data management, data integration, data mining, data visualization, and other computing and information processing services over the Internet. Each participating institution maintains storage of their experimental or computationally derived data. Mediator-based data integration system performs semantic integration over the databases to enable researchers to perform analyses based on larger and broader datasets than would be available from any single institution's data. This paper describes recent revision of the system architecture, implementation, and capabilities of the semantically based data integration environment for BIRN.

  10. FOSS Tools for Research Data Management

    Science.gov (United States)

    Stender, Vivien; Jankowski, Cedric; Hammitzsch, Martin; Wächter, Joachim

    2017-04-01

    Established initiatives and organizations, e.g. the Initiative for Scientific Cyberinfrastructures (NSF, 2007) or the European Strategy Forum on Research Infrastructures (ESFRI, 2008), promote and foster the development of sustainable research infrastructures. These infrastructures aim the provision of services supporting scientists to search, visualize and access data, to collaborate and exchange information, as well as to publish data and other results. In this regard, Research Data Management (RDM) gains importance and thus requires the support by appropriate tools integrated in these infrastructures. Different projects provide arbitrary solutions to manage research data. However, within two projects - SUMARIO for land and water management and TERENO for environmental monitoring - solutions to manage research data have been developed based on Free and Open Source Software (FOSS) components. The resulting framework provides essential components for harvesting, storing and documenting research data, as well as for discovering, visualizing and downloading these data on the basis of standardized services stimulated considerably by enhanced data management approaches of Spatial Data Infrastructures (SDI). In order to fully exploit the potentials of these developments for enhancing data management in Geosciences the publication of software components, e.g. via GitHub, is not sufficient. We will use our experience to move these solutions into the cloud e.g. as PaaS or SaaS offerings. Our contribution will present data management solutions for the Geosciences developed in two projects. A sort of construction kit with FOSS components build the backbone for the assembly and implementation of projects specific platforms. Furthermore, an approach is presented to stimulate the reuse of FOSS RDM solutions with cloud concepts. In further projects specific RDM platforms can be set-up much faster, customized to the individual needs and tools can be added during the run-time.

  11. Text data extraction for a prospective, research-focused data mart: implementation and validation.

    Science.gov (United States)

    Hinchcliff, Monique; Just, Eric; Podlusky, Sofia; Varga, John; Chang, Rowland W; Kibbe, Warren A

    2012-09-13

    Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of 'machine generated' sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. There was a near perfect (99.5%) agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor) to parse, abstract and assemble structured data from text data contained in the electronic health

  12. A data management system to enable urgent natural disaster computing

    Science.gov (United States)

    Leong, Siew Hoon; Kranzlmüller, Dieter; Frank, Anton

    2014-05-01

    Civil protection, in particular natural disaster management, is very important to most nations and civilians in the world. When disasters like flash floods, earthquakes and tsunamis are expected or have taken place, it is of utmost importance to make timely decisions for managing the affected areas and reduce casualties. Computer simulations can generate information and provide predictions to facilitate this decision making process. Getting the data to the required resources is a critical requirement to enable the timely computation of the predictions. An urgent data management system to support natural disaster computing is thus necessary to effectively carry out data activities within a stipulated deadline. Since the trigger of a natural disaster is usually unpredictable, it is not always possible to prepare required resources well in advance. As such, an urgent data management system for natural disaster computing has to be able to work with any type of resources. Additional requirements include the need to manage deadlines and huge volume of data, fault tolerance, reliable, flexibility to changes, ease of usage, etc. The proposed data management platform includes a service manager to provide a uniform and extensible interface for the supported data protocols, a configuration manager to check and retrieve configurations of available resources, a scheduler manager to ensure that the deadlines can be met, a fault tolerance manager to increase the reliability of the platform and a data manager to initiate and perform the data activities. These managers will enable the selection of the most appropriate resource, transfer protocol, etc. such that the hard deadline of an urgent computation can be met for a particular urgent activity, e.g. data staging or computation. We associated 2 types of deadlines [2] with an urgent computing system. Soft-hard deadline: Missing a soft-firm deadline will render the computation less useful resulting in a cost that can have severe

  13. [Big data approaches in psychiatry: examples in depression research].

    Science.gov (United States)

    Bzdok, D; Karrer, T M; Habel, U; Schneider, F

    2017-11-29

    The exploration and therapy of depression is aggravated by heterogeneous etiological mechanisms and various comorbidities. With the growing trend towards big data in psychiatry, research and therapy can increasingly target the individual patient. This novel objective requires special methods of analysis. The possibilities and challenges of the application of big data approaches in depression are examined in closer detail. Examples are given to illustrate the possibilities of big data approaches in depression research. Modern machine learning methods are compared to traditional statistical methods in terms of their potential in applications to depression. Big data approaches are particularly suited to the analysis of detailed observational data, the prediction of single data points or several clinical variables and the identification of endophenotypes. A current challenge lies in the transfer of results into the clinical treatment of patients with depression. Big data approaches enable biological subtypes in depression to be identified and predictions in individual patients to be made. They have enormous potential for prevention, early diagnosis, treatment choice and prognosis of depression as well as for treatment development.

  14. Mars Exploration Student Data Teams: Building Foundations and Influencing Students to Pursue STEM Careers through Experiences with Authentic Research

    Science.gov (United States)

    Turney, D.; Grigsby, B.; Murchie, S. L.; Buczkowski, D.; Seelos, K. D.; Nair, H.; McGovern, A.; Morgan, F.; Viviano, C. E.; Goudge, T. A.; Thompson, D.

    2013-12-01

    The Mars Exploration Student Data Teams (MESDT) immerses diverse teams of high school and undergraduate students in an authentic research Science, Technology, Engineering and Mathematics (STEM) based experience and allows students to be direct participants in the scientific process by working with scientists to analyze data sets from NASA's Mars program, specifically from the CRISM instrument. MESDT was created by Arizona State University's Mars Education Program, and is funded through NASA's Compact Reconnaissance Imaging Spectrometer for Mars or CRISM, an instrument onboard the Mars Reconnaissance Orbiter (MRO). Students work with teacher mentors and CRISM team members to analyze data, develop hypotheses, conduct research, submit proposals, critique and revise work. All students begin the program with basic Mars curriculum lessons developed by the MESDT education team. This foundation enables the program to be inclusive of all students. Teachers have reported that populations of students with diverse academic needs and abilities have been successful in this program. The use of technology in the classroom allows the MESDT program to successfully reach a nationwide audience and funding provided by NASA's CRISM instrument allows students to participate free of charge. Recent changes to the program incorporate a partnership with United States Geological Survey (USGS) and a CRISM sponsored competitive scholarship for two teams of students to present their work at the annual USGS Planetary Mappers Meeting. Returning MESDT teachers have attributed an increase in student enrollment and interest to this scholarship opportunity. The 2013 USGS Planetary Mappers Meeting was held in Washington DC which provided an opportunity for the students to meet with their Senators at the US Capitol to explain the science work they had done throughout the year as well as the impact that the program had had on their goals for the future. This opportunity extended to the students by the

  15. An Inversion Recovery NMR Kinetics Experiment

    OpenAIRE

    Williams, Travis J.; Kershaw, Allan D.; Li, Vincent; Wu, Xinping

    2011-01-01

    A convenient laboratory experiment is described in which NMR magnetization transfer by inversion recovery is used to measure the kinetics and thermochemistry of amide bond rotation. The experiment utilizes Varian spectrometers with the VNMRJ 2.3 software, but can be easily adapted to any NMR platform. The procedures and sample data sets in this article will enable instructors to use inversion recovery as a laboratory activity in applied NMR classes and provide research students with a conveni...

  16. Exploration of the impacts of distributed-site Research Experiences for Undergraduates using pre-/post- student interviews

    Science.gov (United States)

    Colella, H.; Hubenthal, M.; Brudzinski, M. R.

    2013-12-01

    The benefits for student participants of undergraduate research opportunities have been well documented. However, advancements in information and communications technologies (ICT) and cultural shifts around online education and virtual peer-to-peer interaction have lead to new models in which to structure such experiences. Currently, these ICT-enabled Research Experiences for Undergraduates (REU) programs connect geographically distributed interns in supportive e-learning communities while maintaining a traditional local mentoring arrangement. To document and explore the effects of distributed REU Sites in more depth, six interns from such a program, the Incorporated Research Institution for Seismology (IRIS) REU, were selected at random and asked to be interviewed about the REU experience. The primary targets of the interviews are to understand the mentor/mentee relationships, feeling of support and development and value of near-peer and far-peer relationships throughout their internship in a distributed REU program, and whether they receive the training necessary to gain confidence as a researcher. We also examine the various communication technologies as well as best practices and strategies that can increase intern connectedness. Pre-internship interviews were conducted in-person at the start of the centralized internship orientation week, while post-internship interviews were virtual (e.g. video chat with Skype or Google Hangout). These semi-structured interviews have full audio recordings and subsequent transcriptions. An additional, virtual follow-up interview will be conducted next spring after the interns have an opportunity to attend and present their research at a national conference (e.g., AGU). Interview material will be analyzed through a process of coding, sorting, local integration, and inclusive integration. Results will also be triangulated with pre- and post- survey data both from participants and other survey data from previous years of the IRIS

  17. Big Data Application in Biomedical Research and Health Care: A Literature Review.

    Science.gov (United States)

    Luo, Jake; Wu, Min; Gopukumar, Deepika; Zhao, Yiqing

    2016-01-01

    Big data technologies are increasingly used for biomedical and health-care informatics research. Large amounts of biological and clinical data have been generated and collected at an unprecedented speed and scale. For example, the new generation of sequencing technologies enables the processing of billions of DNA sequence data per day, and the application of electronic health records (EHRs) is documenting large amounts of patient data. The cost of acquiring and analyzing biomedical data is expected to decrease dramatically with the help of technology upgrades, such as the emergence of new sequencing machines, the development of novel hardware and software for parallel computing, and the extensive expansion of EHRs. Big data applications present new opportunities to discover new knowledge and create novel methods to improve the quality of health care. The application of big data in health care is a fast-growing field, with many new discoveries and methodologies published in the last five years. In this paper, we review and discuss big data application in four major biomedical subdisciplines: (1) bioinformatics, (2) clinical informatics, (3) imaging informatics, and (4) public health informatics. Specifically, in bioinformatics, high-throughput experiments facilitate the research of new genome-wide association studies of diseases, and with clinical informatics, the clinical field benefits from the vast amount of collected patient data for making intelligent decisions. Imaging informatics is now more rapidly integrated with cloud platforms to share medical image data and workflows, and public health informatics leverages big data techniques for predicting and monitoring infectious disease outbreaks, such as Ebola. In this paper, we review the recent progress and breakthroughs of big data applications in these health-care domains and summarize the challenges, gaps, and opportunities to improve and advance big data applications in health care.

  18. The RCSB Protein Data Bank: new resources for research and education.

    Science.gov (United States)

    Rose, Peter W; Bi, Chunxiao; Bluhm, Wolfgang F; Christie, Cole H; Dimitropoulos, Dimitris; Dutta, Shuchismita; Green, Rachel K; Goodsell, David S; Prlic, Andreas; Quesada, Martha; Quinn, Gregory B; Ramos, Alexander G; Westbrook, John D; Young, Jasmine; Zardecki, Christine; Berman, Helen M; Bourne, Philip E

    2013-01-01

    The Research Collaboratory for Structural Bioinformatics Protein Data Bank (RCSB PDB) develops tools and resources that provide a structural view of biology for research and education. The RCSB PDB web site (http://www.rcsb.org) uses the curated 3D macromolecular data contained in the PDB archive to offer unique methods to access, report and visualize data. Recent activities have focused on improving methods for simple and complex searches of PDB data, creating specialized access to chemical component data and providing domain-based structural alignments. New educational resources are offered at the PDB-101 educational view of the main web site such as Author Profiles that display a researcher's PDB entries in a timeline. To promote different kinds of access to the RCSB PDB, Web Services have been expanded, and an RCSB PDB Mobile application for the iPhone/iPad has been released. These improvements enable new opportunities for analyzing and understanding structure data.

  19. Assess program: Interactive data management systems for airborne research

    Science.gov (United States)

    Munoz, R. M.; Reller, J. O., Jr.

    1974-01-01

    Two data systems were developed for use in airborne research. Both have distributed intelligence and are programmed for interactive support among computers and with human operators. The C-141 system (ADAMS) performs flight planning and telescope control functions in addition to its primary role of data acquisition; the CV-990 system (ADDAS) performs data management functions in support of many research experiments operating concurrently. Each system is arranged for maximum reliability in the first priority function, precision data acquisition.

  20. Experience Effect in E-Learning Research

    Science.gov (United States)

    Wu, Bing; Xu, WenXia; Ge, Jun

    This study is a productivity review on the literature gleaned from SSCI, SCIE databases concerning experience in E-Learning research. The result indicates that the number of literature productions on experience effect in ELearning research is still growing from 2005. The main research development country is Croatia, and from the analysis of the publication year, the number of papers is increasing to the peaking in 2010. And the main source title is British Journal of Educational Technology. In addition the subject area concentrated on Education & Educational Research. Moreover the research focuses on are mainly survey research and empirical research, in order to explore experience effect in E-Learning research. Also the limitations and future research of these research were discussed, so that the direction for further research work can be exploited

  1. The Unified Database for BM@N experiment data handling

    Science.gov (United States)

    Gertsenberger, Konstantin; Rogachevsky, Oleg

    2018-04-01

    The article describes the developed Unified Database designed as a comprehensive relational data storage for the BM@N experiment at the Joint Institute for Nuclear Research in Dubna. The BM@N experiment, which is one of the main elements of the first stage of the NICA project, is a fixed target experiment at extracted Nuclotron beams of the Laboratory of High Energy Physics (LHEP JINR). The structure and purposes of the BM@N setup are briefly presented. The article considers the scheme of the Unified Database, its attributes and implemented features in detail. The use of the developed BM@N database provides correct multi-user access to actual information of the experiment for data processing. It stores information on the experiment runs, detectors and their geometries, different configuration, calibration and algorithm parameters used in offline data processing. An important part of any database - user interfaces are presented.

  2. Liquid-handling Lego robots and experiments for STEM education and research.

    Directory of Open Access Journals (Sweden)

    Lukas C Gerber

    2017-03-01

    Full Text Available Liquid-handling robots have many applications for biotechnology and the life sciences, with increasing impact on everyday life. While playful robotics such as Lego Mindstorms significantly support education initiatives in mechatronics and programming, equivalent connections to the life sciences do not currently exist. To close this gap, we developed Lego-based pipetting robots that reliably handle liquid volumes from 1 ml down to the sub-μl range and that operate on standard laboratory plasticware, such as cuvettes and multiwell plates. These robots can support a range of science and chemistry experiments for education and even research. Using standard, low-cost household consumables, programming pipetting routines, and modifying robot designs, we enabled a rich activity space. We successfully tested these activities in afterschool settings with elementary, middle, and high school students. The simplest robot can be directly built from the widely used Lego Education EV3 core set alone, and this publication includes building and experiment instructions to set the stage for dissemination and further development in education and research.

  3. Liquid-handling Lego robots and experiments for STEM education and research.

    Science.gov (United States)

    Gerber, Lukas C; Calasanz-Kaiser, Agnes; Hyman, Luke; Voitiuk, Kateryna; Patil, Uday; Riedel-Kruse, Ingmar H

    2017-03-01

    Liquid-handling robots have many applications for biotechnology and the life sciences, with increasing impact on everyday life. While playful robotics such as Lego Mindstorms significantly support education initiatives in mechatronics and programming, equivalent connections to the life sciences do not currently exist. To close this gap, we developed Lego-based pipetting robots that reliably handle liquid volumes from 1 ml down to the sub-μl range and that operate on standard laboratory plasticware, such as cuvettes and multiwell plates. These robots can support a range of science and chemistry experiments for education and even research. Using standard, low-cost household consumables, programming pipetting routines, and modifying robot designs, we enabled a rich activity space. We successfully tested these activities in afterschool settings with elementary, middle, and high school students. The simplest robot can be directly built from the widely used Lego Education EV3 core set alone, and this publication includes building and experiment instructions to set the stage for dissemination and further development in education and research.

  4. Future research in technological enablers for knowledge management: A worldwide expert study

    DEFF Research Database (Denmark)

    Sarka, Peter; Caldwell, Nicholas H. M.; Ipsen, Christine

    2014-01-01

    Information Technology (IT) is widely considered as an important part of knowledge management (KM). However, failures of KM in organisational practice have been attributed to an overemphasis of IT in KM. An improved understanding of the role of IT within KM in organisations could help to improve...... key research themes articulated by the KM experts to enhance and develop KM in relation to technological enablers....

  5. Exploring Efficiencies in Data Reduction, Analysis, and Distribution in the Exascale Era

    CERN Multimedia

    CERN. Geneva

    2013-01-01

    DataDirect Networks (DDN) is world leader in massively scalable storage. Fellinger will discuss how the growth of data sets beyond the petabyte boundary presents new challenges to researchers in delivering and extracting usable information. He will also explore a Big Data processing architecture that overcomes constraints in network bandwidth and service layers in large-scale data distribution to enable researchers to request raw data through a filter or an analysis library. This technology, operating directly within the storage device, enables the reduction of service latency and process cycles to provide a more efficient feedback loop in iterative scientific experiments to increase data-intensive processing efficiency by up to 400%. About the speaker Dave Fellinger has over three decades of engineering experience, including film systems, ASIC design and development, GaAs semiconductor manufacture, RAID and storage systems, and video processing devices, and has architected high-performance storage syst...

  6. Technical Note: Harmonizing met-ocean model data via standard web services within small research groups

    Science.gov (United States)

    Signell, Richard; Camossi, E.

    2016-01-01

    Work over the last decade has resulted in standardised web services and tools that can significantly improve the efficiency and effectiveness of working with meteorological and ocean model data. While many operational modelling centres have enabled query and access to data via common web services, most small research groups have not. The penetration of this approach into the research community, where IT resources are limited, can be dramatically improved by (1) making it simple for providers to enable web service access to existing output files; (2) using free technologies that are easy to deploy and configure; and (3) providing standardised, service-based tools that work in existing research environments. We present a simple, local brokering approach that lets modellers continue to use their existing files and tools, while serving virtual data sets that can be used with standardised tools. The goal of this paper is to convince modellers that a standardised framework is not only useful but can be implemented with modest effort using free software components. We use NetCDF Markup language for data aggregation and standardisation, the THREDDS Data Server for data delivery, pycsw for data search, NCTOOLBOX (MATLAB®) and Iris (Python) for data access, and Open Geospatial Consortium Web Map Service for data preview. We illustrate the effectiveness of this approach with two use cases involving small research modelling groups at NATO and USGS.

  7. Involving Research Stakeholders in Developing Policy on Sharing Public Health Research Data in Kenya

    Science.gov (United States)

    Jao, Irene; Kombe, Francis; Mwalukore, Salim; Bull, Susan; Parker, Michael; Kamuya, Dorcas; Molyneux, Sassy

    2015-01-01

    Increased global sharing of public health research data has potential to advance scientific progress but may present challenges to the interests of research stakeholders, particularly in low-to-middle income countries. Policies for data sharing should be responsive to public views, but there is little evidence of the systematic study of these from low-income countries. This qualitative study explored views on fair data-sharing processes among 60 stakeholders in Kenya with varying research experience, using a deliberative approach. Stakeholders’ attitudes were informed by perceptions of benefit and concerns for research data sharing, including risks of stigmatization, loss of privacy, and undermining scientific careers and validity, reported in detail elsewhere. In this article, we discuss institutional trust-building processes seen as central to perceptions of fairness in sharing research data in this setting, including forms of community involvement, individual prior awareness and agreement to data sharing, independence and accountability of governance mechanisms, and operating under a national framework. PMID:26297748

  8. The SMART Platform: early experience enabling substitutable applications for electronic health records

    Science.gov (United States)

    Mandel, Joshua C; Murphy, Shawn N; Bernstam, Elmer Victor; Ramoni, Rachel L; Kreda, David A; McCoy, J Michael; Adida, Ben; Kohane, Isaac S

    2012-01-01

    Objective The Substitutable Medical Applications, Reusable Technologies (SMART) Platforms project seeks to develop a health information technology platform with substitutable applications (apps) constructed around core services. The authors believe this is a promising approach to driving down healthcare costs, supporting standards evolution, accommodating differences in care workflow, fostering competition in the market, and accelerating innovation. Materials and methods The Office of the National Coordinator for Health Information Technology, through the Strategic Health IT Advanced Research Projects (SHARP) Program, funds the project. The SMART team has focused on enabling the property of substitutability through an app programming interface leveraging web standards, presenting predictable data payloads, and abstracting away many details of enterprise health information technology systems. Containers—health information technology systems, such as electronic health records (EHR), personally controlled health records, and health information exchanges that use the SMART app programming interface or a portion of it—marshal data sources and present data simply, reliably, and consistently to apps. Results The SMART team has completed the first phase of the project (a) defining an app programming interface, (b) developing containers, and (c) producing a set of charter apps that showcase the system capabilities. A focal point of this phase was the SMART Apps Challenge, publicized by the White House, using http://www.challenge.gov website, and generating 15 app submissions with diverse functionality. Conclusion Key strategic decisions must be made about the most effective market for further disseminating SMART: existing market-leading EHR vendors, new entrants into the EHR market, or other stakeholders such as health information exchanges. PMID:22427539

  9. Immediate data access system for LHD experiments

    International Nuclear Information System (INIS)

    Emoto, M.; Iwadare, Y.; Nagayama, Y.

    2004-01-01

    Several kinds of computer systems are used to perform large helical device (LHD) experiments, and each produces its own data format. Therefore, it has been difficult to deal with these data simultaneously. In order to solve this problem, the Kaiseki server was developed; it has been facilitating the unified retrieval of LHD data. The data acquired or analyzed by various computer systems are converted into the unified ASCII format, or Kaiseki format, and transferred to the Kaiseki server. With this method, the researchers can visualize and analyze the data produced by various kinds of computers in the same way. Because validations are needed before registering on the Kaiseki server, it takes time to make the validated data available. However, some researchers need data as soon as it is gathered in order to adjust their instruments during the experiments. To satisfy this requirement, a new visualization system has been under development. The new system has two ways to visualize the data as physical values from the raw data. If the conversion task is not complex, the NIFSscope, a visualization tool, converts the raw data into physics data by itself. If the task is too complex to handle, it asks the ANACalc server to make physics data. When the ANACalc server receives a request, it delegates calculation programs to convert the acquired data into physics data. Because the interfaces between the server and the calculation processes are independent of programming languages and operating systems, the calculation processes can be placed on different computers and the server load can be reduced. Therefore, the system can respond to changes in requirements by replacing the calculation programs, and can easily be expanded by increasing the number of calculation servers

  10. Clinical data miner: an electronic case report form system with integrated data preprocessing and machine-learning libraries supporting clinical diagnostic model research.

    Science.gov (United States)

    Installé, Arnaud Jf; Van den Bosch, Thierry; De Moor, Bart; Timmerman, Dirk

    2014-10-20

    Using machine-learning techniques, clinical diagnostic model research extracts diagnostic models from patient data. Traditionally, patient data are often collected using electronic Case Report Form (eCRF) systems, while mathematical software is used for analyzing these data using machine-learning techniques. Due to the lack of integration between eCRF systems and mathematical software, extracting diagnostic models is a complex, error-prone process. Moreover, due to the complexity of this process, it is usually only performed once, after a predetermined number of data points have been collected, without insight into the predictive performance of the resulting models. The objective of the study of Clinical Data Miner (CDM) software framework is to offer an eCRF system with integrated data preprocessing and machine-learning libraries, improving efficiency of the clinical diagnostic model research workflow, and to enable optimization of patient inclusion numbers through study performance monitoring. The CDM software framework was developed using a test-driven development (TDD) approach, to ensure high software quality. Architecturally, CDM's design is split over a number of modules, to ensure future extendability. The TDD approach has enabled us to deliver high software quality. CDM's eCRF Web interface is in active use by the studies of the International Endometrial Tumor Analysis consortium, with over 4000 enrolled patients, and more studies planned. Additionally, a derived user interface has been used in six separate interrater agreement studies. CDM's integrated data preprocessing and machine-learning libraries simplify some otherwise manual and error-prone steps in the clinical diagnostic model research workflow. Furthermore, CDM's libraries provide study coordinators with a method to monitor a study's predictive performance as patient inclusions increase. To our knowledge, CDM is the only eCRF system integrating data preprocessing and machine-learning libraries

  11. Enabling Data Intensive Science through Service Oriented Science: Virtual Laboratories and Science Gateways

    Science.gov (United States)

    Lescinsky, D. T.; Wyborn, L. A.; Evans, B. J. K.; Allen, C.; Fraser, R.; Rankine, T.

    2014-12-01

    We present collaborative work on a generic, modular infrastructure for virtual laboratories (VLs, similar to science gateways) that combine online access to data, scientific code, and computing resources as services that support multiple data intensive scientific computing needs across a wide range of science disciplines. We are leveraging access to 10+ PB of earth science data on Lustre filesystems at Australia's National Computational Infrastructure (NCI) Research Data Storage Infrastructure (RDSI) node, co-located with NCI's 1.2 PFlop Raijin supercomputer and a 3000 CPU core research cloud. The development, maintenance and sustainability of VLs is best accomplished through modularisation and standardisation of interfaces between components. Our approach has been to break up tightly-coupled, specialised application packages into modules, with identified best techniques and algorithms repackaged either as data services or scientific tools that are accessible across domains. The data services can be used to manipulate, visualise and transform multiple data types whilst the scientific tools can be used in concert with multiple scientific codes. We are currently designing a scalable generic infrastructure that will handle scientific code as modularised services and thereby enable the rapid/easy deployment of new codes or versions of codes. The goal is to build open source libraries/collections of scientific tools, scripts and modelling codes that can be combined in specially designed deployments. Additional services in development include: provenance, publication of results, monitoring, workflow tools, etc. The generic VL infrastructure will be hosted at NCI, but can access alternative computing infrastructures (i.e., public/private cloud, HPC).The Virtual Geophysics Laboratory (VGL) was developed as a pilot project to demonstrate the underlying technology. This base is now being redesigned and generalised to develop a Virtual Hazards Impact and Risk Laboratory

  12. Grid-enabled measures: using Science 2.0 to standardize measures and share data.

    Science.gov (United States)

    Moser, Richard P; Hesse, Bradford W; Shaikh, Abdul R; Courtney, Paul; Morgan, Glen; Augustson, Erik; Kobrin, Sarah; Levin, Kerry Y; Helba, Cynthia; Garner, David; Dunn, Marsha; Coa, Kisha

    2011-05-01

    Scientists are taking advantage of the Internet and collaborative web technology to accelerate discovery in a massively connected, participative environment--a phenomenon referred to by some as Science 2.0. As a new way of doing science, this phenomenon has the potential to push science forward in a more efficient manner than was previously possible. The Grid-Enabled Measures (GEM) database has been conceptualized as an instantiation of Science 2.0 principles by the National Cancer Institute (NCI) with two overarching goals: (1) promote the use of standardized measures, which are tied to theoretically based constructs; and (2) facilitate the ability to share harmonized data resulting from the use of standardized measures. The first is accomplished by creating an online venue where a virtual community of researchers can collaborate together and come to consensus on measures by rating, commenting on, and viewing meta-data about the measures and associated constructs. The second is accomplished by connecting the constructs and measures to an ontological framework with data standards and common data elements such as the NCI Enterprise Vocabulary System (EVS) and the cancer Data Standards Repository (caDSR). This paper will describe the web 2.0 principles on which the GEM database is based, describe its functionality, and discuss some of the important issues involved with creating the GEM database such as the role of mutually agreed-on ontologies (i.e., knowledge categories and the relationships among these categories--for data sharing). Published by Elsevier Inc.

  13. Data management routines for reproducible research using the G-Node Python Client library.

    Science.gov (United States)

    Sobolev, Andrey; Stoewer, Adrian; Pereira, Michael; Kellner, Christian J; Garbers, Christian; Rautenberg, Philipp L; Wachtler, Thomas

    2014-01-01

    Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German INCF Node aims to provide open-source solutions for this domain that support the scientific data management and analysis workflow, and thus facilitate future data access and reproducible research. G-Node provides a data management system, accessible through an application interface, that is based on a combination of standardized data representation and flexible data annotation to account for the variety of experimental paradigms in electrophysiology. The G-Node Python Library exposes these services to the Python environment, enabling researchers to organize and access their experimental data using their familiar tools while gaining the advantages that a centralized storage entails. The library provides powerful query features, including data slicing and selection by metadata, as well as fine-grained permission control for collaboration and data sharing. Here we demonstrate key actions in working with experimental neuroscience data, such as building a metadata structure, organizing recorded data in datasets, annotating data, or selecting data regions of interest, that can be automated to large degree using the library. Compliant with existing de-facto standards, the G-Node Python Library is compatible with many Python tools in the field of neurophysiology and thus enables seamless integration of data organization into the scientific data workflow.

  14. The web-enabled database of JRC-EC, a useful tool for managing European Gen IV materials data

    International Nuclear Information System (INIS)

    Over, H.H.; Dietz, W.

    2008-01-01

    Materials and document databases are important tools to conserve knowledge and experimental materials data of European R and D projects. A web-enabled application guarantees a fast access to these data. In combination with analysis tools the experimental data are used for e.g. mechanical design, construction and lifetime predictions of complex components. The effective and efficient handling of large amounts of generic and detailed materials data with regard to properties related to e.g. fabrication processes, joining techniques, irradiation or aging is one of the basic elements of data management within ongoing nuclear safety and design related European research projects and networks. The paper describes the structure and functionality of Mat-DB and gives examples how these tools can be used for the management and evaluation of materials data of European (national or multi-national) R and D activities or future reactor types such as the EURATOM FP7 Generation IV reactor types or the heavy liquid metals cooled reactor

  15. Visualizer: 3D Gridded Data Visualization Software for Geoscience Education and Research

    Science.gov (United States)

    Harwood, C.; Billen, M. I.; Kreylos, O.; Jadamec, M.; Sumner, D. Y.; Kellogg, L. H.; Hamann, B.

    2008-12-01

    In both research and education learning is an interactive and iterative process of exploring and analyzing data or model results. However, visualization software often presents challenges on the path to learning because it assumes the user already knows the locations and types of features of interest, instead of enabling flexible and intuitive examination of results. We present examples of research and teaching using the software, Visualizer, specifically designed to create an effective and intuitive environment for interactive, scientific analysis of 3D gridded data. Visualizer runs in a range of 3D virtual reality environments (e.g., GeoWall, ImmersaDesk, or CAVE), but also provides a similar level of real-time interactivity on a desktop computer. When using Visualizer in a 3D-enabled environment, the software allows the user to interact with the data images as real objects, grabbing, rotating or walking around the data to gain insight and perspective. On the desktop, simple features, such as a set of cross-bars marking the plane of the screen, provide extra 3D spatial cues that allow the user to more quickly understand geometric relationships within the data. This platform portability allows the user to more easily integrate research results into classroom demonstrations and exercises, while the interactivity provides an engaging environment for self-directed and inquiry-based learning by students. Visualizer software is freely available for download (www.keckcaves.org) and runs on Mac OSX and Linux platforms.

  16. Methodological considerations related to nurse researchers using their own experience of a phenomenon within phenomenology.

    Science.gov (United States)

    Johnston, Colleen M; Wallis, Marianne; Oprescu, Florin I; Gray, Marion

    2017-03-01

    This paper summarizes phenomenology and discusses how nurses can use their own experiences as data and maintain rigour within the method. It explores how data from researchers experiencing the phenomenon of interest could be used to explicate assumptions and pre-understandings and may also be used as data. While the ethnographic concept of insider research has gained popularity, the notion of researcher as participant in phenomenology is relatively new. The lived experience of a phenomenon is unique to each person and utilization of the nurse researcher's experiences of the phenomenon should be considered for inclusion as data. Discussion paper. Articles from 2001 - 2015 in the CINAHL and PubMed databases were identified using keywords such as 'insider research', 'phenomenology', 'bracketing' and 'qualitative research'. In addition, reference lists from articles used were examined to identify additional literature. Phenomenology is a valuable research method. Usability, credibility, trustworthiness and auditability of data collected must be considered to ensure rigour and maintain orientation to the phenomenon under investigation. Nurse researchers may be interviewed as participants if these four principles are considered and methods used are made explicit. Utilizing appropriate research methods are as important as getting clinical practice correct to advance knowledge and benefit those under our care. We recommend using the researchers' experience as a data source to gain a complete picture of the phenomenon under investigation. Using the approach proposed here, nurses can ensure they are incorporating all data sources available while maintaining research rigour. © 2016 John Wiley & Sons Ltd.

  17. Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs

    Energy Technology Data Exchange (ETDEWEB)

    Potter, Jennifer; Cappers, Peter

    2017-08-28

    The Demand Response Advanced Controls Framework and Assessment of Enabling Technology Costs research describe a variety of DR opportunities and the various bulk power system services they can provide. The bulk power system services are mapped to a generalized taxonomy of DR “service types”, which allows us to discuss DR opportunities and bulk power system services in fewer yet broader categories that share similar technological requirements which mainly drive DR enablement costs. The research presents a framework for the costs to automate DR and provides descriptions of the various elements that drive enablement costs. The report introduces the various DR enabling technologies and end-uses, identifies the various services that each can provide to the grid and provides the cost assessment for each enabling technology. In addition to a report, this research includes a Demand Response Advanced Controls Database and User Manual. They are intended to provide users with the data that underlies this research and instructions for how to use that database more effectively and efficiently.

  18. Designing Effective Undergraduate Research Experiences

    Science.gov (United States)

    Severson, S.

    2010-12-01

    I present a model for designing student research internships that is informed by the best practices of the Center for Adaptive Optics (CfAO) Professional Development Program. The dual strands of the CfAO education program include: the preparation of early-career scientists and engineers in effective teaching; and changing the learning experiences of students (e.g., undergraduate interns) through inquiry-based "teaching laboratories." This paper will focus on the carry-over of these ideas into the design of laboratory research internships such as the CfAO Mainland internship program as well as NSF REU (Research Experiences for Undergraduates) and senior-thesis or "capstone" research programs. Key ideas in maximizing student learning outcomes and generating productive research during internships include: defining explicit content, scientific process, and attitudinal goals for the project; assessment of student prior knowledge and experience, then following up with formative assessment throughout the project; setting reasonable goals with timetables and addressing motivation; and giving students ownership of the research by implementing aspects of the inquiry process within the internship.

  19. Open Data in Global Environmental Research: Findings from the Community

    Energy Technology Data Exchange (ETDEWEB)

    Van Honk, J.; Calero-Medina, C.; Costas, R.

    2016-07-01

    This paper presents findings from the Belmont Forum’s survey on Open Data which targeted the global environmental research and data infrastructure community (Schmidt, Gemeinholzer & Treloar, 2016). It highlights users’ perceptions of the term “open data”, expectations of infrastructure functionalities, and barriers and enablers for the sharing of data. A wide range of good practice examples was pointed out by the respondents which demonstrates a substantial uptake of data sharing through e-infrastructures and a further need for enhancement and consolidation. Among all policy responses, funder policies seem to be the most important motivator. This supports the conclusion that stronger mandates will strengthen the case for data sharing. The Belmont Forum, a group of high-level representatives from major funding agencies across the globe, coordinates funding for collaborative research to address the challenges and opportunities of global environmental change. In particular, the E-Infrastructure and Data Management Collaborative Research Action has brought together domain scientists, computer and information scientists, legal scholars, social scientists, and other experts from more than 14 countries to establish recommendations on how the Belmont Forum can implement a more coordinated, holistic, and sustainable approach to the funding and support of global environmental change research. (Author)

  20. Review of Quality Assurance in SKB's Repository Research Experiments

    International Nuclear Information System (INIS)

    Hicks, T.W.

    2007-01-01

    SKB is preparing licence applications for a spent nuclear fuel encapsulation plant and repository which will be supported by the SR-Site safety report. A separate safety report, SR-Can, has been produced by SKB in preparation for the SR-Site report. SKI is in the process of reviewing the SR-Can safety report. In preparation for this review, and with a view to building confidence in SKB's research activities and understanding SKB's handling of data and other information, SKI has examined SKB's application of QA measures in the management and conduct of repository research and development projects that support the SR-Can safety assessment. These preliminary investigations will serve to support the preparation of more detailed quality and technical audits of SKB's repository safety assessment after the submission of a licence application. SKI's approach to this QA review is based on the consideration of quality-affecting aspects of a selection of SKB's research and development activities. As part of this review, SKI identified the need to examine quality-related aspects of some of the many experiments and investigations that form part of SKB's repository research programme. This report presents the findings of such a review, focusing on experiments concerned with the properties and performance of the engineered barrier system. First, in order to establish a broad understanding of QA requirements for repository scientific investigations, QA procedures implemented in the management of research and development activities for the low-level radioactive waste repository near Drigg in the UK and the Waste Isolation Pilot Plant and Yucca Mountain repository projects in the US were studied. The QA procedures for experiments and tests undertaken in these projects were compared with those implemented by SKB. Key findings are: QA programmes have been implemented for each repository development programme in response to regulatory requirements. The need for regular audits of the

  1. Correlations between nuclear data and integral slab experiments: the case of hafnium

    International Nuclear Information System (INIS)

    Palau, J.M.

    1999-01-01

    The aim of this work was to evaluate how much integral slab experiments can both reduce discrepancies between experimental results and calculations, and improve the knowledge of hafnium isotopes neutronic parameters by an adapted sensitivity and uncertainty method. A statistical approach, based on the generalized least squares method and perturbation theory, has been incorporated into our calculation system in order to deduce microscopic cross-section adjustments from observed integral measurements on this particular 'mock-up' reactor.In this study it has been established that the correlations between integral parameters and hafnium capture cross-sections enable specific variations in the region of resolved resonances at the level of multigroup and punctual cross-sections recommended data (JEF-2.2 evaluation) to be highlighted. The use of determinist methods together with Monte Carlo- type simulations enabled a depth analysis of the modelling approximations to be carried out. Furthermore, the sensitivity coefficient validation technique employed leads to a reliable assessment of the quality of the new basic nuclear data. In this instance, the adjustments proposed for certain isotope 177 Hf resonance parameters reduce, after error propagation, by 3 to 5 per cent the difference between experimental results and calculations related to this absorbent's efficiency. Beyond this particular application, the qualification methodology integrated in our calculation system should enable other basic sizing parameters to be treated (chemical / geometric data or other unexplored nuclear data) to make technological requirements less stringent. (author)

  2. Learning Practice-Based Research Methods: Capturing the Experiences of MSW Students

    Science.gov (United States)

    Natland, Sidsel; Weissinger, Erika; Graaf, Genevieve; Carnochan, Sarah

    2016-01-01

    The literature on teaching research methods to social work students identifies many challenges, such as dealing with the tensions related to producing research relevant to practice, access to data to teach practice-based research, and limited student interest in learning research methods. This is an exploratory study of the learning experiences of…

  3. Repository of AGH University of Science and Technology – experiences and attitudes of research staff of AGH University of Science and Technology

    Directory of Open Access Journals (Sweden)

    Paulina Maria Strejczek-Jaźwińska

    2017-12-01

    Full Text Available The aim of the stude is presentation of research conclusions concerning experiences and attitudes of members of research staff of AGH academic circles towards already existing repositories and bases of publications, as well as their attitude to the Repositoryof AGH, currently under construction. The research is based on electronic surveys, designed to study also the academic circles’ expectations of the system and its interface. The survey was prepared and designed used Lime Survey, a tool that enables disclosing it on-line in an electronic form; afterwards it was e-mailed to chosen research groups. The e-mail contained invitation to cooperation with the constructed Repository, a link to the survey and a link to educational materials about bases of publications. This article presents results, observations and conclusions drawn from analysis of gathered data.

  4. WormBase 2016: expanding to enable helminth genomic research.

    Science.gov (United States)

    Howe, Kevin L; Bolt, Bruce J; Cain, Scott; Chan, Juancarlos; Chen, Wen J; Davis, Paul; Done, James; Down, Thomas; Gao, Sibyl; Grove, Christian; Harris, Todd W; Kishore, Ranjana; Lee, Raymond; Lomax, Jane; Li, Yuling; Muller, Hans-Michael; Nakamura, Cecilia; Nuin, Paulo; Paulini, Michael; Raciti, Daniela; Schindelman, Gary; Stanley, Eleanor; Tuli, Mary Ann; Van Auken, Kimberly; Wang, Daniel; Wang, Xiaodong; Williams, Gary; Wright, Adam; Yook, Karen; Berriman, Matthew; Kersey, Paul; Schedl, Tim; Stein, Lincoln; Sternberg, Paul W

    2016-01-04

    WormBase (www.wormbase.org) is a central repository for research data on the biology, genetics and genomics of Caenorhabditis elegans and other nematodes. The project has evolved from its original remit to collect and integrate all data for a single species, and now extends to numerous nematodes, ranging from evolutionary comparators of C. elegans to parasitic species that threaten plant, animal and human health. Research activity using C. elegans as a model system is as vibrant as ever, and we have created new tools for community curation in response to the ever-increasing volume and complexity of data. To better allow users to navigate their way through these data, we have made a number of improvements to our main website, including new tools for browsing genomic features and ontology annotations. Finally, we have developed a new portal for parasitic worm genomes. WormBase ParaSite (parasite.wormbase.org) contains all publicly available nematode and platyhelminth annotated genome sequences, and is designed specifically to support helminth genomic research. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

  5. Clinical data integration model. Core interoperability ontology for research using primary care data.

    Science.gov (United States)

    Ethier, J-F; Curcin, V; Barton, A; McGilchrist, M M; Bastiaens, H; Andreasson, A; Rossiter, J; Zhao, L; Arvanitis, T N; Taweel, A; Delaney, B C; Burgun, A

    2015-01-01

    flexible and extensible framework for all types of interaction between health record systems and research systems. CDIM, as core ontology of such an approach, enables simplicity and consistency of design across the heterogeneous software landscape and can support the specific needs of EHR-driven phenotyping research using primary care data.

  6. SPECTRa: the deposition and validation of primary chemistry research data in digital repositories.

    Science.gov (United States)

    Downing, Jim; Murray-Rust, Peter; Tonge, Alan P; Morgan, Peter; Rzepa, Henry S; Cotterill, Fiona; Day, Nick; Harvey, Matt J

    2008-08-01

    The SPECTRa (Submission, Preservation and Exposure of Chemistry Teaching and Research Data) project has investigated the practices of chemists in archiving and disseminating primary chemical data from academic research laboratories. To redress the loss of the large amount of data never archived or disseminated, we have developed software for data publication into departmental and institutional Open Access digital repositories (DSpace). Data adhering to standard formats in selected disciplines (crystallography, NMR, computational chemistry) is transformed to XML (CML, Chemical Markup Language) which provides added validation. Context-specific chemical metadata and persistent Handle identifiers are added to enable long-term data reuse. It was found essential to provide an embargo mechanism, and policies for operating this and other processes are presented.

  7. Research Institute for Technical Careers

    Science.gov (United States)

    Glenn, Ronald L.

    1996-01-01

    The NASA research grant to Wilberforce University enabled us to establish the Research Institute for Technical Careers (RITC) in order to improve the teaching of science and engineering at Wilberforce. The major components of the research grant are infrastructure development, establishment of the Wilberforce Intensive Summer Experience (WISE), and Joint Research Collaborations with NASA Scientists. (A) Infrastructure Development. The NASA grant has enabled us to improve the standard of our chemistry laboratory and establish the electronics, design, and robotics laboratories. These laboratories have significantly improved the level of instruction at Wilberforce University. (B) Wilberforce Intensive Summer Experience (WISE). The WISE program is a science and engineering bridge program for prefreshman students. It is an intensive academic experience designed to strengthen students' knowledge in mathematics, science, engineering, computing skills, and writing. (C) Joint Collaboration. Another feature of the grant is research collaborations between NASA Scientists and Wilberforce University Scientists. These collaborations have enabled our faculty and students to conduct research at NASA Lewis during the summer and publish research findings in various journals and scientific proceedings.

  8. Sustainable Venture Capital Investments: An Enabler Investigation

    Directory of Open Access Journals (Sweden)

    Elena Antarciuc

    2018-04-01

    Full Text Available Investing in sustainable projects can help tackle the current sustainability challenges. Venture capital investments can contribute significantly to the growth of sustainable start-ups. Sustainable venture capital (SVC research is just emerging. This paper identifies enablers for sustainable venture capital investments in Saudi Arabia taking into account different stakeholders and firm’s tangible and intangible resources. Using perspectives from venture capital experts in Saudi Arabia and the grey-based Decision-Making Trial and Evaluation Laboratory (DEMATEL method, this study pinpoints the most critical enablers and investigates their causal and effect interconnections. The methodological process consists of reviewing the SVC literature and consulting the experts to identify the SVC enablers, creating a questionnaire, acquiring the answers from four experts, analyzing the data with grey-based DEMATEL and performing a sensitivity analysis. The government use of international standards, policies and regulations for sustainable investments, the commitment of the venture capitalists to sustainability and their deep understanding of sustainable business models are the most influential enablers. The paper concludes with implications for different actors, limitations and prospective directions for the sustainable venture capital research.

  9. VLAM-G: Interactive Data Driven Workflow Engine for Grid-Enabled Resources

    Directory of Open Access Journals (Sweden)

    Vladimir Korkhov

    2007-01-01

    Full Text Available Grid brings the power of many computers to scientists. However, the development of Grid-enabled applications requires knowledge about Grid infrastructure and low-level API to Grid services. In turn, workflow management systems provide a high-level environment for rapid prototyping of experimental computing systems. Coupling Grid and workflow paradigms is important for the scientific community: it makes the power of the Grid easily available to the end user. The paradigm of data driven workflow execution is one of the ways to enable distributed workflow on the Grid. The work presented in this paper is carried out in the context of the Virtual Laboratory for e-Science project. We present the VLAM-G workflow management system and its core component: the Run-Time System (RTS. The RTS is a dataflow driven workflow engine which utilizes Grid resources, hiding the complexity of the Grid from a scientist. Special attention is paid to the concept of dataflow and direct data streaming between distributed workflow components. We present the architecture and components of the RTS, describe the features of VLAM-G workflow execution, and evaluate the system by performance measurements and a real life use case.

  10. The graphics system and the data saving for the SAPHIR experiment

    International Nuclear Information System (INIS)

    Albold, D.

    1990-08-01

    Important extensions have been made to the data acquisition system SOS for the SAPHIR experiment at the Bonn ELSA facilities. As support for various online-programs, controlling components of the detector, a graphic system for presenting data was developed. This enables any program in the system to use all graphic devices. Main component is a program serving requests for presentation on a 19 inch color monitor. Window-technique allows a presentation of several graphics on one screen. Equipped with a trackball and using menus, this is an easy to use and powerful tool in controlling the experiment. Other important extensions concern data storage. A huge amount of event data can be stored on 8 mm cassettes by the program Eventsaver. This program can be controlled by a component of the SAPHIR-Online SOL running on a VAX-Computer and using windows and menus. The smaller amount of data, containing parameters and programs, which should be accessible within a small period of time, can be stored on a magnetic disk. A program supporting a file-structure for access to this disk is described. (orig./HSI) [de

  11. Enabling narrative pedagogy: inviting, waiting, and letting be.

    Science.gov (United States)

    Ironside, Pamela M

    2014-01-01

    This article describes how teachers enable Narrative Pedagogy in their courses by explicating the Concernful Practice Inviting: Waiting and Letting Be. Narrative Pedagogy, a research-based, phenomenological approach to teaching and learning, extends conventional pedagogies and offers nursing faculty an alternative way of transforming their schools and courses. Using hermeneutic phenomenology, interview data collected over a 10-year period were analyzed by coding practical examples of teachers' efforts to enact Narrative Pedagogy. When Narrative Pedagogy is enacted, teachers and students focus on thinking and learning together about nursing phenomena and seek new understandings about how they may provide care in the myriad situations they encounter. Although the Concernful Practices co-occur, explicating inviting experiences can assist new teachers, and those seeking to extend their pedagogical literacy, by providing new understandings of how Narrative Pedagogy can be enacted.

  12. Text data extraction for a prospective, research-focused data mart: implementation and validation

    Directory of Open Access Journals (Sweden)

    Hinchcliff Monique

    2012-09-01

    Full Text Available Abstract Background Translational research typically requires data abstracted from medical records as well as data collected specifically for research. Unfortunately, many data within electronic health records are represented as text that is not amenable to aggregation for analyses. We present a scalable open source SQL Server Integration Services package, called Regextractor, for including regular expression parsers into a classic extract, transform, and load workflow. We have used Regextractor to abstract discrete data from textual reports from a number of ‘machine generated’ sources. To validate this package, we created a pulmonary function test data mart and analyzed the quality of the data mart versus manual chart review. Methods Eleven variables from pulmonary function tests performed closest to the initial clinical evaluation date were studied for 100 randomly selected subjects with scleroderma. One research assistant manually reviewed, abstracted, and entered relevant data into a database. Correlation with data obtained from the automated pulmonary function test data mart within the Northwestern Medical Enterprise Data Warehouse was determined. Results There was a near perfect (99.5% agreement between results generated from the Regextractor package and those obtained via manual chart abstraction. The pulmonary function test data mart has been used subsequently to monitor disease progression of patients in the Northwestern Scleroderma Registry. In addition to the pulmonary function test example presented in this manuscript, the Regextractor package has been used to create cardiac catheterization and echocardiography data marts. The Regextractor package was released as open source software in October 2009 and has been downloaded 552 times as of 6/1/2012. Conclusions Collaboration between clinical researchers and biomedical informatics experts enabled the development and validation of a tool (Regextractor to parse, abstract and assemble

  13. Background field removal technique using regularization enabled sophisticated harmonic artifact reduction for phase data with varying kernel sizes.

    Science.gov (United States)

    Kan, Hirohito; Kasai, Harumasa; Arai, Nobuyuki; Kunitomo, Hiroshi; Hirose, Yasujiro; Shibamoto, Yuta

    2016-09-01

    An effective background field removal technique is desired for more accurate quantitative susceptibility mapping (QSM) prior to dipole inversion. The aim of this study was to evaluate the accuracy of regularization enabled sophisticated harmonic artifact reduction for phase data with varying spherical kernel sizes (REV-SHARP) method using a three-dimensional head phantom and human brain data. The proposed REV-SHARP method used the spherical mean value operation and Tikhonov regularization in the deconvolution process, with varying 2-14mm kernel sizes. The kernel sizes were gradually reduced, similar to the SHARP with varying spherical kernel (VSHARP) method. We determined the relative errors and relationships between the true local field and estimated local field in REV-SHARP, VSHARP, projection onto dipole fields (PDF), and regularization enabled SHARP (RESHARP). Human experiment was also conducted using REV-SHARP, VSHARP, PDF, and RESHARP. The relative errors in the numerical phantom study were 0.386, 0.448, 0.838, and 0.452 for REV-SHARP, VSHARP, PDF, and RESHARP. REV-SHARP result exhibited the highest correlation between the true local field and estimated local field. The linear regression slopes were 1.005, 1.124, 0.988, and 0.536 for REV-SHARP, VSHARP, PDF, and RESHARP in regions of interest on the three-dimensional head phantom. In human experiments, no obvious errors due to artifacts were present in REV-SHARP. The proposed REV-SHARP is a new method combined with variable spherical kernel size and Tikhonov regularization. This technique might make it possible to be more accurate backgroud field removal and help to achive better accuracy of QSM. Copyright © 2016 Elsevier Inc. All rights reserved.

  14. Herbarium data: Global biodiversity and societal botanical needs for novel research.

    Science.gov (United States)

    James, Shelley A; Soltis, Pamela S; Belbin, Lee; Chapman, Arthur D; Nelson, Gil; Paul, Deborah L; Collins, Matthew

    2018-02-01

    Building on centuries of research based on herbarium specimens gathered through time and around the globe, a new era of discovery, synthesis, and prediction using digitized collections data has begun. This paper provides an overview of how aggregated, open access botanical and associated biological, environmental, and ecological data sets, from genes to the ecosystem, can be used to document the impacts of global change on communities, organisms, and society; predict future impacts; and help to drive the remediation of change. Advocacy for botanical collections and their expansion is needed, including ongoing digitization and online publishing. The addition of non-traditional digitized data fields, user annotation capability, and born-digital field data collection enables the rapid access of rich, digitally available data sets for research, education, informed decision-making, and other scholarly and creative activities. Researchers are receiving enormous benefits from data aggregators including the Global Biodiversity Information Facility (GBIF), Integrated Digitized Biocollections (iDigBio), the Atlas of Living Australia (ALA), and the Biodiversity Heritage Library (BHL), but effective collaboration around data infrastructures is needed when working with large and disparate data sets. Tools for data discovery, visualization, analysis, and skills training are increasingly important for inspiring novel research that improves the intrinsic value of physical and digital botanical collections.

  15. Integrating Multiple Types of Data for Signaling Research: Challenges and Opportunities

    Energy Technology Data Exchange (ETDEWEB)

    Wiley, H. S.

    2011-02-15

    New technologies promise to provide unprecedented amounts of information that can provide a foundation for creating predictive models of cell signaling pathways. To be useful, however, this information must be integrated into a coherent framework. In addition, the sheer volume of data gathered from the new technologies requires computational approaches for its analysis. Unfortunately, there are many barriers to data integration and analysis, mostly because of a lack of adequate data standards and their inconsistent use by scientists. However, solving the fundamental issues of data sharing will enable the investigation of entirely new areas of cell signaling research.

  16. Linking Hospital and Tax data to support research on the economic impacts of hospitalization

    Directory of Open Access Journals (Sweden)

    Claudia Sanmartin

    2017-04-01

    This project has created a unique linked database that will support research on the economic consequences of ‘health shocks’ for individuals and their families, and the implications for income, labour and health policies. This database represents a new and unique resource that will fill an important national data gap, and enable a wide range of relevant research.

  17. 1H-detected MAS solid-state NMR experiments enable the simultaneous mapping of rigid and dynamic domains of membrane proteins

    Science.gov (United States)

    Gopinath, T.; Nelson, Sarah E. D.; Veglia, Gianluigi

    2017-12-01

    Magic angle spinning (MAS) solid-state NMR (ssNMR) spectroscopy is emerging as a unique method for the atomic resolution structure determination of native membrane proteins in lipid bilayers. Although 13C-detected ssNMR experiments continue to play a major role, recent technological developments have made it possible to carry out 1H-detected experiments, boosting both sensitivity and resolution. Here, we describe a new set of 1H-detected hybrid pulse sequences that combine through-bond and through-space correlation elements into single experiments, enabling the simultaneous detection of rigid and dynamic domains of membrane proteins. As proof-of-principle, we applied these new pulse sequences to the membrane protein phospholamban (PLN) reconstituted in lipid bilayers under moderate MAS conditions. The cross-polarization (CP) based elements enabled the detection of the relatively immobile residues of PLN in the transmembrane domain using through-space correlations; whereas the most dynamic region, which is in equilibrium between folded and unfolded states, was mapped by through-bond INEPT-based elements. These new 1H-detected experiments will enable one to detect not only the most populated (ground) states of biomacromolecules, but also sparsely populated high-energy (excited) states for a complete characterization of protein free energy landscapes.

  18. The Ophidia Stack: Toward Large Scale, Big Data Analytics Experiments for Climate Change

    Science.gov (United States)

    Fiore, S.; Williams, D. N.; D'Anca, A.; Nassisi, P.; Aloisio, G.

    2015-12-01

    The Ophidia project is a research effort on big data analytics facing scientific data analysis challenges in multiple domains (e.g. climate change). It provides a "datacube-oriented" framework responsible for atomically processing and manipulating scientific datasets, by providing a common way to run distributive tasks on large set of data fragments (chunks). Ophidia provides declarative, server-side, and parallel data analysis, jointly with an internal storage model able to efficiently deal with multidimensional data and a hierarchical data organization to manage large data volumes. The project relies on a strong background on high performance database management and On-Line Analytical Processing (OLAP) systems to manage large scientific datasets. The Ophidia analytics platform provides several data operators to manipulate datacubes (about 50), and array-based primitives (more than 100) to perform data analysis on large scientific data arrays. To address interoperability, Ophidia provides multiple server interfaces (e.g. OGC-WPS). From a client standpoint, a Python interface enables the exploitation of the framework into Python-based eco-systems/applications (e.g. IPython) and the straightforward adoption of a strong set of related libraries (e.g. SciPy, NumPy). The talk will highlight a key feature of the Ophidia framework stack: the "Analytics Workflow Management System" (AWfMS). The Ophidia AWfMS coordinates, orchestrates, optimises and monitors the execution of multiple scientific data analytics and visualization tasks, thus supporting "complex analytics experiments". Some real use cases related to the CMIP5 experiment will be discussed. In particular, with regard to the "Climate models intercomparison data analysis" case study proposed in the EU H2020 INDIGO-DataCloud project, workflows related to (i) anomalies, (ii) trend, and (iii) climate change signal analysis will be presented. Such workflows will be distributed across multiple sites - according to the

  19. How Elsevier is supporting the value and usefulness of data with Cross-linking and Research Data Services.

    Science.gov (United States)

    Keall, Bethan; Koers, Hylke; Marques, David

    2013-04-01

    right. We are working on several initiatives at Elsevier that enhance the online article format, and to make it easier for researchers to share, find, access, link together and analyze relevant research data. This helps to increase the value of both articles and data, and enables researchers to gain full credit for their research data output.

  20. TSTA Piping and Flame Arrestor Operating Experience Data

    Energy Technology Data Exchange (ETDEWEB)

    Cadwallader, Lee C.; Willms, R. Scott

    2014-10-01

    The Tritium Systems Test Assembly (TSTA) was a facility dedicated to tritium handling technology and experiment research at the Los Alamos National Laboratory. The facility operated from 1984 to 2001, running a prototype fusion fuel processing loop with ~100 grams of tritium as well as small experiments. There have been several operating experience reports written on this facility’s operation and maintenance experience. This paper describes analysis of two additional components from TSTA, small diameter gas piping that handled small amounts of tritium in a nitrogen carrier gas, and the flame arrestor used in this piping system. The operating experiences and the component failure rates for these components are discussed in this paper. Comparison data from other applications are also presented.

  1. Enabling Spatial OLAP Over Environmental and Farming Data with QB4SOLAP

    DEFF Research Database (Denmark)

    Gur, Nurefsan; Hose, Katja; Pedersen, Torben Bach

    2016-01-01

    Governmental organizations and agencies have been making large amounts of spatial data available on the Semantic Web (SW). However, we still lack efficient techniques for analyzing such large amounts of data as we know them from relational database systems, e.g., multidimensional (MD) data...... warehouses and On-line Analytical Processing (OLAP). A basic prerequisite to enable such advanced analytics is a well-defined schema, which can be defined using the QB4SOLAP vocabulary that provides sufficient context for spatial OLAP (SOLAP). In this paper, we address the challenging problem of MD querying...

  2. SPRUCE experiment data infrastructure

    Science.gov (United States)

    Krassovski, M.; Hanson, P. J.; Boden, T.; Riggs, J.; Nettles, W. R.; Hook, L. A.

    2013-12-01

    The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL), USA has provided scientific data management support for the US Department of Energy and international climate change science since 1982. Among the many data activities CDIAC performs are design and implementation of the data systems. One current example is the data system and network for SPRUCE experiment. The SPRUCE experiment (http://mnspruce.ornl.gov) is the primary component of the Terrestrial Ecosystem Science Scientific Focus Area of ORNL's Climate Change Program, focused on terrestrial ecosystems and the mechanisms that underlie their responses to climatic change. The experimental work is to be conducted in a bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF). The site is located at the southern margin of the boreal peatland forest. Experimental work in the 8.1-ha S1 bog will be a climate change manipulation focusing on the combined responses to multiple levels of warming at ambient or elevated CO2 (eCO2) levels. The experiment provides a platform for testing mechanisms controlling the vulnerability of organisms, biogeochemical processes and ecosystems to climatic change (e.g., thresholds for organism decline or mortality, limitations to regeneration, biogeochemical limitations to productivity, the cycling and release of CO2 and CH4 to the atmosphere). The manipulation will evaluate the response of the existing biological communities to a range of warming levels from ambient to +9°C, provided via large, modified open-top chambers. The ambient and +9°C warming treatments will also be conducted at eCO2 (in the range of 800 to 900 ppm). Both direct and indirect effects of these experimental perturbations will be analyzed to develop and refine models needed for full Earth system analyses. SPRUCE provides wide range continuous and discrete measurements. To successfully manage SPRUCE data flow

  3. Dialectical Inquiry--Does It Deliver? A User Based Research Experience

    Science.gov (United States)

    Seligman, James

    2013-01-01

    Dialectical Enquiry (DI) as a research method was used in the study of customer/student experience and its management (CEM) in not for profit as higher education. The (DI) method is applied to senders, receivers of the customer experience across six English universities to gather real world data using an imposed dialectical structure and analysis.…

  4. CHOICE, PURCHASE AND CONSUMPTION OF DRUGS: SOCIOLOGICAL RESEARCH EXPERIENCE

    Directory of Open Access Journals (Sweden)

    Ольга Викторовна Ткаченко

    2013-09-01

    Full Text Available The results of pharmaceutical market’s sociological research are representing in the paper. Determinate the basic agents influenced on pharmaceuticals choice and purchase such as a doctor, experience of individual, information from advertisement. Physician competency is of secondary importance to advertisement messages. Experience of individual prepotency of the pharmaceuticals choice raises a point of a level attention of pharmaceuticals consumer behavior. We can describe it in a low level both base on respondents self-conception and in accordance with data research of drug’s advertisement and patient package inserts «content-analysis».DOI: http://dx.doi.org/10.12731/2218-7405-2013-6-53

  5. Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis.

    Science.gov (United States)

    Duarte, Afonso M S; Psomopoulos, Fotis E; Blanchet, Christophe; Bonvin, Alexandre M J J; Corpas, Manuel; Franc, Alain; Jimenez, Rafael C; de Lucas, Jesus M; Nyrönen, Tommi; Sipos, Gergely; Suhr, Stephanie B

    2015-01-01

    With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.

  6. In-space research, technology and engineering experiments and Space Station

    Science.gov (United States)

    Tyson, Richard; Gartrell, Charles F.

    1988-01-01

    The NASA Space Station will serve as a technology research laboratory, a payload-servicing facility, and a large structure fabrication and assembly facility. Space structures research will encompass advanced structural concepts and their dynamics, advanced control concepts, sensors, and actuators. Experiments dealing with fluid management will gather data on such fundamentals as multiphase flow phenomena. As requirements for power systems and thermal management grow, experiments quantifying the performance of energy systems and thermal management concepts will be undertaken, together with expanded efforts in the fields of information systems, automation, and robotics.

  7. Enabling High-performance Interactive Geoscience Data Analysis Through Data Placement and Movement Optimization

    Science.gov (United States)

    Zhu, F.; Yu, H.; Rilee, M. L.; Kuo, K. S.; Yu, L.; Pan, Y.; Jiang, H.

    2017-12-01

    Since the establishment of data archive centers and the standardization of file formats, scientists are required to search metadata catalogs for data needed and download the data files to their local machines to carry out data analysis. This approach has facilitated data discovery and access for decades, but it inevitably leads to data transfer from data archive centers to scientists' computers through low-bandwidth Internet connections. Data transfer becomes a major performance bottleneck in such an approach. Combined with generally constrained local compute/storage resources, they limit the extent of scientists' studies and deprive them of timely outcomes. Thus, this conventional approach is not scalable with respect to both the volume and variety of geoscience data. A much more viable solution is to couple analysis and storage systems to minimize data transfer. In our study, we compare loosely coupled approaches (exemplified by Spark and Hadoop) and tightly coupled approaches (exemplified by parallel distributed database management systems, e.g., SciDB). In particular, we investigate the optimization of data placement and movement to effectively tackle the variety challenge, and boost the popularization of parallelization to address the volume challenge. Our goal is to enable high-performance interactive analysis for a good portion of geoscience data analysis exercise. We show that tightly coupled approaches can concentrate data traffic between local storage systems and compute units, and thereby optimizing bandwidth utilization to achieve a better throughput. Based on our observations, we develop a geoscience data analysis system that tightly couples analysis engines with storages, which has direct access to the detailed map of data partition locations. Through an innovation data partitioning and distribution scheme, our system has demonstrated scalable and interactive performance in real-world geoscience data analysis applications.

  8. Implications and Benefits of a Long-Term Peer Debriefing Experience on Teacher Researchers

    OpenAIRE

    Cynthia Schneider; Christy Youker; Joanne Heilman; Melanie Wenrick; Candace Figg

    2010-01-01

    Peer debriefing ensures the trustworthiness of a qualitative research study. Through peer debriefing, the researcher explores the research design, data collection process, and data analysis while colleagues, serving as critical friends, encourage the researcher to examine the research process from multiple perspectives. This paper examines experiences in a peer debriefing group formed by five female teacher researchers as a part of their graduate requirements for doctoral work, and their cont...

  9. Automated Agricultural Field Extraction from Multi-temporal Web Enabled Landsat Data

    Science.gov (United States)

    Yan, L.; Roy, D. P.

    2012-12-01

    Agriculture has caused significant anthropogenic surface change. In many regions agricultural field sizes may be increasing to maximize yields and reduce costs resulting in decreased landscape spatial complexity and increased homogenization of land uses with potential for significant biogeochemical and ecological effects. To date, studies of the incidence, drivers and impacts of changing field sizes have not been undertaken over large areas because of computational constraints and because consistently processed appropriate resolution data have not been available or affordable. The Landsat series of satellites provides near-global coverage, long term, and appropriate spatial resolution (30m) satellite data to document changing field sizes. The recent free availability of all the Landsat data in the U.S. Landsat archive now provides the opportunity to study field size changes in a global and consistent way. Commercial software can be used to extract fields from Landsat data but are inappropriate for large area application because they require considerable human interaction. This paper presents research to develop and validate an automated computational Geographic Object Based Image Analysis methodology to extract agricultural fields and derive field sizes from Web Enabled Landsat Data (WELD) (http://weld.cr.usgs.gov/). WELD weekly products (30m reflectance and brightness temperature) are classified into Satellite Image Automatic Mapper™ (SIAM™) spectral categories and an edge intensity map and a map of the probability of each pixel being agricultural are derived from five years of 52 weeks of WELD and corresponding SIAM™ data. These data are fused to derive candidate agriculture field segments using a variational region-based geometric active contour model. Geometry-based algorithms are used to decompose connected segments belonging to multiple fields into coherent isolated field objects with a divide and conquer strategy to detect and merge partial circle

  10. Health Research Governance: Introduction of a New Web-based Research Evaluation Model in Iran: One-decade Experience

    Science.gov (United States)

    MALEKZADEH, Reza; AKHONDZADEH, Shahin; EBADIFAR, Asghar; BARADARAN EFTEKHARI, Monir; OWLIA, Parviz; GHANEI, Mostafa; FALAHAT, Katayoun; HABIBI, Elham; SOBHANI, Zahra; DJALALINIA, Shirin; PAYKARI, Niloofar; MOJARRAB, Shahnaz; ELTEMASI, Masoumeh; LAALI, Reza

    2016-01-01

    Background: Governance is one of the main functions of Health Research System (HRS) that consist of four essential elements such as setting up evaluation system. The goal of this study was to introduce a new web based research evaluation model in Iran. Methods: Based on main elements of governance, research indicators have been clarified and with cooperation of technical team, appropriate software was designed. Three main steps in this study consist of developing of mission-oriented program, creating enabling environment and set up Iran Research Medical Portal as a center for research evaluation. Results: Fifty-two universities of medical sciences in three types have been participated. After training the evaluation focal points in all of medical universities, access to data entry and uploading all of documents were provided. Regarding to mission – based program, the contribution of medical universities in knowledge production was 60% for type one, 31% for type two and 9% for type three. The research priorities based on Essential National Health Research (ENHR) approach and mosaic model were gathered from universities of medical sciences and aggregated to nine main areas as national health research priorities. Ethical committees were established in all of medical universities. Conclusion: Web based research evaluation model is a comprehensive and integrated system for data collection in research. This system is appropriate tool to national health research ranking. PMID:27957437

  11. Web enabled data management with DPM and LFC

    International Nuclear Information System (INIS)

    Alvarez Ayllon, Alejandro; Beche, Alexandre; Furano, Fabrizio; Hellmich, Martin; Keeble, Oliver; Brito Da Rocha, Ricardo

    2012-01-01

    The Disk Pool Manager (DPM) and LCG File Catalog (LFC) are two grid data management components currently used in production with more than 240 endpoints. Together with a set of grid client tools they give the users a unified view of their data, hiding most details concerning data location and access. Recently we've put a lot of effort in developing a reliable and high performance HTTP/WebDAV frontend to both our grid catalog and storage components, exposing the existing functionality to users accessing the services via standard clients - e.g. web browsers, curl - present in all operating systems, giving users a simple and straight-forward way of interaction. In addition, as other relevant grid storage components (like dCache) expose their data using the same protocol, for the first time we had the opportunity of attempting a unified view of all grid storage using HTTP. We describe the HTTP redirection mechanism used to integrate the grid catalog(s) with the multiple storage components, including details on some assumptions made to allow integration with other implementations. We describe the way we hide the details regarding site availability or catalog inconsistencies by switching the standard HTTP client automatically between multiple replicas. We also present measurements of access performance, and the relevant factors regarding replica selection - current throughput and load, geographic proximity, etc. Finally, we report on some additional work done to have this system as a viable alternative to GridFTP, providing multi-stream transfers and exploiting some additional features of WebDAV to enable third party copies - essential for managing data movements between storage systems - with equivalent performance.

  12. Event Recording Data Acquisition System and Experiment Data Management System for Neutron Experiments at MLF, J-PARC

    Science.gov (United States)

    Nakatani, T.; Inamura, Y.; Moriyama, K.; Ito, T.; Muto, S.; Otomo, T.

    Neutron scattering can be a powerful probe in the investigation of many phenomena in the materials and life sciences. The Materials and Life Science Experimental Facility (MLF) at the Japan Proton Accelerator Research Complex (J-PARC) is a leading center of experimental neutron science and boasts one of the most intense pulsed neutron sources in the world. The MLF currently has 18 experimental instruments in operation that support a wide variety of users from across a range of research fields. The instruments include optical elements, sample environment apparatus and detector systems that are controlled and monitored electronically throughout an experiment. Signals from these components and those from the neutron source are converted into a digital format by the data acquisition (DAQ) electronics and recorded as time-tagged event data in the DAQ computers using "DAQ-Middleware". Operating in event mode, the DAQ system produces extremely large data files (˜GB) under various measurement conditions. Simultaneously, the measurement meta-data indicating each measurement condition is recorded in XML format by the MLF control software framework "IROHA". These measurement event data and meta-data are collected in the MLF common storage and cataloged by the MLF Experimental Database (MLF EXP-DB) based on a commercial XML database. The system provides a web interface for users to manage and remotely analyze experimental data.

  13. Ames Life Science Data Archive: Translational Rodent Research at Ames

    Science.gov (United States)

    Wood, Alan E.; French, Alison J.; Ngaotheppitak, Ratana; Leung, Dorothy M.; Vargas, Roxana S.; Maese, Chris; Stewart, Helen

    2014-01-01

    The Life Science Data Archive (LSDA) office at Ames is responsible for collecting, curating, distributing and maintaining information pertaining to animal and plant experiments conducted in low earth orbit aboard various space vehicles from 1965 to present. The LSDA will soon be archiving data and tissues samples collected on the next generation of commercial vehicles; e.g., SpaceX & Cygnus Commercial Cargo Craft. To date over 375 rodent flight experiments with translational application have been archived by the Ames LSDA office. This knowledge base of fundamental research can be used to understand mechanisms that affect higher organisms in microgravity and help define additional research whose results could lead the way to closing gaps identified by the Human Research Program (HRP). This poster will highlight Ames contribution to the existing knowledge base and how the LSDA can be a resource to help answer the questions surrounding human health in long duration space exploration. In addition, it will illustrate how this body of knowledge was utilized to further our understanding of how space flight affects the human system and the ability to develop countermeasures that negate the deleterious effects of space flight. The Ames Life Sciences Data Archive (ALSDA) includes current descriptions of over 700 experiments conducted aboard the Shuttle, International Space Station (ISS), NASA/MIR, Bion/Cosmos, Gemini, Biosatellites, Apollo, Skylab, Russian Foton, and ground bed rest studies. Research areas cover Behavior and Performance, Bone and Calcium Physiology, Cardiovascular Physiology, Cell and Molecular Biology, Chronobiology, Developmental Biology, Endocrinology, Environmental Monitoring, Gastrointestinal Physiology, Hematology, Immunology, Life Support System, Metabolism and Nutrition, Microbiology, Muscle Physiology, Neurophysiology, Pharmacology, Plant Biology, Pulmonary Physiology, Radiation Biology, Renal, Fluid and Electrolyte Physiology, and Toxicology. These

  14. Data collection and field experiments at the Apache Leap research site. Annual report, May 1995--1996

    International Nuclear Information System (INIS)

    Woodhouse, E.G.; Bassett, R.L.; Neuman, S.P.; Chen, G.

    1997-08-01

    This report documents the research performed during the period May 1995-May 1996 for a project of the U.S. Regulatory Commission (sponsored contract NRC-04-090-051) by the University of Arizona. The project manager for this research in Thomas J. Nicholson, Office of Nuclear Regulatory Research. The objectives of this research were to examine hypotheses and test alternative conceptual models concerning unsaturated flow and transport through fractured rock, and to design and execute confirmatory field and laboratory experiments to test these hypotheses and conceptual models at the Apache Leap Research Site near Superior, Arizona. Each chapter in this report summarizes research related to a specific set of objectives and can be read and interpreted as a separate entity. Topics include: crosshole pneumatic and gaseous tracer field and modeling experiments designed to help validate the applicability of contiuum geostatistical and stochastic concepts, theories, models, and scaling relations relevant to unsaturated flow and transport in fractured porous tuffs; use of geochemistry and aquifer testing to evaluate fracture flow and perching mechanisms; investigations of 234 U/ 238 U fractionation to evaluate leaching selectivity; and transport and modeling of both conservative and non-conservative tracers

  15. TinyONet: A Cache-Based Sensor Network Bridge Enabling Sensing Data Reusability and Customized Wireless Sensor Network Services

    Science.gov (United States)

    Jung, Eui-Hyun; Park, Yong-Jin

    2008-01-01

    In recent years, a few protocol bridge research projects have been announced to enable a seamless integration of Wireless Sensor Networks (WSNs) with the TCP/IP network. These studies have ensured the transparent end-to-end communication between two network sides in the node-centric manner. Researchers expect this integration will trigger the development of various application domains. However, prior research projects have not fully explored some essential features for WSNs, especially the reusability of sensing data and the data-centric communication. To resolve these issues, we suggested a new protocol bridge system named TinyONet. In TinyONet, virtual sensors play roles as virtual counterparts of physical sensors and they dynamically group to make a functional entity, Slice. Instead of direct interaction with individual physical sensors, each sensor application uses its own WSN service provided by Slices. If a new kind of service is required in TinyONet, the corresponding function can be dynamically added at runtime. Beside the data-centric communication, it also supports the node-centric communication and the synchronous access. In order to show the effectiveness of the system, we implemented TinyONet on an embedded Linux machine and evaluated it with several experimental scenarios. PMID:27873968

  16. Using PIDs to Support the Full Research Data Publishing Lifecycle

    Science.gov (United States)

    Waard, A. D.

    2016-12-01

    Persistent identifiers can help support scientific research, track scientific impact and let researchers achieve recognition for their work. We discuss a number of ways in which Elsevier utilizes PIDs to support the scholarly lifecycle: To improve the process of storing and sharing data, Mendeley Data (http://data.mendeley.com) makes use of persistent identifiers to support the dynamic nature of data and software, by tracking and recording the provenance and versioning of datasets. This system now allows the comparison of different versions of a dataset, to see precisely what was changed during a versioning update. To present research data in context for the reader, we include PIDs in research articles as hyperlinks: https://www.elsevier.com/books-and-journals/content-innovation/data-base-linking. In some cases, PIDs fetch data files from the repositories provide that allow the embedding of visualizations, e.g. with PANGAEA and PubChem: https://www.elsevier.com/books-and-journals/content-innovation/protein-viewer; https://www.elsevier.com/books-and-journals/content-innovation/pubchem. To normalize referenced data elements, the Resource Identification Initiative - which we developed together with members of the Force11 RRID group - introduces a unified standard for resource identifiers (RRIDs) that can easily be interpreted by both humans and text mining tools. https://www.force11.org/group/resource-identification-initiative/update-resource-identification-initiative, as can be seen in our Antibody Data app: https://www.elsevier.com/books-and-journals/content-innovation/antibody-data To enable better citation practices and support robust metrics system for sharing research data, we have helped develop, and are early adopters of the Force11 Data Citation Principles and Implementation groups (https://www.force11.org/group/dcip) Lastly, through our work with the Research Data Alliance Publishing Data Services group, we helped create a set of guidelines (http

  17. Data management for interdisciplinary field experiments: OTTER project support

    Science.gov (United States)

    Angelici, Gary; Popovici, Lidia; Skiles, J. W.

    1993-01-01

    The ability of investigators of an interdisciplinary science project to properly manage the data that are collected during the experiment is critical to the effective conduct of science. When the project becomes large, possibly including several scenes of large-format remotely sensed imagery shared by many investigators requiring several services, the data management effort can involve extensive staff and computerized data inventories. The OTTER (Oregon Transect Ecosystem Research) project was supported by the PLDS (Pilot Land Data System) with several data management services, such as data inventory, certification, and publication. After a brief description of these services, experiences in providing them are compared with earlier data management efforts and some conclusions regarding data management in support of interdisciplinary science are discussed. In addition to providing these services, a major goal of this data management capability was to adopt characteristics of a pro-active attitude, such as flexibility and responsiveness, believed to be crucial for the effective conduct of active, interdisciplinary science. These are also itemized and compared with previous data management support activities. Identifying and improving these services and characteristics can lead to the design and implementation of optimal data management support capabilities, which can result in higher quality science and data products from future interdisciplinary field experiments.

  18. AGC-3 Experiment Irradiation Monitoring Data Qualification Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Laurence Hull

    2014-10-01

    The Graphite Technology Development Program will run a series of six experiments to quantify the effects of irradiation on nuclear grade graphite. The third experiment, Advanced Graphite Creep 3 (AGC 3), began with Advanced Test Reactor (ATR) Cycle 152B on November 27, 2012, and ended with ATR Cycle 155B on April 23, 2014. This report documents qualification of AGC 3 experiment irradiation monitoring data for use by the Very High Temperature Reactor (VHTR) Technology Development Office (TDO) Program for research and development activities required to design and license the first VHTR nuclear plant. Qualified data meet the requirements for data collection and use as described in the experiment planning and quality assurance documents. Failed data do not meet the requirements. Trend data may not meet the requirements, but may still provide some useable information. All thermocouples (TCs) functioned throughout the AGC 3 experiment. There was one interval between December 18, 2012, and December 20, 2012, where 10 NULL values were reported for various TCs. These NULL values were deleted from the Nuclear Data Management and Analysis System database. All temperature data are Qualified for use by the VHTR TDO Program. Argon, helium, and total gas flow data were within expected ranges and are Qualified for use by the VHTR TDO Program. Total gas flow was approximately 50 sccm through the AGC 3 experiment capsule. Helium gas flow was briefly increased to 100 sccm during ATR shutdowns. At the start of the AGC 3 experiment, moisture in the outflow gas line was stuck at a constant value of 335.6174 ppmv for the first cycle (Cycle 152B). When the AGC 3 experiment capsule was reinstalled in ATR for Cycle 154B, a new moisture filter was installed. Moisture data from Cycle 152B are Failed. All moisture data from the final three cycles (Cycles 154B, 155A, and 155B) are Qualified for use by the VHTR TDO Program.

  19. A Federated Network for Translational Cancer Research Using Clinical Data and Biospecimens.

    Science.gov (United States)

    Jacobson, Rebecca S; Becich, Michael J; Bollag, Roni J; Chavan, Girish; Corrigan, Julia; Dhir, Rajiv; Feldman, Michael D; Gaudioso, Carmelo; Legowski, Elizabeth; Maihle, Nita J; Mitchell, Kevin; Murphy, Monica; Sakthivel, Mayurapriyan; Tseytlin, Eugene; Weaver, JoEllen

    2015-12-15

    Advances in cancer research and personalized medicine will require significant new bridging infrastructures, including more robust biorepositories that link human tissue to clinical phenotypes and outcomes. In order to meet that challenge, four cancer centers formed the Text Information Extraction System (TIES) Cancer Research Network, a federated network that facilitates data and biospecimen sharing among member institutions. Member sites can access pathology data that are de-identified and processed with the TIES natural language processing system, which creates a repository of rich phenotype data linked to clinical biospecimens. TIES incorporates multiple security and privacy best practices that, combined with legal agreements, network policies, and procedures, enable regulatory compliance. The TIES Cancer Research Network now provides integrated access to investigators at all member institutions, where multiple investigator-driven pilot projects are underway. Examples of federated search across the network illustrate the potential impact on translational research, particularly for studies involving rare cancers, rare phenotypes, and specific biologic behaviors. The network satisfies several key desiderata including local control of data and credentialing, inclusion of rich phenotype information, and applicability to diverse research objectives. The TIES Cancer Research Network presents a model for a national data and biospecimen network. ©2015 American Association for Cancer Research.

  20. Processing techniques for data from the GKSS pressure suppression experiments

    International Nuclear Information System (INIS)

    Holman, G.S.; McCauley, E.W.

    1980-01-01

    This report describes techniques developed at LLNL for processing data from large-scale steam condensation experiments being performed by the GKSS Research Center in the Federal Republic of Germany. In particular, the computer code GKPLOT, a special evaluation program for generating time-history plots and numerical output files of GKSS data, will be discussed together with tape handling techniques to unblock the data to a form compatible with the LLNL octopus computer network. Using these data processing techniques, we have provided a convenient means of independently examining and analyzing a very extensive data base for steam condenstaion phenomena. In addition, the techniques developed for handling the GKSS data are applicable to the treatment of similar, but perhaps differently structured, experiment data sets

  1. Final Report: Archiving Data to Support Data Synthesis of DOE Sponsored Elevated CO2 Experiments

    Energy Technology Data Exchange (ETDEWEB)

    Megonigal, James [Smithsonian Environmental Research Center, Edgewater, MD (United States); Lu, Meng [Smithsonian Environmental Research Center, Edgewater, MD (United States)

    2017-09-05

    Over the last three decades DOE made a large investment in field-scale experiments in order to understand the role of terrestrial ecosystems in the global carbon cycle, and forecast how carbon cycling will change over the next century. The Smithsonian Environmental Research Center received one of the first awards in this program and managed two long-term studies (25 years and 10 years) with a total of approximately $10 million of support from DOE, and many more millions leveraged from the Smithsonian Institution and agencies such as NSF. The present DOE grant was based on the premise that such a large investment demands a proper synthesis effort so that the full potential of these experiments are realized through data analysis and modeling. The goal of the this grant was to archive legacy data from two major elevated carbon dioxide experiments in DOE databases, and to engage in synthesis activities using these data. Both goals were met. All datasets deemed a high priority for data synthesis and modeling were prepared for archiving and analysis. Many of these datasets were deposited in DOE’s CDIAC, while others are being held at the Oak Ridge National Lab and the Smithsonian Institution until they can be received by DOE’s new ESS-DIVE system at Berkeley Lab. Most of the effort was invested in researching and re-constituting high-quality data sets from a 30-year elevated CO2 experiment. Using these data, the grant produced products that are already benefiting climate change science, including the publication of new coastal wetland allometry equations based on 9,771 observations, public posting of dozens of datasets, metadata and supporting codes from long-term experiments at the Global Change Research Wetland, and publication of two synthetic data papers on scrub oak forest responses to elevated CO2. In addition, three papers are in review or nearing submission reporting unexpected long-term patterns in ecosystem responses to elevated CO

  2. Correlations between nuclear data and results of integral slab experiments. Case of hafnium

    International Nuclear Information System (INIS)

    Palau, J.M.

    1997-01-01

    The aim of this thesis was to evaluate how much integral slab experiments can both reduce discrepancies between experimental results and calculations, and improve the knowledge of hafnium isotopes neutronic parameters by an adapted sensitivity and uncertainty method. A statistical approach, based on the generalized least squares method and perturbation theory, has been incorporated into our calculation system in order to deduce microscopic cross-section adjustments from observed integral measurements on this particular 'mock-up' reactor. In this study it has been established that the correlations between integral parameters and hafnium capture cross-sections enable specific variations in the region of resolved resonances at the level of multigroup and punctual cross-sections recommended data (JEF-2.2 evaluation) to be highlighted. The use of determinist methods (APOLLO2 code) together with Monte Carlo- type simulations (TRIPOLI4 code) enabled a depth analysis of the modelling approximations to be carried out. Furthermore, the sensitivity coefficient validation technique employed leads to a reliable assessment of the quality of the new basic nuclear data. In this instance, the adjustments proposed for certain isotope 177 Hf resonance parameters reduce, after error propagation, by 3 to 5 per cent the difference between experimental results and calculations related to this absorbent's efficiency. Beyond this particular application, the qualification methodology integrated in our calculation system should enable other basic sizing parameters to be treated (chemical / geometric data or other unexplored nuclear data) to make technological requirements less stringent. (author)

  3. Data analysis method for plant experience feedback data bank

    International Nuclear Information System (INIS)

    Ployart, R.; Lannoy, A.

    1988-01-01

    French pressurized water reactors (PWRs) represent at the moment about fifty units, among which the oldest have been in operation for ten years. Furthermore, these PWRs developed according to a growth strategy of standardized plants and with a single plant operator are quite homogeneous in their design as well as in their operating and maintenance procedures. Lastly, the improvements brought about are usually passed on to the whole of the concerned standardized plant. In this context, the operating plant experience feedback data banks hold valuable information that starts being statistically significant. The reliability oriented methods are rather well known; the ones that enable to read out some information on performance and availability, susceptible to guide the plant operator in the decision making are less tested. It concerns changes of operating or maintenance procedure, or technical changes which could be decided from an assessment of the effects of previous changes, or by observing and explaining a posteriori natural evolutions in the behaviour of components. The method used within the framework of this report leads to reveal and explain singularities, correlations, regroupings and trends in the behaviour of the french PWRs

  4. Unsteady Aerodynamics Experiment Phases II-IV Test Configurations and Available Data Campaigns

    Energy Technology Data Exchange (ETDEWEB)

    Simms, D. A.; Hand, M. M.; Fingersh, L. J.; Jager, D. W.

    1999-08-19

    The main objective of the Unsteady Aerodynamics Experiment is to provide information needed to quantify the full-scale three-dimensional aerodynamic behavior of horizontal axis wind turbines. To accomplish this, an experimental wind turbine configured to meet specific research objectives was assembled and operated at the National Renewable Energy Laboratory (NREL). The turbine was instrumented to characterize rotating blade aerodynamic performance, machine structural responses, and atmospheric inflow conditions. Comprehensive tests were conducted with the turbine operating in an outdoor field environment under diverse conditions. Resulting data are used to validate aerodynamic and structural dynamics models which are an important part of wind turbine design and engineering codes. Improvements in these models are needed to better characterize aerodynamic response in both the steady-state post-stall and dynamic stall regimes. Much of the effort in the earlier phase of the Unsteady Aerodynamics Experiment focused on developing required data acquisition systems. Complex instrumentation and equipment was needed to meet stringent data requirements while operating under the harsh environmental conditions of a wind turbine rotor. Once the data systems were developed, subsequent phases of experiments were then conducted to collect data for use in answering specific research questions. A description of the experiment configuration used during Phases II-IV of the experiment is contained in this report.

  5. Unsteady Aerodynamics Experiment Phase V: Test Configuration and Available Data Campaigns; TOPICAL

    International Nuclear Information System (INIS)

    Hand, M. M.; Simms, D. A.; Fingersh, L. J.; Jager, D. W.; Cotrell, J. R.

    2001-01-01

    The main objective of the Unsteady Aerodynamics Experiment is to provide information needed to quantify the full-scale, three-dimensional, unsteady aerodynamic behavior of horizontal-axis wind turbines (HAWTs). To accomplish this, an experimental wind turbine configured to meet specific research objectives was assembled and operated at the National Renewable Energy Laboratory (NREL). The turbine was instrumented to characterize rotating-blade aerodynamic performance, machine structural responses, and atmospheric inflow conditions. Comprehensive tests were conducted with the turbine operating in an outdoor field environment under diverse conditions. Resulting data are used to validate aerodynamic and structural dynamics models, which are an important part of wind turbine design and engineering codes. Improvements in these models are needed to better characterize aerodynamic response in both the steady-state post-stall and dynamic-stall regimes. Much of the effort in the first phase of the Unsteady Aerodynamics Experiment focused on developing required data acquisition systems. Complex instrumentation and equipment was needed to meet stringent data requirements while operating under the harsh environmental conditions of a wind turbine rotor. Once the data systems were developed, subsequent phases of experiments were then conducted to collect data for use in answering specific research questions. A description of the experiment configuration used during Phase V of the experiment is contained in this report

  6. Open cyberGIS software for geospatial research and education in the big data era

    Science.gov (United States)

    Wang, Shaowen; Liu, Yan; Padmanabhan, Anand

    CyberGIS represents an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS), spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as new-generation GIS that enable unprecedented advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision-making. This paper describes three open software strategies-open access, source, and integration-to serve various research and education purposes of diverse geospatial communities. These strategies have been implemented in a leading-edge cyberGIS software environment through three corresponding software modalities: CyberGIS Gateway, Toolkit, and Middleware, and achieved broad and significant impacts.

  7. Open cyberGIS software for geospatial research and education in the big data era

    Directory of Open Access Journals (Sweden)

    Shaowen Wang

    2016-01-01

    Full Text Available CyberGIS represents an interdisciplinary field combining advanced cyberinfrastructure, geographic information science and systems (GIS, spatial analysis and modeling, and a number of geospatial domains to improve research productivity and enable scientific breakthroughs. It has emerged as new-generation GIS that enable unprecedented advances in data-driven knowledge discovery, visualization and visual analytics, and collaborative problem solving and decision-making. This paper describes three open software strategies–open access, source, and integration–to serve various research and education purposes of diverse geospatial communities. These strategies have been implemented in a leading-edge cyberGIS software environment through three corresponding software modalities: CyberGIS Gateway, Toolkit, and Middleware, and achieved broad and significant impacts.

  8. Enabling Grid Computing resources within the KM3NeT computing model

    Directory of Open Access Journals (Sweden)

    Filippidis Christos

    2016-01-01

    Full Text Available KM3NeT is a future European deep-sea research infrastructure hosting a new generation neutrino detectors that – located at the bottom of the Mediterranean Sea – will open a new window on the universe and answer fundamental questions both in particle physics and astrophysics. International collaborative scientific experiments, like KM3NeT, are generating datasets which are increasing exponentially in both complexity and volume, making their analysis, archival, and sharing one of the grand challenges of the 21st century. These experiments, in their majority, adopt computing models consisting of different Tiers with several computing centres and providing a specific set of services for the different steps of data processing such as detector calibration, simulation and data filtering, reconstruction and analysis. The computing requirements are extremely demanding and, usually, span from serial to multi-parallel or GPU-optimized jobs. The collaborative nature of these experiments demands very frequent WAN data transfers and data sharing among individuals and groups. In order to support the aforementioned demanding computing requirements we enabled Grid Computing resources, operated by EGI, within the KM3NeT computing model. In this study we describe our first advances in this field and the method for the KM3NeT users to utilize the EGI computing resources in a simulation-driven use-case.

  9. Facebook’s Emotional Contagion Experiment as a Challenge to Research Ethics

    Directory of Open Access Journals (Sweden)

    Jukka Jouhki

    2016-10-01

    Full Text Available This article analyzes the ethical discussion focusing on the Facebook emotional contagion experiment published by the Proceedings of the National Academy of Sciences in 2014. The massive-scale experiment manipulated the News Feeds of a large amount of Facebook users and was successful in proving that emotional contagion happens also in online environments. However, the experiment caused ethical concerns within and outside academia mainly for two intertwined reasons, the first revolving around the idea of research as manipulation, and the second focusing on the problematic definition of informed consent. The article concurs with recent research that the era of social media and big data research are posing a significant challenge to research ethics, the practice and views of which are grounded in the pre social media era, and reflect the classical ethical stances of utilitarianism and deontology.

  10. Researching the experience of kidney cancer patients.

    Science.gov (United States)

    Taylor, K

    2002-09-01

    The author's personal experience as a kidney cancer patient, researcher and founder of a kidney cancer support group forms the basis for consideration of the challenges involved in researching patients' experiences. The researcher needs to understand the variability of those experiences in both clinical and psychological-emotional terms, and in relation to the personal, familial and social contexts of the patient. It is also essential to define the purpose of the research and to show how an understanding of personal experiences of cancer can be used to enhance the quality of care for cancer patients. The research encounter with a patient is also in some respects a therapeutic encounter requiring a considerable degree of sensitivity on the part of the researcher. The person-centred approach of Carl Rogers is of value in supporting such an encounter.

  11. ChIPWig: a random access-enabling lossless and lossy compression method for ChIP-seq data.

    Science.gov (United States)

    Ravanmehr, Vida; Kim, Minji; Wang, Zhiying; Milenkovic, Olgica

    2018-03-15

    Chromatin immunoprecipitation sequencing (ChIP-seq) experiments are inexpensive and time-efficient, and result in massive datasets that introduce significant storage and maintenance challenges. To address the resulting Big Data problems, we propose a lossless and lossy compression framework specifically designed for ChIP-seq Wig data, termed ChIPWig. ChIPWig enables random access, summary statistics lookups and it is based on the asymptotic theory of optimal point density design for nonuniform quantizers. We tested the ChIPWig compressor on 10 ChIP-seq datasets generated by the ENCODE consortium. On average, lossless ChIPWig reduced the file sizes to merely 6% of the original, and offered 6-fold compression rate improvement compared to bigWig. The lossy feature further reduced file sizes 2-fold compared to the lossless mode, with little or no effects on peak calling and motif discovery using specialized NarrowPeaks methods. The compression and decompression speed rates are of the order of 0.2 sec/MB using general purpose computers. The source code and binaries are freely available for download at https://github.com/vidarmehr/ChIPWig-v2, implemented in C ++. milenkov@illinois.edu. Supplementary data are available at Bioinformatics online.

  12. Using Grounded Theory Method to Capture and Analyze Health Care Experiences

    Science.gov (United States)

    Foley, Geraldine; Timonen, Virpi

    2015-01-01

    Objective Grounded theory (GT) is an established qualitative research method, but few papers have encapsulated the benefits, limits, and basic tenets of doing GT research on user and provider experiences of health care services. GT can be used to guide the entire study method, or it can be applied at the data analysis stage only. Methods We summarize key components of GT and common GT procedures used by qualitative researchers in health care research. We draw on our experience of conducting a GT study on amyotrophic lateral sclerosis patients’ experiences of health care services. Findings We discuss why some approaches in GT research may work better than others, particularly when the focus of study is hard-to-reach population groups. We highlight the flexibility of procedures in GT to build theory about how people engage with health care services. Conclusion GT enables researchers to capture and understand health care experiences. GT methods are particularly valuable when the topic of interest has not previously been studied. GT can be applied to bring structure and rigor to the analysis of qualitative data. PMID:25523315

  13. Data base on nuclear power plant dose reduction research projects

    Energy Technology Data Exchange (ETDEWEB)

    Khan, T.A.; Dionne, B.J.; Baum, J.W.

    1985-12-01

    This report contains project information on the research and development activities of the nuclear power industry in the area of dose reduction. It is based on a data base of information set up at the ALARA Center of Brookhaven National Laboratory. One purpose of this report is to draw attention to work in progress and to enable researchers and subscribers to obtain further information from the investigators and project managers. Information is provided on 180 projects, divided according to whether they are oriented to Engineering Research or to Health Physics Technology. The report contains indices on main category, project manager, principal investigator, sponsoring organization, contracting organization, and subject. This is an initial report. It is intended that periodic updates be issued whenever sufficient material has been accumulated.

  14. Data base on nuclear power plant dose reduction research projects

    International Nuclear Information System (INIS)

    Khan, T.A.; Dionne, B.J.; Baum, J.W.

    1985-12-01

    This report contains project information on the research and development activities of the nuclear power industry in the area of dose reduction. It is based on a data base of information set up at the ALARA Center of Brookhaven National Laboratory. One purpose of this report is to draw attention to work in progress and to enable researchers and subscribers to obtain further information from the investigators and project managers. Information is provided on 180 projects, divided according to whether they are oriented to Engineering Research or to Health Physics Technology. The report contains indices on main category, project manager, principal investigator, sponsoring organization, contracting organization, and subject. This is an initial report. It is intended that periodic updates be issued whenever sufficient material has been accumulated

  15. The qualitative orientation in medical education research.

    Science.gov (United States)

    Cleland, Jennifer Anne

    2017-06-01

    Qualitative research is very important in educational research as it addresses the "how" and "why" research questions and enables deeper understanding of experiences, phenomena and context. Qualitative research allows you to ask questions that cannot be easily put into numbers to understand human experience. Getting at the everyday realities of some social phenomenon and studying important questions as they are really practiced helps extend knowledge and understanding. To do so, you need to understand the philosophical stance of qualitative research and work from this to develop the research question, study design, data collection methods and data analysis. In this article, I provide an overview of the assumptions underlying qualitative research and the role of the researcher in the qualitative process. I then go on to discuss the type of research objectives which are common in qualitative research, then introduce the main qualitative designs, data collection tools, and finally the basics of qualitative analysis. I introduce the criteria by which you can judge the quality of qualitative research. Many classic references are cited in this article, and I urge you to seek out some of these further reading to inform your qualitative research program.

  16. Curating research data

    DEFF Research Database (Denmark)

    Nielsen, Hans Jørn; Hjørland, Birger

    2014-01-01

    libraries may be the best place to select, keep, organize and use research data. To prepare for this task, research libraries should be actively involved in domain-specific analytic studies of their respective domains. Originality/value – This paper offers a theoretical analysis and clarification......Purpose – A key issue in the literature about research libraries concerns their potential role in managing research data. The aim of this paper is to study the arguments for and against associating this task with libraries and the impact such an association would have on information professionals......, and consider the competitors to libraries in this field. Design/methodology/approach – This paper considers the nature of data and discusses data typologies, the kinds of data contained within databases and the implications of criticisms of the data-information-knowledge (DIK) hierarchy. It outlines the many...

  17. Towards a research informed teaching experience within a diagnostic radiography curriculum: The level 4 (year 1) student holistic experience

    International Nuclear Information System (INIS)

    Higgins, Robert; Hogg, Peter; Robinson, Leslie

    2013-01-01

    Aim: This article discusses the level 4 (year 1) diagnostic radiography student holistic experience of the Research-informed Teaching experience (RiTe) at the University of Salford, UK. The purpose of RiTe is to expose undergraduate radiography students to more formal research, as part of their normal teaching and learning experience. Method: A grounded theory approach was adopted and a focus group with eight level 4 students was used to explore and evaluate the student experience and perception of RiTe. Results: Open coding defined categories and sub-categories, with axial and selective coding used to interrogate and explore the relationships between the focus group data. A number of insights were gained into the student holistic experience of RiTe. The issue of leadership for level 4 students was also identified. Discussion: The focus group participants found RiTe to be an extremely positive learning experience. RiTe also facilitated their translation of learnt theory into clinical skills knowledge alongside their understanding of and desire to participate in more research as undergraduates. The article also highlights areas for future research.

  18. Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

    Science.gov (United States)

    Kuo, Kwo-Sen; Seablom, Michael; Clune, Thomas; Ramachandran, Rahul

    2014-05-01

    A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code. We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higher-quality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the

  19. Anticipated Changes in Conducting Scientific Data-Analysis Research in the Big-Data Era

    Science.gov (United States)

    Kuo, Kwo-Sen; Seablom, Michael; Clune, Thomas; Ramachandran, Rahul

    2014-01-01

    A Big-Data environment is one that is capable of orchestrating quick-turnaround analyses involving large volumes of data for numerous simultaneous users. Based on our experiences with a prototype Big-Data analysis environment, we anticipate some important changes in research behaviors and processes while conducting scientific data-analysis research in the near future as such Big-Data environments become the mainstream. The first anticipated change will be the reduced effort and difficulty in most parts of the data management process. A Big-Data analysis environment is likely to house most of the data required for a particular research discipline along with appropriate analysis capabilities. This will reduce the need for researchers to download local copies of data. In turn, this also reduces the need for compute and storage procurement by individual researchers or groups, as well as associated maintenance and management afterwards. It is almost certain that Big-Data environments will require a different "programming language" to fully exploit the latent potential. In addition, the process of extending the environment to provide new analysis capabilities will likely be more involved than, say, compiling a piece of new or revised code.We thus anticipate that researchers will require support from dedicated organizations associated with the environment that are composed of professional software engineers and data scientists. A major benefit will likely be that such extensions are of higherquality and broader applicability than ad hoc changes by physical scientists. Another anticipated significant change is improved collaboration among the researchers using the same environment. Since the environment is homogeneous within itself, many barriers to collaboration are minimized or eliminated. For example, data and analysis algorithms can be seamlessly shared, reused and re-purposed. In conclusion, we will be able to achieve a new level of scientific productivity in the Big-Data

  20. Authentic Astronomy Research Experiences for Teachers: The NASA/IPAC Teacher Archive Research Program (NITARP)

    Science.gov (United States)

    Rebull, L. M.; Gorjian, V.; Squires, G.; Nitarp Team

    2012-08-01

    How many times have you gotten a question from the general public, or read a news story, and concluded that "they just don't understand how real science works?" One really good way to get the word out about how science works is to have more people experience the process of scientific research. Since 2004, the way we have chosen to do this is to provide authentic research experiences for teachers using real data (the program used to be called the Spitzer Teacher Program for Teachers and Students, which in 2009 was rechristened the NASA/IPAC Teacher Archive Research Program, or NITARP). We partner small groups of teachers with a mentor astronomer, they do research as a team, write up a poster, and present it at an American Astronomical Society (AAS) meeting. The teachers incorporate this experience into their classroom, and their experiences color their teaching for years to come, influencing hundreds of students per teacher. This program differs from other similar programs in several important ways. First, each team works on an original, unique project. There are no canned labs here! Second, each team presents their results in posters at the AAS, in science sessions (not outreach sessions). The posters are distributed throughout the meeting, in amongst other researchers' work; the participants are not "given a free pass" because they are teachers. Finally, the "product" of this project is the scientific result, not any sort of curriculum packet. The teachers adapt their project to their classroom environment, and we change the way they think about science and scientists.

  1. Authentic Astronomy Research Experiences for Teachers: the NASA/IPAC Teacher Archive Research Program (NITARP)

    Science.gov (United States)

    Rebull, L.; NITARP Team

    2011-12-01

    Since 2004, we have provided authentic astronomy research experiences for teachers using professional astronomical data. (The program used to be called the Spitzer Teacher Program for Teachers and Students, and in 2009 was renamed NITARP--NASA/IPAC Teacher Archive Research Program.) We partner small groups of teachers with a mentor astronomer, the team does research, writes up a poster, and presents it at the major annual meeting for professional US astronomers, the American Astronomical Society (winter meeting). The teachers incorporate this research experience into their classroom, and their experiences color their teaching for years to come, influencing hundreds of students per teacher. This program, to the best of our knowledge, is completely unique in the following three ways: (1) Each team does original research using real astronomical data, not canned labs or reproductions of previously done research. (2) Each team writes up the results of their research and presents it at an AAS meeting. Each team also presents the educational results of their experience. (3) The 'products' of the program are primarily the scientific results, as opposed to curriculum packets. The teachers in the program involve students at their school and incorporate the experience into their teaching in a way that works for them, their environment, and their local/state standards. The educators in the program are selected from a nationwide annual application process, and they get three trips, all reasonable expenses paid. First, they attend a winter AAS meeting to get their bearings as attendees of the largest professional astronomy meetings in the world. We sponsor a kickoff workshop specifically for the NITARP educators on the day before the AAS meeting starts. After the meeting, they work remotely with their team to write a proposal, as well as read background literature. In the summer (at a time convenient to all team members), the educators plus up to two students per teacher come

  2. AAS WorldWide Telescope: A Seamless, Cross-platform Data Visualization Engine for Astronomy Research, Education, and Democratizing Data

    Science.gov (United States)

    Rosenfield, Philip; Fay, Jonathan; Gilchrist, Ronald K.; Cui, Chenzhou; Weigel, A. David; Robitaille, Thomas; Otor, Oderah Justin; Goodman, Alyssa

    2018-05-01

    The American Astronomical Society’s WorldWide Telescope (WWT) project enables terabytes of astronomical images, data, and stories to be viewed and shared among researchers, exhibited in science museums, projected into full-dome immersive planetariums and virtual reality headsets, and taught in classrooms, from middle school to college. We review the WWT ecosystem, how WWT has been used in the astronomical community, and comment on future directions.

  3. The IRIS Data Management Center: Enabling Access to Observational Time Series Spanning Decades

    Science.gov (United States)

    Ahern, T.; Benson, R.; Trabant, C.

    2009-04-01

    are of acceptably high quality. The formats and data structures used by the seismological community are esoteric. IRIS and its FDSN partners are developing web services that can transform the data holdings to structures that are more easily used by broader scientific communities. For instance, atmospheric scientists are interested in using global observations of microbarograph data but that community does not understand the methods of applying instrument corrections to the observations. Web processing services under development at IRIS will transform these data in a manner that allows direct use within such analysis tools as MATLAB® already in use by that community. By continuing to develop web-service based methods of data discovery and access, IRIS is enabling broader access to its data holdings. We currently support data discovery using many of the Open Geospatial Consortium (OGC) web mapping services. We are involved in portal technologies to support data discovery and distribution for all data from the EarthScope project. We are working with computer scientists at several universities including the University of Washington as part of a DataNet proposal and we intend to enhance metadata, further develop ontologies, develop a Registry Service to aid in the discovery of data sets and services, and in general improve the semantic interoperability of the data managed at the IRIS DMC. Finally IRIS has been identified as one of four scientific organizations that the External Research Division of Microsoft wants to work with in the development of web services and specifically with the development of a scientific workflow engine. More specific details of current and future developments at the IRIS DMC will be included in this presentation.

  4. A midas plugin to enable construction of reproducible web-based image processing pipelines.

    Science.gov (United States)

    Grauer, Michael; Reynolds, Patrick; Hoogstoel, Marion; Budin, Francois; Styner, Martin A; Oguz, Ipek

    2013-01-01

    Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based User Interface, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI) of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

  5. A Midas Plugin to Enable Construction of Reproducible Web-based Image Processing Pipelines

    Directory of Open Access Journals (Sweden)

    Michael eGrauer

    2013-12-01

    Full Text Available Image processing is an important quantitative technique for neuroscience researchers, but difficult for those who lack experience in the field. In this paper we present a web-based platform that allows an expert to create a brain image processing pipeline, enabling execution of that pipeline even by those biomedical researchers with limited image processing knowledge. These tools are implemented as a plugin for Midas, an open-source toolkit for creating web based scientific data storage and processing platforms. Using this plugin, an image processing expert can construct a pipeline, create a web-based UI, manage jobs, and visualize intermediate results. Pipelines are executed on a grid computing platform using BatchMake and HTCondor. This represents a new capability for biomedical researchers and offers an innovative platform for scientific collaboration. Current tools work well, but can be inaccessible for those lacking image processing expertise. Using this plugin, researchers in collaboration with image processing experts can create workflows with reasonable default settings and streamlined user interfaces, and data can be processed easily from a lab environment without the need for a powerful desktop computer. This platform allows simplified troubleshooting, centralized maintenance, and easy data sharing with collaborators. These capabilities enable reproducible science by sharing datasets and processing pipelines between collaborators. In this paper, we present a description of this innovative Midas plugin, along with results obtained from building and executing several ITK based image processing workflows for diffusion weighted MRI (DW MRI of rodent brain images, as well as recommendations for building automated image processing pipelines. Although the particular image processing pipelines developed were focused on rodent brain MRI, the presented plugin can be used to support any executable or script-based pipeline.

  6. Forging New Service Paths: Institutional Approaches to Providing Research Data Management Services

    Directory of Open Access Journals (Sweden)

    Regina Raboin

    2012-01-01

    Full Text Available Objective: This paper describes three different institutional experiences in developing research data management programs and services, challenges/opportunities and lessons learned.Overview: This paper is based on the Librarian Panel Discussion during the 4th Annual University of Massachusetts and New England Region e-Science Symposium. Librarians representing large public and private research universities presented an overview of service models developed at their respective organizations to bring support for data management and eScience to their communities. The approaches described include two library-based, integrated service models and one collaboratively-staffed, center-based service model.Results: Three institutions describe their experiences in creating the organizational capacity for research data management support services. Although each institutional approach is unique, common challenges include garnering administrative support, managing the integration of services with new or existing staff structures, and continuing to meet researchers needs as they evolve.Conclusions: There is no one way to provide research data management services, but any staff position, committee, or formalized center reflects an overarching organizational commitment to data management support.

  7. Teacher Research Experience Programs = Increase in Student Achievement

    Science.gov (United States)

    Dubner, J.

    2010-12-01

    Columbia University's Summer Research Program for Science Teachers (SRP), founded in 1990, is one of the largest, best known university-based professional development programs for science teachers in the U.S. The program’s basic premise is simple: teachers cannot effectively teach science if they have not experienced it firsthand. For eight weeks in each of two consecutive summers, teachers participate as a member of a research team, led by a member of Columbia University’s research faculty. In addition to the laboratory experience, all teachers meet as a group one day each week during the summer for a series of pedagogical activities. A unique quality of the Summer Research Program is its focus on objective assessment of its impact on attitudes and instructional practices of participating teachers, on the performance of these teachers in their mentors’ laboratories, and most importantly, on the impact of their participation in the program on student interest and performance in science. SRP uses pass rate on the New York State Regents standardized science examinations as an objective measure of student achievement. SRP's data is the first scientific evidence of a connection between a research experience for teachers program and gains in student achievement. As a result of the research, findings were published in Science Magazine. The author will present an overview of Columbia's teacher research program and the results of the published program evaluation.

  8. New Content Addressable Memory (CAM) Technologies for Big Data and Intelligent Electronics Enabled by Magneto-Electric Ternary CAM

    Science.gov (United States)

    2017-12-11

    AFRL-RY-WP-TR-2017-0198 NEW CONTENT ADDRESSABLE MEMORY (CAM) TECHNOLOGIES FOR BIG DATA AND INTELLIGENT ELECTRONICS ENABLED BY MAGNETO-ELECTRIC...MEMORY (CAM) TECHNOLOGIES FOR BIG DATA AND INTELLIGENT ELECTRONICS ENABLED BY MAGNETO-ELECTRIC TERNARY CAM 5a. CONTRACT NUMBER FA8650-16-1-7655 5b... electronic applications, such as internet of things, big data, wireless sensors, and mobile devices, have begun to focus on the importance of energy

  9. Results from the Data & Democracy initiative to enhance community-based organization data and research capacity.

    Science.gov (United States)

    Carroll-Scott, Amy; Toy, Peggy; Wyn, Roberta; Zane, Jazmin I; Wallace, Steven P

    2012-07-01

    In an era of community-based participatory research and increased expectations for evidence-based practice, we evaluated an initiative designed to increase community-based organizations' data and research capacity through a 3-day train-the-trainer course on community health assessments. We employed a mixed method pre-post course evaluation design. Various data sources collected from 171 participants captured individual and organizational characteristics and pre-post course self-efficacy on 19 core skills, as well as behavior change 1 year later among a subsample of participants. Before the course, participants reported limited previous experience with data and low self-efficacy in basic research skills. Immediately after the course, participants demonstrated statistically significant increases in data and research self-efficacy. The subsample reported application of community assessment skills to their work and increased use of data 1 year later. Results suggest that an intensive, short-term training program can achieve large immediate gains in data and research self-efficacy in community-based organization staff. In addition, they demonstrate initial evidence of longer-term behavior change related to use of data and research skills to support their community work.

  10. GES DISC Datalist Enables Easy Data Selection For Natural Phenomena Studies

    Science.gov (United States)

    Li, Angela; Shie, Chung-Lin; Hegde, Mahabaleshwa; Petrenko, Maksym; Teng, William; Bryant, Keith; Liu, Zhong; Hearty, Thomas; Shen, Suhung; Seiler, Edward; hide

    2017-01-01

    In order to investigate and assess natural hazards such as tropical storms, winter storms, volcanic eruptions, floods, and drought in a timely manner, the NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) has been developing an efficient data search and access service. Called "Datalist," this service enables users to acquire their data of interest "all at once," with minimum effort. A Datalist is a virtual collection of predefined or user-defined data variables from one or more archived data sets. Datalists are more than just data. Datalists effectively provide users with a sophisticated integrated data and services package, including metadata, citation, documentation, visualization, and data-specific services (e.g., subset and OPeNDAP), all available from one-stop shopping. The predefined Datalists, created by the experienced GES DISC science support team, should save a significant amount of time that users would otherwise have to spend. The Datalist service is an extension of the new GES DISC website, which is completely data-driven. A Datalist, also known as "data bundle," is treated just as any other data set. Being a virtual collection, a Datalist requires no extra storage space.

  11. Decommissioning project feedback experience in the Japan Atomic Energy Research Institut

    International Nuclear Information System (INIS)

    Yanagihara, S.; Tachibana, M.; Miyajima, K.

    2003-01-01

    and to implement a decommissioning project in safe and economical manner. The Japan Power Demonstration Reactor (JPDR) decommissioning project was completed by March, 1996, accumulating various data, experience and know-how on dismantling activities. The data and project experience were analyzed for future decommissioning of commercial and research nuclear facilities, in which the lessons learnt are categorized into three groups: safety case, waste management and work efficiency. The feedback experience was good for planning and implementing decommissioning projects. This paper deals with the decommissioning projects and the feedback experience in JAERI. At present more than 20 research nuclear facilities are listed for decommissioning in the near future in JAERI, and some of the facilities are in dismantling stage. In addition, nearly 200 nuclear facilities will be decommissioned in JAERI and JNC for 80 years after unification of both research organizations. Consequently, it has been required to implement the decommissioning projects in safe and economical manner by effectively referring the past decommissioning experience. JPDR and JRTF decommissioning projects were set up as demonstration programs for future decommissioning of large nuclear facilities. The JPDR decommissioning project was completed successfully without serious problems, accumulating various data and know-how. The JRTF decommissioning project has also been in progress, in which the experience of JPDR dismantling activities are referred and various data and experience are collected to characterize the dismantling activities in fuel cycle facilities. In case of JRR-2 decommissioning project, it has been decided that the building will be used for a centralized fuel storage facility for the time before dismantling the core part. Various lessons learnt have been accumulated through these projects, including technology application, project management and organizational matters. The project data and the

  12. Limitations of Experiments in Education Research

    Science.gov (United States)

    Schanzenbach, Diane Whitmore

    2012-01-01

    Research based on randomized experiments (along with high-quality quasi-experiments) has gained traction in education circles in recent years. There is little doubt this has been driven in large part by the shift in research funding strategy by the Department of Education's Institute of Education Sciences under Grover Whitehurst's lead, described…

  13. Ultra-wideband real-time data acquisition in steady-state experiments

    International Nuclear Information System (INIS)

    Nakanishi, Hideya; Ohsuna, Masaki; Kojima, Mamoru; Nonomura, Miki; Emoto, Masahiko; Nagayama, Yoshio; Kawahata, Kazuo; Imazu, Setsuo; Okumura, Haruhiko

    2006-01-01

    The ultra-wideband real-time data acquisition (DAQ) system has started its operation at LHD steady-state experiments since 2004. It uses Compact PCI standard digitizers whose acquisition performance is continuously above 80 MB/s for each frontend, and is also capable of grabbing picture frames from high-resolution cameras. Near the end of the 8th LHD experimental period, it achieved a new world record of 84 GB/shot acquired data during about 4,000 s long-pulse discharge (no.56068). Numbers of real-time and batch DAQ were 15 and 30, respectively. To realize 80 MB/s streaming from the digitizer frontend to data storage and network clients, the acquired data are once buffered on the shared memory to be read by network streaming and data saving tasks independently. The former sends 1/N thinned stream by using a set of TCP and UDP sessions for every monitoring clients, and the latter saves raw data into a series of 10 s chunk files. Afterward, the subdivided segmental compression library 'titz' is applied in migrating them to the mass storage for enabling users to retrieve a smaller chunk of huge data. Different compression algorithms, zlib and JPEG-LS, are automatically applied for waveform picture and data, respectively. Newly made utilities and many improvements, such as acquisition status monitor, real-time waveform monitor, and 64 bit counting in digital timing system, have put the ultra-wideband acquisition system fit for practical use by entire stuff. Demonstrated technologies here could be applied for the next generation fusion experiment like ITER. (author)

  14. Data acquisition. GRAAL experiment. Hybrid reactor experiment. AMS experiment

    International Nuclear Information System (INIS)

    Barancourt, D.; Barbier, G.; Bosson, G.; Bouvier, J.; Gallin-Martel, L.; Meillon, B.; Stassi, P.; Tournier, M.

    1997-01-01

    The main activity of the data acquisition team has consisted in hardware and software developments for the GRAAL experiment with the trigger board, for the 'Reacteurs Hybrides' group with an acquisition board ADCVME8V and for the AMS experiment with the monitoring of the aerogel detector. (authors)

  15. PRIS-WEDAS. User’s Manual to the Web Enabled Data Acquisition System for PRIS

    International Nuclear Information System (INIS)

    2015-01-01

    The user manual for the Web Enabled Data Acquisition System (WEDAS), a system that supports the Power Reactor Information System (PRIS), provides instructions, guidelines and detailed definitions for each of the data items required for PRIS. The purpose of this manual is to ensure PRIS performance data are collected consistently and that the required quality of data collection is ensured. This PRIS-WEDAS user’s manual replaces reporting instructions published in the IAEA Technical Reports Series No. 428

  16. Mentoring health researchers globally: Diverse experiences, programmes, challenges and responses.

    Science.gov (United States)

    Cole, Donald C; Johnson, Nancy; Mejia, Raul; McCullough, Hazel; Turcotte-Tremblay, Anne-Marie; Barnoya, Joaquin; Falabella Luco, María Soledad

    2016-10-01

    Mentoring experiences and programmes are becoming increasingly recognised as important by those engaged in capacity strengthening in global health research. Using a primarily qualitative study design, we studied three experiences of mentorship and eight mentorship programmes for early career global health researchers based in high-income and low- and middle-income countries. For the latter, we drew upon programme materials, existing unpublished data and more formal mixed-method evaluations, supplemented by individual email questionnaire responses. Research team members wrote stories, and the team assembled and analysed them for key themes. Across the diverse experiences and programmes, key emergent themes included: great mentors inspire others in an inter-generational cascade, mentorship is transformative in personal and professional development and involves reciprocity, and finding the right balance in mentoring relationships and programmes includes responding creatively to failure. Among the challenges encountered were: struggling for more level playing fields for new health researchers globally, changing mindsets in institutions that do not have a culture of mentorship and building collaboration not competition. Mentoring networks spanning institutions and countries using multiple virtual and face-to-face methods are a potential avenue for fostering organisational cultures supporting quality mentorship in global health research.

  17. Enabling a systems biology knowledgebase with gaggle and firegoose

    Energy Technology Data Exchange (ETDEWEB)

    Baliga, Nitin S. [Institute for Systems Biology, Seattle, WA (United States)

    2014-12-12

    The overall goal of this project was to extend the existing Gaggle and Firegoose systems to develop an open-source technology that runs over the web and links desktop applications with many databases and software applications. This technology would enable researchers to incorporate workflows for data analysis that can be executed from this interface to other online applications. The four specific aims were to (1) provide one-click mapping of genes, proteins, and complexes across databases and species; (2) enable multiple simultaneous workflows; (3) expand sophisticated data analysis for online resources; and enhance open-source development of the Gaggle-Firegoose infrastructure. Gaggle is an open-source Java software system that integrates existing bioinformatics programs and data sources into a user-friendly, extensible environment to allow interactive exploration, visualization, and analysis of systems biology data. Firegoose is an extension to the Mozilla Firefox web browser that enables data transfer between websites and desktop tools including Gaggle. In the last phase of this funding period, we have made substantial progress on development and application of the Gaggle integration framework. We implemented the workspace to the Network Portal. Users can capture data from Firegoose and save them to the workspace. Users can create workflows to start multiple software components programmatically and pass data between them. Results of analysis can be saved to the cloud so that they can be easily restored on any machine. We also developed the Gaggle Chrome Goose, a plugin for the Google Chrome browser in tandem with an opencpu server in the Amazon EC2 cloud. This allows users to interactively perform data analysis on a single web page using the R packages deployed on the opencpu server. The cloud-based framework facilitates collaboration between researchers from multiple organizations. We have made a number of enhancements to the cmonkey2 application to enable and

  18. Librarians' Perspectives on the Factors Influencing Research Data Management Programs

    Science.gov (United States)

    Faniel, Ixchel M.; Connaway, Lynn Silipigni

    2018-01-01

    This qualitative research study examines librarians' research data management (RDM) experiences, specifically the factors that influence their ability to support researchers' needs. Findings from interviews with 36 academic library professionals in the United States identify 5 factors of influence: (1) technical resources; (2) human resources; (3)…

  19. Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

    Science.gov (United States)

    Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

    2012-06-08

    Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

  20. Research Data Alliance's Interest Group on "Weather, Climate and Air Quality"

    Science.gov (United States)

    Bretonnière, Pierre-Antoine; Benincasa, Francesco

    2016-04-01

    Research Data Alliance's Interest Group on "Weather, Climate and Air Quality" More than ever in the history of Earth sciences, scientists are confronted with the problem of dealing with huge amounts of data that grow continuously at a rate that becomes a challenge to process and analyse them using conventional methods. Data come from many different and widely distributed sources, ranging from satellite platforms and in-situ sensors to model simulations, and with different degrees of openness. How can Earth scientists deal with this diversity and big volume and extract useful information to understand and predict the relevant processes? The Research Data Alliance (RDA, https://rd-alliance.org/), an organization that promotes and develops new data policies, data standards and focuses on the development of new technical solutions applicable in many distinct areas of sciences, recently entered in its third phase. In this framework, an Interest Group (IG) comprised of community experts that are committed to directly or indirectly enable and facilitate data sharing, exchange, or interoperability in the fields of weather, climate and air quality has been created recently. Its aim is to explore and discuss the challenges for the use and efficient analysis of large and diverse datasets of relevance for these fields taking advantage of the knowledge generated and exchanged in RDA. At the same time, this IG intends to be a meeting point between members of the aforementioned communities to share experiences and propose new solutions to overcome the forthcoming challenges. Based on the collaboration between several research meteorological and European climate institutes, but also taking into account the input from the private (from the renewable energies, satellites and agriculture sectors for example) and public sectors, this IG will suggest practical and applicable solutions for Big Data issues, both at technological and policy level, encountered by these communities. We

  1. A Graduate Student's Experience and Perspective on a Student-Teacher-Researcher Partnership

    Science.gov (United States)

    Bostic, J.; Stylinski, C.; Doty, C.

    2017-12-01

    Teachers and their K-12 students lack firsthand experience in science research and often harbor misconceptions about science practices and the nature of science. To address this challenge, the NOAA-funded Student-Teacher-Researcher (STAR) partnership that provides rural high school students with authentic research experiences investigating the amount and sources of nitrate in schoolyard runoff. Teachers received training, guiding curricular materials aligned with NGSS and in-classroom support. With a focus on evidence-based reasoning skills, students actively participate in the research process through sample collection, data analysis, and an in-person discussion of conclusions and implications with our scientist team. As a member of this team, I assisted with refining the study design, analyzing nitrate isotope runoff samples, and sharing insights and feedback with students during the in-person discussion session. Assessment results indicate student gained an understanding of nitrate pollution and of science practices. As a graduate student, young scientist, and possessor of a B.S. in Science Education, I already recognized the value of involving K-12 students and teachers in authentic research experiences, as these experiences expose students to the nature of science while also improving content knowledge. During the STAR partnership, I learned firsthand some of the obstacles presented during outreach involving partnerships between a research institution and schools, such as inflexibility of school scheduling and the need for flexibility with research questions requiring complex lab analysis. Additionally, I discovered the challenge of working systemically across a school district, which can have broad impact but limit student experiences. Highlights of my experience included interactions with students and teachers, especially when students have unexpected answers to my questions, providing novel explanations for patterns observed in the data. Despite the

  2. Transforming the findings of narrative research into poetry.

    Science.gov (United States)

    Edwards, Sharon Lorraine

    2015-05-01

    To offer dramatic poetry as representing findings from narrative research that is more accessible. This article is drawn from the author's doctorate work on how students' stories about their 'clinical' experiences can aid learning. Nursing students' stories of clinical practice experiences when engaged in the care of patients represented as dramatic poetry. Qualitative analytical approaches in narrative data analysis to provide a review of student stories from a variety of perspectives. This article illustrates a method for converting story data to poetry. It suggests that a range of audiences can learn from nursing students' stories of clinical practice when translated into dramatic poetry. Audiences can come close to understanding what students are experiencing in practice when engaged in the care of patients and learning from their practice experiences, when these experiences are expressed as dramatic poetry. Representing findings from narrative research as dramatic poetry can help audiences engage with nursing students' experiences at an emotional level. Enabling researchers and readers to become immersed in the poem transforming their understanding of what the students have learned.

  3. 78 FR 65452 - Proposed Information Collection (Veterans, Researchers, and IRB Members Experiences With...

    Science.gov (United States)

    2013-10-31

    ... qualitative research methods to understand Veterans' preferences on research recruitment methods. The data... research study subjects and to explore Veterans views on recruitment procedures. DATES: Written comments... Members Experiences with Recruitment Restrictions). Type of Review: New collection. Abstracts: The VHA...

  4. Examining how youth of color engage youth participatory action research to interrogate racism in their science experiences

    Science.gov (United States)

    Sato, Takumi C.

    While many researchers have worked to address the unequal educational outcomes between White and non-White students, there are few signs of progress for people of color seeking entry into a STEM career trajectory. Starting from high school, the number of students who persist to complete a STEM bachelor's degree and obtaining a job in science or engineering continues to indicate that people of color are underrepresented. I suggest that research must consider the role of race and racism in the education of youth of color. Especially in science education, there is very little work addressing how racism may present barriers that impede progress for students along the STEM trajectory. This study is informed by critical race theory (CRT) that posits racism is endemic in society. White privilege enables the dominant group to maintain inequitable advantages that marginalizes populations of color. CRT also puts forth that counter narratives of the marginalized groups is essential to challenge the institutionalized forms of oppression. Using CRT and youth participatory action research (YPAR), this investigation re-imagines youth as capable of transforming their own social and political condition through research and action. This project asked youth of color to interrogate their own experiences as science learners, engage in research on structural inequities of STEM trajectories, plan strategic moves to challenge power structures, and take action for social justice. The youth started by exploring the concept of race and instances where racism was found in public spaces and in their personal experiences. They examined their experiences in science as a student more generally and then for racism. Then, the focus turned to conducting research with peers, observing science classrooms in another school, and using online information to compare schools. The youth planned strategic action against the racism they found in the analysis of the data that included conference presentations

  5. [Analysis of qualitative data collection methods used in adolescent research].

    Science.gov (United States)

    Ndengeyingoma, Assumpta; De Montigny, Francine; Miron, Jean-Marie

    2013-03-01

    There has been remarkable growth in research on adolescents in the last decade, particularly in nursing science. The goal of this article is to produce a synthesis of findings justifying the use of qualitative methods in collecting data from adolescents. A literature review identified relevant articles (N : 27) from digital databases. While the studies done on adolescents were on different topics, the data collection methods were often similar. Most of the studies used more than one technique to reconcile scientific rigour and the way the adolescents expressed themselves. In order to understand a phenomenon, its context and the meaning given to the experience proved essential. In qualitative research on adolescents, it is important to use data collection methods that make it possible to clearly target the experience explored and to orient and guide the individual in deepening that experience in order to favour the emergence of his or her point of view. Data collection methods based on written communication have to be complemented with other methods more focused on oral communication so as to draw out interpretations reflecting adolescents' points of view as accurately as possible.

  6. Feasibility of extracting data from electronic medical records for research: an international comparative study.

    Science.gov (United States)

    van Velthoven, Michelle Helena; Mastellos, Nikolaos; Majeed, Azeem; O'Donoghue, John; Car, Josip

    2016-07-13

    Electronic medical records (EMR) offer a major potential for secondary use of data for research which can improve the safety, quality and efficiency of healthcare. They also enable the measurement of disease burden at the population level. However, the extent to which this is feasible in different countries is not well known. This study aimed to: 1) assess information governance procedures for extracting data from EMR in 16 countries; and 2) explore the extent of EMR adoption and the quality and consistency of EMR data in 7 countries, using management of diabetes type 2 patients as an exemplar. We included 16 countries from Australia, Asia, the Middle East, and Europe to the Americas. We undertook a multi-method approach including both an online literature review and structured interviews with 59 stakeholders, including 25 physicians, 23 academics, 7 EMR providers, and 4 information commissioners. Data were analysed and synthesised thematically considering the most relevant issues. We found that procedures for information governance, levels of adoption and data quality varied across the countries studied. The required time and ease of obtaining approval also varies widely. While some countries seem ready for secondary uses of data from EMR, in other countries several barriers were found, including limited experience with using EMR data for research, lack of standard policies and procedures, bureaucracy, confidentiality, data security concerns, technical issues and costs. This is the first international comparative study to shed light on the feasibility of extracting EMR data across a number of countries. The study will inform future discussions and development of policies that aim to accelerate the adoption of EMR systems in high and middle income countries and seize the rich potential for secondary use of data arising from the use of EMR solutions.

  7. Genelab: Scientific Partnerships and an Open-Access Database to Maximize Usage of Omics Data from Space Biology Experiments

    Science.gov (United States)

    Reinsch, S. S.; Galazka, J..; Berrios, D. C; Chakravarty, K.; Fogle, H.; Lai, S.; Bokyo, V.; Timucin, L. R.; Tran, P.; Skidmore, M.

    2016-01-01

    NASA's mission includes expanding our understanding of biological systems to improve life on Earth and to enable long-duration human exploration of space. The GeneLab Data System (GLDS) is NASA's premier open-access omics data platform for biological experiments. GLDS houses standards-compliant, high-throughput sequencing and other omics data from spaceflight-relevant experiments. The GeneLab project at NASA-Ames Research Center is developing the database, and also partnering with spaceflight projects through sharing or augmentation of experiment samples to expand omics analyses on precious spaceflight samples. The partnerships ensure that the maximum amount of data is garnered from spaceflight experiments and made publically available as rapidly as possible via the GLDS. GLDS Version 1.0, went online in April 2015. Software updates and new data releases occur at least quarterly. As of October 2016, the GLDS contains 80 datasets and has search and download capabilities. Version 2.0 is slated for release in September of 2017 and will have expanded, integrated search capabilities leveraging other public omics databases (NCBI GEO, PRIDE, MG-RAST). Future versions in this multi-phase project will provide a collaborative platform for omics data analysis. Data from experiments that explore the biological effects of the spaceflight environment on a wide variety of model organisms are housed in the GLDS including data from rodents, invertebrates, plants and microbes. Human datasets are currently limited to those with anonymized data (e.g., from cultured cell lines). GeneLab ensures prompt release and open access to high-throughput genomics, transcriptomics, proteomics, and metabolomics data from spaceflight and ground-based simulations of microgravity, radiation or other space environment factors. The data are meticulously curated to assure that accurate experimental and sample processing metadata are included with each data set. GLDS download volumes indicate strong

  8. Operation experience of the Indonesian multipurpose research reactor RSG-GAS

    Energy Technology Data Exchange (ETDEWEB)

    Hastowo, Hudi; Tarigan, Alim [Multipurpose Reactor Center, National Nuclear Energy Agency of the Republic of Indonesia (PRSG-BATAN), Kawasan PUSPIPTEK Serpong, Tangerang (Indonesia)

    1999-08-01

    RSG-GAS is a multipurpose research reactor with nominal power of 30 MW, operated by BATAN since 1987. The reactor is an open pool type, cooled and moderated with light water, using the LEU-MTR fuel element in the form of U{sub 3}O{sub 8}-Al dispersion. Up to know, the reactor have been operated around 30,000 hours to serve the user. The reactor have been utilized to produce radioisotope, neutron beam experiments, irradiation of fuel element and its structural material, and reactor physics experiments. This report will explain in further detail concerning operational experience of this reactor, i.e. reactor operation data, reactor utilization, research program, technical problems and it solutions, plant modification and improvement, and development plan to enhance better reactor operation performance and its utilization. (author)

  9. Operation experience of the Indonesian multipurpose research reactor RSG-GAS

    International Nuclear Information System (INIS)

    Hastowo, Hudi; Tarigan, Alim

    1999-01-01

    RSG-GAS is a multipurpose research reactor with nominal power of 30 MW, operated by BATAN since 1987. The reactor is an open pool type, cooled and moderated with light water, using the LEU-MTR fuel element in the form of U 3 O 8 -Al dispersion. Up to know, the reactor have been operated around 30,000 hours to serve the user. The reactor have been utilized to produce radioisotope, neutron beam experiments, irradiation of fuel element and its structural material, and reactor physics experiments. This report will explain in further detail concerning operational experience of this reactor, i.e. reactor operation data, reactor utilization, research program, technical problems and it solutions, plant modification and improvement, and development plan to enhance better reactor operation performance and its utilization. (author)

  10. BDI: the Cadarache data bank for LMBFR integral experiment data

    International Nuclear Information System (INIS)

    Rimpault, G.; Reynaud, G.

    1986-09-01

    The Integral Data Bank is part of the procedure to create the so-called neutronic formulaire with which every design calculation is performed with associated uncertainty. A modern way to store the integral data has been set up in order to handle and recalculate easily with a standard procedure (fig. 1) each experimental programme. A direct access way to read the data allows an automatic way to obtain the calculation/experiment discrepancies associated with a particular data base. The BDI has proved to be fully operational and has been used with the new nuclear data file JEF1. In the present version of the BDI more than 140 experiments (critical mass, spectrum indexes, buckling, etc...) both from MASURCA and SNEAK critical experiments are documented and stored in an easy-to-retrieve from. Also included are irradiation experiments in PHENIX and the STEK fission product related experiments. Future plans of development concern reactivity measurements in critical assemblies, irradiation experiments and start-up experiments of SUPER PHENIX and ZEBRA critical experiments

  11. A linked GeoData map for enabling information access

    Science.gov (United States)

    Powell, Logan J.; Varanka, Dalia E.

    2018-01-10

    OverviewThe Geospatial Semantic Web (GSW) is an emerging technology that uses the Internet for more effective knowledge engineering and information extraction. Among the aims of the GSW are to structure the semantic specifications of data to reduce ambiguity and to link those data more efficiently. The data are stored as triples, the basic data unit in graph databases, which are similar to the vector data model of geographic information systems (GIS); that is, a node-edge-node model that forms a graph of semantically related information. The GSW is supported by emerging technologies such as linked geospatial data, described below, that enable it to store and manage geographical data that require new cartographic methods for visualization. This report describes a map that can interact with linked geospatial data using a simulation of a data query approach called the browsable graph to find information that is semantically related to a subject of interest, visualized using the Data Driven Documents (D3) library. Such a semantically enabled map functions as a map knowledge base (MKB) (Varanka and Usery, 2017).A MKB differs from a database in an important way. The central element of a triple, alternatively called the edge or property, is composed of a logic formalization that structures the relation between the first and third parts, the nodes or objects. Node-edge-node represents the graphic form of the triple, and the subject-property-object terms represent the data structure. Object classes connect to build a federated graph, similar to a network in visual form. Because the triple property is a logical statement (a predicate), the data graph represents logical propositions or assertions accepted to be true about the subject matter. These logical formalizations can be manipulated to calculate new triples, representing inferred logical assertions, from the existing data.To demonstrate a MKB system, a technical proof-of-concept is developed that uses geographically

  12. How can cloud processing enable generation of new knowledge through multidisciplinary research? The case of Co-ReSyF for coastal research

    Science.gov (United States)

    Politi, Eirini; Scarrott, Rory; Tuohy, Eimear; Terra Homem, Miguel; Caumont, Hervé; Grosso, Nuno; Mangin, Antoine; Catarino, Nuno

    2017-04-01

    advancing collaboration between different scientific communities. With core research applications currently ranging from bathymetry mapping to oil spill detection, sea level change and exploitation of data-rich time series to explore oceanic processes, the Co-ReSyF capabilities will be further enhanced by its users, who will be able to upload their own algorithms and processors onto the system. Co-ReSyF aims to address gaps and issues faced by remote sensing scientists and researchers, but also target non-remote sensing coastal experts, marine scientists and downstream users, with main focus on enabling Big Data access and processing for coastal and marine applications.

  13. Enabling Effective Problem-oriented Research for Sustainable Development

    Directory of Open Access Journals (Sweden)

    Christoph Kueffer

    2012-12-01

    -/transdisciplinary research practices into all teaching curricula. At the level of system innovation, we propose radical changes in institutional structures, research and career incentives, teaching programs, and research partnerships. We see much value in a view of change that emphasizes the complementarity of system innovation and system optimization. The goal must be a process of change that preserves the traditional strengths of academic research, with its emphasis on disciplinary excellence and scientific rigor, while ensuring that institutional environments and the skills, worldviews, and experiences of the involved actors adapt to the rapidly changing needs of society.

  14. Developing an occupational skills profile for the emerging profession of "big-data-enabled professional"

    Science.gov (United States)

    Kastens, K. A.; Malyn-Smith, J.; Ippolito, J.; Krumhansl, R.

    2014-12-01

    In August of 2014, the Oceans of Data Institute at Education Development Center, Inc. (EDC) is convening an expert panel to begin the process of developing an occupational skills profile for the "big-data-enabled professional." We define such a professional as an "individual who works with large complex data sets on a regular basis, asking and answering questions, analyzing trends, and finding meaningful patterns, in order to increase the efficiency of processes, make decisions and predictions, solve problems, generate hypotheses, and/or develop new understandings." The expert panel includes several geophysicists, as well as data professionals from engineering, higher education, analytical journalism, forensics, bioinformatics, and telecommunications. Working with experienced facilitators, the expert panel will create a detailed synopsis of the tasks and responsibilities characteristic of their profession, as well as the skills, knowledge and behaviors that enable them to succeed in the workplace. After the panel finishes their work, the task matrix and associated narrative will be vetted and validated by a larger group of additional professionals, and then disseminated for use by educators and employers. The process we are using is called DACUM (Developing a Curriculum), adapted by EDC and optimized for emergent professions, such as the "big-data-enabled professional." DACUM is a well-established method for analyzing jobs and occupations, commonly used in technical fields to develop curriculum and training programs that reflect authentic work tasks found in scientific and technical workplaces. The premises behind the DACUM approach are that: expert workers are better able to describe their own occupation than anyone else; any job can be described in terms of the tasks that successful workers in the occupation perform; all tasks have direct implications for the knowledge, skills, understandings and attitudes that must be taught and learned in preparation for the

  15. Big data and data repurposing - using existing data to answer new questions in vascular dementia research.

    Science.gov (United States)

    Doubal, Fergus N; Ali, Myzoon; Batty, G David; Charidimou, Andreas; Eriksdotter, Maria; Hofmann-Apitius, Martin; Kim, Yun-Hee; Levine, Deborah A; Mead, Gillian; Mucke, Hermann A M; Ritchie, Craig W; Roberts, Charlotte J; Russ, Tom C; Stewart, Robert; Whiteley, William; Quinn, Terence J

    2017-04-17

    Traditional approaches to clinical research have, as yet, failed to provide effective treatments for vascular dementia (VaD). Novel approaches to collation and synthesis of data may allow for time and cost efficient hypothesis generating and testing. These approaches may have particular utility in helping us understand and treat a complex condition such as VaD. We present an overview of new uses for existing data to progress VaD research. The overview is the result of consultation with various stakeholders, focused literature review and learning from the group's experience of successful approaches to data repurposing. In particular, we benefitted from the expert discussion and input of delegates at the 9 th International Congress on Vascular Dementia (Ljubljana, 16-18 th October 2015). We agreed on key areas that could be of relevance to VaD research: systematic review of existing studies; individual patient level analyses of existing trials and cohorts and linking electronic health record data to other datasets. We illustrated each theme with a case-study of an existing project that has utilised this approach. There are many opportunities for the VaD research community to make better use of existing data. The volume of potentially available data is increasing and the opportunities for using these resources to progress the VaD research agenda are exciting. Of course, these approaches come with inherent limitations and biases, as bigger datasets are not necessarily better datasets and maintaining rigour and critical analysis will be key to optimising data use.

  16. Integrating UNIX workstation into existing online data acquisition systems for Fermilab experiments

    International Nuclear Information System (INIS)

    Oleynik, G.

    1991-03-01

    With the availability of cost effective computing prior from multiple vendors of UNIX workstations, experiments at Fermilab are adding such computers to their VMS based online data acquisition systems. In anticipation of this trend, we have extended the software products available in our widely used VAXONLINE and PANDA data acquisition software systems, to provide support for integrating these workstations into existing distributed online systems. The software packages we are providing pave the way for the smooth migration of applications from the current Data Acquisition Host and Monitoring computers running the VMS operating systems, to UNIX based computers of various flavors. We report on software for Online Event Distribution from VAXONLINE and PANDA, integration of Message Reporting Facilities, and a framework under UNIX for experiments to monitor and view the raw event data produced at any level in their DA system. We have developed software that allows host UNIX computers to communicate with intelligent front-end embedded read-out controllers and processor boards running the pSOS operating system. Both RS-232 and Ethernet control paths are supported. This enables calibration and hardware monitoring applications to be migrated to these platforms. 6 refs., 5 figs

  17. The Interaction between Multimedia Data Analysis and Theory Development in Design Research

    Science.gov (United States)

    van Nes, Fenna; Doorman, Michiel

    2010-01-01

    Mathematics education researchers conducting instruction experiments using a design research methodology are challenged with the analysis of often complex and large amounts of qualitative data. In this paper, we present two case studies that show how multimedia analysis software can greatly support video data analysis and theory development in…

  18. The Index to Marine and Lacustrine Geological Samples: Improving Sample Accessibility and Enabling Current and Future Research

    Science.gov (United States)

    Moore, C.

    2011-12-01

    The Index to Marine and Lacustrine Geological Samples is a community designed and maintained resource enabling researchers to locate and request sea floor and lakebed geologic samples archived by partner institutions. Conceived in the dawn of the digital age by representatives from U.S. academic and government marine core repositories and the NOAA National Geophysical Data Center (NGDC) at a 1977 meeting convened by the National Science Foundation (NSF), the Index is based on core concepts of community oversight, common vocabularies, consistent metadata and a shared interface. Form and content of underlying vocabularies and metadata continue to evolve according to the needs of the community, as do supporting technologies and access methodologies. The Curators Consortium, now international in scope, meets at partner institutions biennially to share ideas and discuss best practices. NGDC serves the group by providing database access and maintenance, a list server, digitizing support and long-term archival of sample metadata, data and imagery. Over three decades, participating curators have performed the herculean task of creating and contributing metadata for over 195,000 sea floor and lakebed cores, grabs, and dredges archived in their collections. Some partners use the Index for primary web access to their collections while others use it to increase exposure of more in-depth institutional systems. The Index is currently a geospatially-enabled relational database, publicly accessible via Web Feature and Web Map Services, and text- and ArcGIS map-based web interfaces. To provide as much knowledge as possible about each sample, the Index includes curatorial contact information and links to related data, information and images; 1) at participating institutions, 2) in the NGDC archive, and 3) at sites such as the Rolling Deck to Repository (R2R) and the System for Earth Sample Registration (SESAR). Over 34,000 International GeoSample Numbers (IGSNs) linking to SESAR are

  19. A Semantic Cross-Species Derived Data Management Application

    Directory of Open Access Journals (Sweden)

    David B. Keator

    2017-09-01

    Full Text Available Managing dynamic information in large multi-site, multi-species, and multi-discipline consortia is a challenging task for data management applications. Often in academic research studies the goals for informatics teams are to build applications that provide extract-transform-load (ETL functionality to archive and catalog source data that has been collected by the research teams. In consortia that cross species and methodological or scientific domains, building interfaces which supply data in a usable fashion and make intuitive sense to scientists from dramatically different backgrounds increases the complexity for developers. Further, reusing source data from outside one’s scientific domain is fraught with ambiguities in understanding the data types, analysis methodologies, and how to combine the data with those from other research teams. We report on the design, implementation, and performance of a semantic data management application to support the NIMH funded Conte Center at the University of California, Irvine. The Center is testing a theory of the consequences of “fragmented” (unpredictable, high entropy early-life experiences on adolescent cognitive and emotional outcomes in both humans and rodents. It employs cross-species neuroimaging, epigenomic, molecular, and neuroanatomical approaches in humans and rodents to assess the potential consequences of fragmented unpredictable experience on brain structure and circuitry. To address this multi-technology, multi-species approach, the system uses semantic web techniques based on the Neuroimaging Data Model (NIDM to facilitate data ETL functionality. We find this approach enables a low-cost, easy to maintain, and semantically meaningful information management system, enabling the diverse research teams to access and use the data.

  20. Subsetting Tools for Enabling Easy Access to International Airborne Chemistry Data

    Science.gov (United States)

    Northup, E. A.; Chen, G.; Quam, B. M.; Beach, A. L., III; Silverman, M. L.; Early, A. B.

    2017-12-01

    In response to the Research Opportunities in Earth and Space Science (ROSES) 2015 release announcement for Advancing Collaborative Connections for Earth System Science (ACCESS), researchers at NASA Langley Research Center (LaRC) proposed to extend the capabilities of the existing Toolsets for Airborne Data (TAD) to include subsetting functionality to allow for easier access to international airborne field campaign data. Airborne field studies are commonly used to gain a detailed understanding of atmospheric processes for scientific research on international climate change and air quality issues. To accommodate the rigorous process for manipulating airborne field study chemistry data, and to lessen barriers for researchers, TAD was created with the ability to geolocate data from various sources measured on different time scales from a single flight. The analysis of airborne chemistry data typically requires data subsetting, which can be challenging and resource-intensive for end users. In an effort to streamline this process, new data subsetting features and updates to the current database model will be added to the TAD toolset. These will include two subsetters: temporal and spatial, and vertical profile. The temporal and spatial subsetter will allow users to both focus on data from a specific location and/or time period. The vertical profile subsetter will retrieve data collected during an individual aircraft ascent or descent spiral. These new web-based tools will allow for automation of the typically labor-intensive manual data subsetting process, which will provide users with data tailored to their specific research interests. The system has been designed to allow for new in-situ airborne missions to be added as they become available, with only minor pre-processing required. The development of these enhancements will be discussed in this presentation.

  1. An intelligent data acquisition system for fluid mechanics research

    Science.gov (United States)

    Cantwell, E. R.; Zilliac, G.; Fukunishi, Y.

    1989-01-01

    This paper describes a novel data acquisition system for use with wind-tunnel probe-based measurements, which incorporates a degree of specific fluid dynamics knowledge into a simple expert system-like control program. The concept was developed with a rudimentary expert system coupled to a probe positioning mechanism operating in a small-scale research wind tunnel. The software consisted of two basic elements, a general-purpose data acquisition system and the rulebased control element to take and analyze data and supplying decisions as to where to measure, how many data points to take, and when to stop. The system was validated in an experiment involving a vortical flow field, showing that it was possible to increase the resolution of the experiment or, alternatively, reduce the total number of data points required, to achieve parity with the results of most conventional data acquisition approaches.

  2. An IT-enabled supply chain model: a simulation study

    Science.gov (United States)

    Cannella, Salvatore; Framinan, Jose M.; Barbosa-Póvoa, Ana

    2014-11-01

    During the last decades, supply chain collaboration practices and the underlying enabling technologies have evolved from the classical electronic data interchange (EDI) approach to a web-based and radio frequency identification (RFID)-enabled collaboration. In this field, most of the literature has focused on the study of optimal parameters for reducing the total cost of suppliers, by adopting operational research (OR) techniques. Herein we are interested in showing that the considered information technology (IT)-enabled structure is resilient, that is, it works well across a reasonably broad range of parameter settings. By adopting a methodological approach based on system dynamics, we study a multi-tier collaborative supply chain. Results show that the IT-enabled supply chain improves operational performance and customer service level. Nonetheless, benefits for geographically dispersed networks are of minor entity.

  3. The NCAR Research Data Archive's Hybrid Approach for Data Discovery and Access

    Science.gov (United States)

    Schuster, D.; Worley, S. J.

    2013-12-01

    The NCAR Research Data Archive (RDA http://rda.ucar.edu) maintains a variety of data discovery and access capabilities for it's 600+ dataset collections to support the varying needs of a diverse user community. In-house developed and standards-based community tools offer services to more than 10,000 users annually. By number of users the largest group is external and access the RDA through web based protocols; the internal NCAR HPC users are fewer in number, but typically access more data volume. This paper will detail the data discovery and access services maintained by the RDA to support both user groups, and show metrics that illustrate how the community is using the services. The distributed search capability enabled by standards-based community tools, such as Geoportal and an OAI-PMH access point that serves multiple metadata standards, provide pathways for external users to initially discover RDA holdings. From here, in-house developed web interfaces leverage primary discovery level metadata databases that support keyword and faceted searches. Internal NCAR HPC users, or those familiar with the RDA, may go directly to the dataset collection of interest and refine their search based on rich file collection metadata. Multiple levels of metadata have proven to be invaluable for discovery within terabyte-sized archives composed of many atmospheric or oceanic levels, hundreds of parameters, and often numerous grid and time resolutions. Once users find the data they want, their access needs may vary as well. A THREDDS data server running on targeted dataset collections enables remote file access through OPENDAP and other web based protocols primarily for external users. In-house developed tools give all users the capability to submit data subset extraction and format conversion requests through scalable, HPC based delayed mode batch processing. Users can monitor their RDA-based data processing progress and receive instructions on how to access the data when it is

  4. Big data-enabled multiscale serviceability analysis for aging bridges☆

    Directory of Open Access Journals (Sweden)

    Yu Liang

    2016-08-01

    Full Text Available This work is dedicated to constructing a multi-scale structural health monitoring system to monitor and evaluate the serviceability of bridges based on the Hadoop Ecosystem (MS-SHM-Hadoop. By taking the advantages of the fault-tolerant distributed file system called the Hadoop Distributed File System (HDFS and high-performance parallel data processing engine called MapReduce programming paradigm, MS-SHM-Hadoop features include high scalability and robustness in data ingestion, fusion, processing, retrieval, and analytics. MS-SHM-Hadoop is a multi-scale reliability analysis framework, which ranges from nationwide bridge-surveys, global structural integrity analysis, and structural component reliability analysis. This Nationwide bridge survey uses deep-learning techniques to evaluate the bridge serviceability according to real-time sensory data or archived bridge-related data such as traffic status, weather conditions and bridge structural configuration. The global structural integrity analysis of a targeted bridge is made by processing and analyzing the measured vibration signals incurred by external loads such as wind and traffic flow. Component-wise reliability analysis is also enabled by the deep learning technique, where the input data is derived from the measured structural load effects, hyper-spectral images, and moisture measurement of the structural components. As one of its major contributions, this work employs a Bayesian network to formulate the integral serviceability of a bridge according to its components serviceability and inter-component correlations. Here the inter-component correlations are jointly specified using a statistics-oriented machine learning method (e.g., association rule learning or structural mechanics modeling and simulation.

  5. The RCSB Protein Data Bank: views of structural biology for basic and applied research and education.

    Science.gov (United States)

    Rose, Peter W; Prlić, Andreas; Bi, Chunxiao; Bluhm, Wolfgang F; Christie, Cole H; Dutta, Shuchismita; Green, Rachel Kramer; Goodsell, David S; Westbrook, John D; Woo, Jesse; Young, Jasmine; Zardecki, Christine; Berman, Helen M; Bourne, Philip E; Burley, Stephen K

    2015-01-01

    The RCSB Protein Data Bank (RCSB PDB, http://www.rcsb.org) provides access to 3D structures of biological macromolecules and is one of the leading resources in biology and biomedicine worldwide. Our efforts over the past 2 years focused on enabling a deeper understanding of structural biology and providing new structural views of biology that support both basic and applied research and education. Herein, we describe recently introduced data annotations including integration with external biological resources, such as gene and drug databases, new visualization tools and improved support for the mobile web. We also describe access to data files, web services and open access software components to enable software developers to more effectively mine the PDB archive and related annotations. Our efforts are aimed at expanding the role of 3D structure in understanding biology and medicine. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  6. The Benefits of Being a Student of Teacher Researchers Experiences (sotre)

    Science.gov (United States)

    Eubanks, E.; Guinan, E.; Chiste, M.; Lavoie, A.

    2016-02-01

    Being a Student of Teacher Researcher Experiences (SoTRE), gets students excited for science. Eubanks brings real, current science to the classroom because of time spent in Teacher Researcher Experiences (TRE), where she works with researchers in and out of the field. She involves students in many programs including the National Oceanographic and Atmospheric Administration (NOAA), Polar TREC (Teachers and Researchers & Exploring & Collaboration), National Science Foundation (NSF) funded researchers, (EARTH) Education and Research: Testing Hypothesis, the RJ Dunlap Marine Conservation Program, C-DEBI (Center for Dark Energy Biosphere Investigations and (STARS) Sending Teachers Aboard Research Ships. Being in these programs gives students special privileges such as understanding unique research ideas, tracking tagged sharks, following daily journals written on location, taking part in cross-continental experiments, tracking real time data, exploring current research via posters or visiting universities. Furthermore, contacts made by a TRE give students an added set of resources. When doing experiments for class or advancing their education or career goals, Mrs. Eubanks helps students connect with scientists. This gives students a unique opportunity to learn from real scientists. Being part of these relationships with NOAA, Polar TREC, EARTH, RJ Dunlap, STARS and NSF funded scientists who are actively working, makes being SoTRE the ultimate learning experience. Many students have felt so strongly about the TRE relationship that they have presented at several local and international science conferences. Their message is to encourage scientists to partner with teachers. The benefits of participation in such conferences have included abstract writing and submission, travel, poster creation, networking and presentation, all tools that they will carry with them for a lifetime.

  7. Restitution of the research data in ethnographic health research: issues for debate based on field research conducted in Brazil and France.

    Science.gov (United States)

    Ferreira, Jaqueline

    2015-09-01

    This study examines relevant aspects about the way anthropological research data restitution has been applied in the area of health, based on data obtained from ethnographic field research conducted in Brazil and France. These experiences show that data restitution has been part of the area of research, in different forms and time frames, making it possible to extend periods spent in the field and to interact with individual respondents. This also made it possible to interact with research interlocutors and compare different points of view, adding new information and thereby enriching the research. These aspects raise important questions that require reflection, from an ethical and epistemological standpoint. One is related to the demands made on health anthropologists when they begin their field research and how they deal with these questions: how will researchers use the data they collect without worrying that this may be wrongly interpreted or used in some way to reinforce normative patterns? So, how should an anthropological debate be "translated"? Conscientious researchers will seek to validate their analysis, to discover new points of view and provoke new lines of questioning. Thus, such data should provoke reflexivity about new avenues of research and interpretations.

  8. Hippo Experiment Data Access and Subseting System

    Science.gov (United States)

    Krassovski, M.; Hook, L.; Boden, T.

    2014-12-01

    HIAPER Pole-to-Pole Observations (HIPPO) was an NSF- and NOAA-funded, multi-year global airborne research project to survey the latitudinal and vertical distribution of greenhouse and related gases, and aerosols. Project scientists and support staff flew five month-long missions over the Pacific Basin on the NSF/NCAR Gulfstream V, High-performance Instrumented Airborne Platform for Environmental Research (HIAPER) aircraft between January 2009 and September 2011, spread throughout the annual cycle, from the surface to 14 km in altitude, and from 87°N to 67°S. Data from the HIPPO study of greenhouse gases and aerosols are now available to the atmospheric research community and the public. This comprehensive dataset provides the first high-resolution vertically resolved measurements of over 90 unique atmospheric species from nearly pole-to-pole over the Pacific Ocean across all seasons. The suite of atmospheric trace gases and aerosols is pertinent to understanding the carbon cycle and challenging global climate models. This dataset will provide opportunities for research across a broad spectrum of Earth sciences, including those analyzing the evolution in time and space of the greenhouse gases that affect global climate. The Carbon Dioxide Information Analysis Center (CDIAC) at Oak Ridge National Laboratory (ORNL) provides data management support for the HIPPO experiment including long-term data storage and dissemination. CDIAC has developed a relational database to house HIPPO merged 10-second meteorology, atmospheric chemistry, and aerosol data. This data set provides measurements from all Missions, 1 through 5, that took place from January of 2009 to September 2011. This presentation introduces newly build database and web interface, reflects the present state and functionality of the HIPPO Database and Exploration System as well as future plans for expansion and inclusion of combined discrete flask and GC sample GHG, Halocarbon, and hydrocarbon data.

  9. New Tools for New Research in Psychiatry: A Scalable and Customizable Platform to Empower Data Driven Smartphone Research.

    Science.gov (United States)

    Torous, John; Kiang, Mathew V; Lorme, Jeanette; Onnela, Jukka-Pekka

    2016-05-05

    A longstanding barrier to progress in psychiatry, both in clinical settings and research trials, has been the persistent difficulty of accurately and reliably quantifying disease phenotypes. Mobile phone technology combined with data science has the potential to offer medicine a wealth of additional information on disease phenotypes, but the large majority of existing smartphone apps are not intended for use as biomedical research platforms and, as such, do not generate research-quality data. Our aim is not the creation of yet another app per se but rather the establishment of a platform to collect research-quality smartphone raw sensor and usage pattern data. Our ultimate goal is to develop statistical, mathematical, and computational methodology to enable us and others to extract biomedical and clinical insights from smartphone data. We report on the development and early testing of Beiwe, a research platform featuring a study portal, smartphone app, database, and data modeling and analysis tools designed and developed specifically for transparent, customizable, and reproducible biomedical research use, in particular for the study of psychiatric and neurological disorders. We also outline a proposed study using the platform for patients with schizophrenia. We demonstrate the passive data capabilities of the Beiwe platform and early results of its analytical capabilities. Smartphone sensors and phone usage patterns, when coupled with appropriate statistical learning tools, are able to capture various social and behavioral manifestations of illnesses, in naturalistic settings, as lived and experienced by patients. The ubiquity of smartphones makes this type of moment-by-moment quantification of disease phenotypes highly scalable and, when integrated within a transparent research platform, presents tremendous opportunities for research, discovery, and patient health.

  10. Enabling MPEG-2 video playback in embedded systems through improved data cache efficiency

    Science.gov (United States)

    Soderquist, Peter; Leeser, Miriam E.

    1999-01-01

    Digital video decoding, enabled by the MPEG-2 Video standard, is an important future application for embedded systems, particularly PDAs and other information appliances. Many such system require portability and wireless communication capabilities, and thus face severe limitations in size and power consumption. This places a premium on integration and efficiency, and favors software solutions for video functionality over specialized hardware. The processors in most embedded system currently lack the computational power needed to perform video decoding, but a related and equally important problem is the required data bandwidth, and the need to cost-effectively insure adequate data supply. MPEG data sets are very large, and generate significant amounts of excess memory traffic for standard data caches, up to 100 times the amount required for decoding. Meanwhile, cost and power limitations restrict cache sizes in embedded systems. Some systems, including many media processors, eliminate caches in favor of memories under direct, painstaking software control in the manner of digital signal processors. Yet MPEG data has locality which caches can exploit if properly optimized, providing fast, flexible, and automatic data supply. We propose a set of enhancements which target the specific needs of the heterogeneous types within the MPEG decoder working set. These optimizations significantly improve the efficiency of small caches, reducing cache-memory traffic by almost 70 percent, and can make an enhanced 4 KB cache perform better than a standard 1 MB cache. This performance improvement can enable high-resolution, full frame rate video playback in cheaper, smaller system than woudl otherwise be possible.

  11. Electron Microscopy-Data Analysis Specialist | Center for Cancer Research

    Science.gov (United States)

    PROGRAM DESCRIPTION The Cancer Research Technology Program (CRTP) develops and implements emerging technology, cancer biology expertise and research capabilities to accomplish NCI research objectives.  The CRTP is an outward-facing, multi-disciplinary hub purposed to enable the external cancer research community and provides dedicated support to NCI’s intramural Center for

  12. Collaborative Approaches to Undergraduate Research Training: Information Literacy and Data Management

    Directory of Open Access Journals (Sweden)

    Hailey Mooney

    2014-03-01

    Full Text Available The undergraduate research experience (URE provides an opportunity for students to engage in meaningful work with faculty mentors on research projects. An increasingly important component of scholarly research is the application of research data management best practices, yet this often falls out of the scope of URE programs. This article presents a case study of faculty and librarian collaboration in the integration of a library and research data management curriculum into a social work URE research team. Discussion includes reflections on the content and learning outcomes, benefits of a holistic approach to introducing undergraduate students to research practice, and challenges of scale.

  13. Systematic collection of patient reported outcome research data: A checklist for clinical research professionals.

    Science.gov (United States)

    Wehrlen, Leslie; Krumlauf, Mike; Ness, Elizabeth; Maloof, Damiana; Bevans, Margaret

    2016-05-01

    Understanding the human experience is no longer an outcome explored strictly by social and behavioral researchers. Increasingly, biomedical researchers are also including patient reported outcomes (PROs) in their clinical research studies not only due to calls for increased patient engagement in research but also healthcare. Collecting PROs in clinical research studies offers a lens into the patient's unique perspective providing important information to industry sponsors and the FDA. Approximately 30% of trials include PROs as primary or secondary endpoints and a quarter of FDA new drug, device and biologic applications include PRO data to support labeling claims. In this paper PRO, represents any information obtained directly from the patient or their proxy, without interpretation by another individual to ascertain their health, evaluate symptoms or conditions and extends the reference of PRO, as defined by the FDA, to include other sources such as patient diaries. Consumers and clinicians consistently report that PRO data are valued, and can aide when deciding between treatment options; therefore an integral part of clinical research. However, little guidance exists for clinical research professionals (CRPs) responsible for collecting PRO data on the best practices to ensure quality data collection so that an accurate assessment of the patient's view is collected. Therefore the purpose of this work was to develop and validate a checklist to guide quality collection of PRO data. The checklist synthesizes best practices from published literature and expert opinions addressing practical and methodological challenges CRPs often encounter when collecting PRO data in research settings. Published by Elsevier Inc.

  14. Automated Data Quality Assurance using OGC Sensor Web Enablement Frameworks for Marine Observatories

    Science.gov (United States)

    Toma, Daniel; Bghiel, Ikram; del Rio, Joaquin; Hidalgo, Alberto; Carreras, Normandino; Manuel, Antoni

    2014-05-01

    Over the past years, environmental sensors have continuously improved by becoming smaller, cheaper, and more intelligent. Therefore, many sensor networks are increasingly deployed to monitor our environment. But due to the large number of sensor manufacturers, accompanying protocols and data encoding, automated integration and data quality assurance of diverse sensors in an observing systems is not straightforward, requiring development of data management code and manual tedious configuration. However, over the past few years it has been demonstrated that Open-Geospatial Consortium (OGC) frameworks can enable web services with fully-described sensor systems, including data processing, sensor characteristics and quality control tests and results. So far, the SWE framework does not describe how to integrate sensors on-the-fly with minimal human intervention. The data management software which enables access to sensors, data processing and quality control tests has to be implemented and the results have to be manually mapped to the SWE models. In this contribution, we describe a Sensor Plug & Play infrastructure for the Sensor Web by combining (1) OGC PUCK protocol - a simple standard embedded instrument protocol to store and retrieve directly from the devices the declarative description of sensor characteristics and quality control tests, (2) an automatic mechanism for data processing and quality control tests underlying the Sensor Web - the Sensor Interface Descriptor (SID) concept, as well as (3) a model for the declarative description of sensor which serves as a generic data management mechanism - designed as a profile and extension of OGC SWE's SensorML standard. We implement and evaluate our approach by applying it to the OBSEA Observatory, and can be used to demonstrate the ability to assess data quality for temperature, salinity, air pressure and wind speed and direction observations off the coast of Garraf, in the north-eastern Spain.

  15. Eodataservice.org: Big Data Platform to Enable Multi-disciplinary Information Extraction from Geospatial Data

    Science.gov (United States)

    Natali, S.; Mantovani, S.; Barboni, D.; Hogan, P.

    2017-12-01

    In 1999, US Vice-President Al Gore outlined the concept of `Digital Earth' as a multi-resolution, three-dimensional representation of the planet to find, visualise and make sense of vast amounts of geo- referenced information on physical and social environments, allowing to navigate through space and time, accessing historical and forecast data to support scientists, policy-makers, and any other user. The eodataservice platform (http://eodataservice.org/) implements the Digital Earth Concept: eodatasevice is a cross-domain platform that makes available a large set of multi-year global environmental collections allowing data discovery, visualization, combination, processing and download. It implements a "virtual datacube" approach where data stored on distributed data centers are made available via standardized OGC-compliant interfaces. Dedicated web-based Graphic User Interfaces (based on the ESA-NASA WebWorldWind technology) as well as web-based notebooks (e.g. Jupyter notebook), deskop GIS tools and command line interfaces can be used to access and manipulate the data. The platform can be fully customized on users' needs. So far eodataservice has been used for the following thematic applications: High resolution satellite data distribution Land surface monitoring using SAR surface deformation data Atmosphere, ocean and climate applications Climate-health applications Urban Environment monitoring Safeguard of cultural heritage sites Support to farmers and (re)-insurances in the agriculturés field In the current work, the EO Data Service concept is presented as key enabling technology; furthermore various examples are provided to demonstrate the high level of interdisciplinarity of the platform.

  16. Leveraging 35 years of Pinus taeda research in the southeastern US to constrain forest carbon cycle predictions: regional data assimilation using ecosystem experiments

    Science.gov (United States)

    Quinn Thomas, R.; Brooks, Evan B.; Jersild, Annika L.; Ward, Eric J.; Wynne, Randolph H.; Albaugh, Timothy J.; Dinon-Aldridge, Heather; Burkhart, Harold E.; Domec, Jean-Christophe; Fox, Thomas R.; Gonzalez-Benecke, Carlos A.; Martin, Timothy A.; Noormets, Asko; Sampson, David A.; Teskey, Robert O.

    2017-07-01

    predictions of stem biomass productivity under elevated CO2, decreased precipitation, and increased nutrient availability that include estimates of uncertainty for the southeastern US. Overall, we (1) demonstrated how three decades of research in southeastern US planted pine forests can be used to develop DA techniques that use multiple locations, multiple data streams, and multiple ecosystem experiment types to optimize parameters and (2) developed a tool for the development of future predictions of forest productivity for natural resource managers that leverage a rich dataset of integrated ecosystem observations across a region.

  17. An Authentic Research Experience in an Astronomy Education Professional Development Program: An Analysis of 8 Years of Data on the NASA/IPAC Teacher Archive Research Program (NITARP)

    Science.gov (United States)

    Rebull, Luisa; Roberts, Tracy; Laurence, Wendi; Fitzgerald, Michael; French, Debbie; Gorjian, Varoujan; Squires, Gordon

    2018-01-01

    The NASA/IPAC Teacher Archive Research Program (NITARP) partners small groups of educators with a research astronomer for a year-long authentic research project. This program aligns well with the characteristics of high-quality professional development (PD) programs and has worked with a total of 103 educators since 2005. In this poster, we explore surveys obtained from 74 different educators, at up to four waypoints during the course of 13 months, incorporating data from the class of 2010 through the class of 2017. The reasons educators participate are mapped onto a continuum ranging from more inward-focused to more outward-focused; NITARP has had more outward-focused educators than inward-focused, though there is a bias against the extremes on either end of the continuum. This insight into teacher motivations has implications for how the educators are supported during the NITARP year. Three-quarters of the educators self-report some or major changes in their understanding of the nature of science. The program provides educators with experience collaborating with astronomers and other educators, and forges a strong link to the astronomical research community; the NITARP community of practice encourages and reinforces these linkages. During the experience, educators get comfortable with learning complex new concepts, with ~40% noting in their surveys that their approach to learning has changed. Educators are provided opportunities for professional growth; at least 12% have changed career paths substantially in part due to the program, and 11% report that the experience was “life changing.” At least 60% are including richer, more authentic science activities in their classrooms. This work illuminates what benefits the program brings to its participants, and serves as a model for similar PD programs in other STEM subjects.

  18. The Undergraduate Teaching Assistant Experience Offers Opportunities Similar to the Undergraduate Research Experience†

    Science.gov (United States)

    Schalk, Kelly A.; McGinnis, J. Randy; Harring, Jeffrey R.; Hendrickson, Amy; Smith, Ann C.

    2009-01-01

    There has been a growing concern in higher education about our failure to produce scientifically trained workers and scientifically literate citizens. Active-learning and research-oriented activities are posited as ways to give students a deeper understanding of science. We report on an undergraduate teaching assistant (UTA) experience and suggest that students who participate as a UTA obtain benefits analogous to those who participate as an undergraduate research assistant (URA). We examined the experiences of 24 undergraduates acting as UTAs in a general microbiology course. Self-reported gains by the UTAs were supported by observational data from undergraduates in the course who were mentored by the UTAs and by the graduate teaching assistants (GTAs) with whom the UTAs worked. Specifically, data from the UTAs’ journals and self-reported Likert scales and rubrics indicated that our teaching assistants developed professional characteristics such as self-confidence and communication and leadership skills, while they acquired knowledge of microbiology content and laboratory skills. Data from the undergraduate Likert scale as well as the pre- and post-GTA rubrics further confirmed our UTA’s data interpretations. These findings are significant because they offer empirical data to support the suggestion that the UTA experience is an effective option for developing skills and knowledge in undergraduates that are essential for careers in science. The UTA experience provides a valuable alternative to the URA experience. PMID:23653688

  19. TCIA: An information resource to enable open science.

    Science.gov (United States)

    Prior, Fred W; Clark, Ken; Commean, Paul; Freymann, John; Jaffe, Carl; Kirby, Justin; Moore, Stephen; Smith, Kirk; Tarbox, Lawrence; Vendt, Bruce; Marquez, Guillermo

    2013-01-01

    Reusable, publicly available data is a pillar of open science. The Cancer Imaging Archive (TCIA) is an open image archive service supporting cancer research. TCIA collects, de-identifies, curates and manages rich collections of oncology image data. Image data sets have been contributed by 28 institutions and additional image collections are underway. Since June of 2011, more than 2,000 users have registered to search and access data from this freely available resource. TCIA encourages and supports cancer-related open science communities by hosting and managing the image archive, providing project wiki space and searchable metadata repositories. The success of TCIA is measured by the number of active research projects it enables (>40) and the number of scientific publications and presentations that are produced using data from TCIA collections (39).

  20. Researcher perspectives on publication and peer review of data.

    Directory of Open Access Journals (Sweden)

    John Ernest Kratz

    Full Text Available Data "publication" seeks to appropriate the prestige of authorship in the peer-reviewed literature to reward researchers who create useful and well-documented datasets. The scholarly communication community has embraced data publication as an incentive to document and share data. But, numerous new and ongoing experiments in implementation have not yet resolved what a data publication should be, when data should be peer-reviewed, or how data peer review should work. While researchers have been surveyed extensively regarding data management and sharing, their perceptions and expectations of data publication are largely unknown. To bring this important yet neglected perspective into the conversation, we surveyed ∼ 250 researchers across the sciences and social sciences- asking what expectations"data publication" raises and what features would be useful to evaluate the trustworthiness, evaluate the impact, and enhance the prestige of a data publication. We found that researcher expectations of data publication center on availability, generally through an open database or repository. Few respondents expected published data to be peer-reviewed, but peer-reviewed data enjoyed much greater trust and prestige. The importance of adequate metadata was acknowledged, in that almost all respondents expected data peer review to include evaluation of the data's documentation. Formal citation in the reference list was affirmed by most respondents as the proper way to credit dataset creators. Citation count was viewed as the most useful measure of impact, but download count was seen as nearly as valuable. These results offer practical guidance for data publishers seeking to meet researcher expectations and enhance the value of published data.

  1. Neutron data experiments for transmutation. Annual Report 2007/2008

    Energy Technology Data Exchange (ETDEWEB)

    Blomgren, J.; al-Adili, A.; Andersson, P.; Bevilacqua, R.; Nilsson, L.; Pomp, S.; Simutkin, V.; Oehrn, A.; Oesterlund, M. (Uppsala Univ. (Sweden). Div. of Applied Nuclear Physics)

    2008-08-15

    The project NEXT, Neutron data Experiments for Transmutation, is performed within the nuclear reactions group of the Dept. of Physics and Astronomy. The activities of the group are directed towards experimental studies of nuclear reaction probabilities of importance for various applications, like transmutation of nuclear waste, biomedical effects and electronics reliability. The experimental work is primarily undertaken at the The Svedberg Laboratory (TSL) in Uppsala, where the group is operating two world-unique instruments, MEDLEY and SCANDAL. Highlights from the past year: - The SCANDAL facility has been upgraded. - One PhD student has successfully defended her thesis. - Two PhD students have been accepted. - Vasily Simutkin has been selected as one of the top 12 PhD students within the European Nuclear Education Network. He has accordingly been invited to present his work at the ENEN PhD event held in connection with the PHYSOR conference in Interlaken, Switzerland, September 2008. - A research collaboration with the dedicated EU laboratory for nuclear data research has been established. - A well-attended workshop on nuclear data for ADS and Gen-IV has been organized as part of the EU project CANDIDE (Coordination Action on Nuclear Data for Industrial Development in Europe), coordinated by Jan Blomgren. - Several experiments have been performed at TSL, with beamtime funded through the EU project EFNUDAT (European Facilities for Nuclear Data research), partly coordinated by Jan Blomgren. - Nuclear power education has reached all-time high at Uppsala University. In particular, industry education has increased significantly. - IAEA has visited Uppsala University to investigate the industry-related nuclear power education, as part of a safety culture review of the Forsmark nuclear power plant

  2. Neutron data experiments for transmutation. Annual Report 2007/2008

    International Nuclear Information System (INIS)

    Blomgren, J.; Al-Adili, A.; Andersson, P.; Bevilacqua, R.; Nilsson, L.; Pomp, S.; Simutkin, V.; Oehrn, A.; Oesterlund, M.

    2008-08-01

    The project NEXT, Neutron data Experiments for Transmutation, is performed within the nuclear reactions group of the Dept. of Physics and Astronomy. The activities of the group are directed towards experimental studies of nuclear reaction probabilities of importance for various applications, like transmutation of nuclear waste, biomedical effects and electronics reliability. The experimental work is primarily undertaken at the The Svedberg Laboratory (TSL) in Uppsala, where the group is operating two world-unique instruments, MEDLEY and SCANDAL. Highlights from the past year: - The SCANDAL facility has been upgraded. - One PhD student has successfully defended her thesis. - Two PhD students have been accepted. - Vasily Simutkin has been selected as one of the top 12 PhD students within the European Nuclear Education Network. He has accordingly been invited to present his work at the ENEN PhD event held in connection with the PHYSOR conference in Interlaken, Switzerland, September 2008. - A research collaboration with the dedicated EU laboratory for nuclear data research has been established. - A well-attended workshop on nuclear data for ADS and Gen-IV has been organized as part of the EU project CANDIDE (Coordination Action on Nuclear Data for Industrial Development in Europe), coordinated by Jan Blomgren. - Several experiments have been performed at TSL, with beamtime funded through the EU project EFNUDAT (European Facilities for Nuclear Data research), partly coordinated by Jan Blomgren. - Nuclear power education has reached all-time high at Uppsala University. In particular, industry education has increased significantly. - IAEA has visited Uppsala University to investigate the industry-related nuclear power education, as part of a safety culture review of the Forsmark nuclear power plant

  3. The National Extreme Events Data and Research Center (NEED)

    Science.gov (United States)

    Gulledge, J.; Kaiser, D. P.; Wilbanks, T. J.; Boden, T.; Devarakonda, R.

    2014-12-01

    The Climate Change Science Institute at Oak Ridge National Laboratory (ORNL) is establishing the National Extreme Events Data and Research Center (NEED), with the goal of transforming how the United States studies and prepares for extreme weather events in the context of a changing climate. NEED will encourage the myriad, distributed extreme events research communities to move toward the adoption of common practices and will develop a new database compiling global historical data on weather- and climate-related extreme events (e.g., heat waves, droughts, hurricanes, etc.) and related information about impacts, costs, recovery, and available research. Currently, extreme event information is not easy to access and is largely incompatible and inconsistent across web sites. NEED's database development will take into account differences in time frames, spatial scales, treatments of uncertainty, and other parameters and variables, and leverage informatics tools developed at ORNL (i.e., the Metadata Editor [1] and Mercury [2]) to generate standardized, robust documentation for each database along with a web-searchable catalog. In addition, NEED will facilitate convergence on commonly accepted definitions and standards for extreme events data and will enable integrated analyses of coupled threats, such as hurricanes/sea-level rise/flooding and droughts/wildfires. Our goal and vision is that NEED will become the premiere integrated resource for the general study of extreme events. References: [1] Devarakonda, Ranjeet, et al. "OME: Tool for generating and managing metadata to handle BigData." Big Data (Big Data), 2014 IEEE International Conference on. IEEE, 2014. [2] Devarakonda, Ranjeet, et al. "Mercury: reusable metadata management, data discovery and access system." Earth Science Informatics 3.1-2 (2010): 87-94.

  4. Experiment Databases

    Science.gov (United States)

    Vanschoren, Joaquin; Blockeel, Hendrik

    Next to running machine learning algorithms based on inductive queries, much can be learned by immediately querying the combined results of many prior studies. Indeed, all around the globe, thousands of machine learning experiments are being executed on a daily basis, generating a constant stream of empirical information on machine learning techniques. While the information contained in these experiments might have many uses beyond their original intent, results are typically described very concisely in papers and discarded afterwards. If we properly store and organize these results in central databases, they can be immediately reused for further analysis, thus boosting future research. In this chapter, we propose the use of experiment databases: databases designed to collect all the necessary details of these experiments, and to intelligently organize them in online repositories to enable fast and thorough analysis of a myriad of collected results. They constitute an additional, queriable source of empirical meta-data based on principled descriptions of algorithm executions, without reimplementing the algorithms in an inductive database. As such, they engender a very dynamic, collaborative approach to experimentation, in which experiments can be freely shared, linked together, and immediately reused by researchers all over the world. They can be set up for personal use, to share results within a lab or to create open, community-wide repositories. Here, we provide a high-level overview of their design, and use an existing experiment database to answer various interesting research questions about machine learning algorithms and to verify a number of recent studies.

  5. Review of Quality Assurance in SKB's Repository Research Experiments

    Energy Technology Data Exchange (ETDEWEB)

    Hicks, T.W. [Galson Sciences Ltd, 5 Grosvenor House, Melton Road, Oakham(United Kingdom)

    2007-01-15

    SKB is preparing licence applications for a spent nuclear fuel encapsulation plant and repository which will be supported by the SR-Site safety report. A separate safety report, SR-Can, has been produced by SKB in preparation for the SR-Site report. SKI is in the process of reviewing the SR-Can safety report. In preparation for this review, and with a view to building confidence in SKB's research activities and understanding SKB's handling of data and other information, SKI has examined SKB's application of QA measures in the management and conduct of repository research and development projects that support the SR-Can safety assessment. These preliminary investigations will serve to support the preparation of more detailed quality and technical audits of SKB's repository safety assessment after the submission of a licence application. SKI's approach to this QA review is based on the consideration of quality-affecting aspects of a selection of SKB's research and development activities. As part of this review, SKI identified the need to examine quality-related aspects of some of the many experiments and investigations that form part of SKB's repository research programme. This report presents the findings of such a review, focusing on experiments concerned with the properties and performance of the engineered barrier system. First, in order to establish a broad understanding of QA requirements for repository scientific investigations, QA procedures implemented in the management of research and development activities for the low-level radioactive waste repository near Drigg in the UK and the Waste Isolation Pilot Plant and Yucca Mountain repository projects in the US were studied. The QA procedures for experiments and tests undertaken in these projects were compared with those implemented by SKB. Key findings are: QA programmes have been implemented for each repository development programme in response to regulatory requirements

  6. Improving Geoscience Education through the PolarTREC Teacher Research Experience Model (Invited)

    Science.gov (United States)

    Warburton, J.; Timm, K.; Larson, A. M.

    2010-12-01

    Teacher Research Experiences (TRE’s) are not new. For more than a decade, the National Science Foundation (NSF) as well as other federal agencies have been funding programs that place teachers with researchers in efforts to invigorate science education by bringing educators and researchers together through hands-on experiences. Many of the TRE’s are successful in providing a hands-on field experience for the teachers and researchers however many of the programs lack the resources to continue the collaborations and support the growing network of teachers that have had these field experiences. In 2007, NSF provided funding for PolarTREC—Teachers and Researchers Exploring and Collaborating, a program of the Arctic Research Consortium of the U.S. (ARCUS). PolarTREC is a TRE where K-12 teachers participate in polar field research, working closely with scientists as a pathway to improving science education. In just three years, it has become a successful TRE. What makes PolarTREC different than other the teacher research experience programs and how can others benefit from what we have learned? During this presentation, we will share data collected through the program evaluation and on how PolarTREC contributes to the discipline of Science, Technology, Engineering, and Mathematics (STEM) education and pedagogy through a model program conceived and organized according to current best practices, such as pre-research training, mentoring, support for classroom transfer, and long-term access to resources and support. Data shows that PolarTREC’s comprehensive program activities have many positive impacts on educators and their ability to teach science concepts and improve their teaching methods. Additionally, K-12 students polled in interest surveys showed significant changes in key areas including amount of time spent in school exploring research activities, importance of understanding science for future work, importance of understanding the polar regions as a person

  7. SoTRE's Speak Up: Students Share the Benefits of Teacher Researcher Experiences

    Science.gov (United States)

    Eubanks, E.; Allen, S.; Farmer, S.; Jones, K.

    2016-12-01

    Being Students of Teacher Researcher Experiences (SoTRE) gives students special advantages that most students do not get. Teachers Elizabeth Eubanks and Steve Allen share their knowledge gained via partnerships with Teacher Researcher Experiences (TRE's) such as the National Oceanographic and Atmospheric Administration Teacher at Sea program (NOAA- TAS), Polar TREC (Teachers and Researchers & Exploring & Collaboration), National Science Foundation (NSF) funded researchers, (EARTH) Education and Research: Testing Hypothesis, the RJ Dunlap Marine Conservation Program, C-DEBI (Center for Dark Energy Biosphere Investigations and (STARS) Sending Teachers Aboard Research Ships, The Maury Project and Mate. Students gain special privileges such as understanding unique research ideas, tracking tagged sharks, following daily journals written on location, taking part in cross-continental experiments, tracking real time data, exploring current research via posters or visiting universities. Furthermore, contacts made by a TRE give students an added set of resources. When doing experiments for class or advancing their education or career goals Eubanks and Allen help students connect with scientists. Many students have felt so strongly about the TRE relationship that they have presented at several local and international science conferences. Their message is to encourage scientists to partner with teachers. The benefits of participation in such conferences have included abstract writing and submission, travel, poster creation, oral presentation, networking and personal research presentation, all tools that they will carry with them for a lifetime.

  8. Forward Technology Solar Cell Experiment First On-Orbit Data

    Science.gov (United States)

    Walters, R. J.; Garner, J. C.; Lam, S. N.; Vazquez, J. A.; Braun, W. R.; Ruth, R. E.; Warner, J. H.; Lorentzen, J. R.; Messenger, S. R.; Bruninga, R.; hide

    2007-01-01

    This paper presents first on orbit measured data from the Forward Technology Solar Cell Experiment (FTSCE). FTSCE is a space experiment housed within the 5th Materials on the International Space Station Experiment (MISSE-5). MISSE-5 was launched aboard the Shuttle return to flight mission (STS-114) on July 26, 2005 and deployed on the exterior of the International Space Station (ISS). The experiment will remain in orbit for nominally one year, after which it will be returned to Earth for post-flight testing and analysis. While on orbit, the experiment is designed to measure a 36 point current vs. voltage (IV) curve on each of the experimental solar cells, and the data is continuously telemetered to Earth. The experiment also measures the solar cell temperature and the orientation of the solar cells to the sun. A range of solar cell technologies are included in the experiment including state-of-the-art triple junction InGaP/GaAs/Ge solar cells from several vendors, thin film amorphous Si and CuIn(Ga)Se2 cells, and next-generation technologies like single-junction GaAs cells grown on Si wafers and metamorphic InGaP/InGaAs/Ge triple-junction cells. In addition to FTSCE, MISSE-5 also contains a Thin-Film Materials experiment. This is a passive experiment that will provide data on the effect of the space environment on more than 200 different materials. FTSCE was initially conceived in response to various on-orbit and ground test anomalies associated with space power systems. The Department of Defense (DoD) required a method of rapidly obtaining on orbit validation data for new space solar cell technologies, and NRL was tasked to devise an experiment to meet this requirement. Rapid access to space was provided by the MISSE Program which is a NASA Langley Research Center program. MISSE-5 is a completely self-contained experiment system with its own power generation and storage system and communications system. The communications system, referred to as PCSat, transmits

  9. Virtual Laboratory Enabling Collaborative Research in Applied Vehicle Technologies

    Science.gov (United States)

    Lamar, John E.; Cronin, Catherine K.; Scott, Laura E.

    2005-01-01

    The virtual laboratory is a new technology, based on the internet, that has had wide usage in a variety of technical fields because of its inherent ability to allow many users to participate simultaneously in instruction (education) or in the collaborative study of a common problem (real-world application). The leadership in the Applied Vehicle Technology panel has encouraged the utilization of this technology in its task groups for some time and its parent organization, the Research and Technology Agency, has done the same for its own administrative use. This paper outlines the application of the virtual laboratory to those fields important to applied vehicle technologies, gives the status of the effort, and identifies the benefit it can have on collaborative research. The latter is done, in part, through a specific example, i.e. the experience of one task group.

  10. Ultra-Scale Visualization: Research and Education

    International Nuclear Information System (INIS)

    Ma, K-L; Ross, Robert; Huang Jian; Humphreys, Greg; Max, Nelson; Moreland, Kenneth; Owens, John D; Shen, H-W

    2007-01-01

    Understanding the science behind large-scale simulations and high-throughput experiments requires extracting meaning from data sets of hundreds of terabytes or more. Visualization is the most intuitive means for scientists to understand data at this scale, and the most effective way to communicate their findings with others. Even though visualization technology has matured over the past twenty years, it is still limited by the extent and scale of the data that it can be applied to, and also by the functionalities that were mostly designed for single-user, single-variable, and single-space investigation. The Institute for Ultra-Scale Visualization (IUSV), funded by the DOE SciDAC-2 program, has the mission to advance visualization technologies to enable knowledge discovery and dissemination for peta-scale applications. By working with the SciDAC application projects, Centers for Enabling Technology, and other Institutes, IUSV aims to lead the research innovation that can create new visualization capabilities needed for gleaning insights from data at petascale and beyond to solve forefront scientific problems. This paper outlines what we see as some of the biggest research challenges facing the visualization community, and how we can approach education and outreach to put successful research in the hands of scientists

  11. A Binaural CI Research Platform for Oticon Medical SP/XP Implants Enabling ITD/ILD and Variable Rate Processing

    Science.gov (United States)

    Adiloğlu, K.; Herzke, T.

    2015-01-01

    We present the first portable, binaural, real-time research platform compatible with Oticon Medical SP and XP generation cochlear implants. The platform consists of (a) a pair of behind-the-ear devices, each containing front and rear calibrated microphones, (b) a four-channel USB analog-to-digital converter, (c) real-time PC-based sound processing software called the Master Hearing Aid, and (d) USB-connected hardware and output coils capable of driving two implants simultaneously. The platform is capable of processing signals from the four microphones simultaneously and producing synchronized binaural cochlear implant outputs that drive two (bilaterally implanted) SP or XP implants. Both audio signal preprocessing algorithms (such as binaural beamforming) and novel binaural stimulation strategies (within the implant limitations) can be programmed by researchers. When the whole research platform is combined with Oticon Medical SP implants, interaural electrode timing can be controlled on individual electrodes to within ±1 µs and interaural electrode energy differences can be controlled to within ±2%. Hence, this new platform is particularly well suited to performing experiments related to interaural time differences in combination with interaural level differences in real-time. The platform also supports instantaneously variable stimulation rates and thereby enables investigations such as the effect of changing the stimulation rate on pitch perception. Because the processing can be changed on the fly, researchers can use this platform to study perceptual changes resulting from different processing strategies acutely. PMID:26721923

  12. A Binaural CI Research Platform for Oticon Medical SP/XP Implants Enabling ITD/ILD and Variable Rate Processing.

    Science.gov (United States)

    Backus, B; Adiloğlu, K; Herzke, T

    2015-12-30

    We present the first portable, binaural, real-time research platform compatible with Oticon Medical SP and XP generation cochlear implants. The platform consists of (a) a pair of behind-the-ear devices, each containing front and rear calibrated microphones, (b) a four-channel USB analog-to-digital converter, (c) real-time PC-based sound processing software called the Master Hearing Aid, and (d) USB-connected hardware and output coils capable of driving two implants simultaneously. The platform is capable of processing signals from the four microphones simultaneously and producing synchronized binaural cochlear implant outputs that drive two (bilaterally implanted) SP or XP implants. Both audio signal preprocessing algorithms (such as binaural beamforming) and novel binaural stimulation strategies (within the implant limitations) can be programmed by researchers. When the whole research platform is combined with Oticon Medical SP implants, interaural electrode timing can be controlled on individual electrodes to within ±1 µs and interaural electrode energy differences can be controlled to within ±2%. Hence, this new platform is particularly well suited to performing experiments related to interaural time differences in combination with interaural level differences in real-time. The platform also supports instantaneously variable stimulation rates and thereby enables investigations such as the effect of changing the stimulation rate on pitch perception. Because the processing can be changed on the fly, researchers can use this platform to study perceptual changes resulting from different processing strategies acutely. © The Author(s) 2015.

  13. The Grid Enabled Mass Storage System (GEMMS): the Storage and Data management system used at the INFN Tier1 at CNAF.

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    The storage solution currently used in production at the INFN Tier-1 at CNAF, is the result of several years of case studies, software development and tests. This solution, called the Grid Enabled Mass Storage System (GEMSS), is based on a custom integration between a fast and reliable parallel filesystem (IBM GPFS), with a complete integrated tape backend based on TIVOLI TSM Hierarchical storage management (HSM) and the Storage Resource Manager (StoRM), providing access to grid users through a standard SRM interface. Since the start of the operations of the Large Hadron Collider (LHC), all the LHC experiments have been using GEMMS at CNAF for both the fast access to data on disk and the long-term tape archive. Moreover, during the last year, GEMSS has become the standard solution for all the other experiments hosted at CNAF, allowing the definitive consolidation of the data storage layer. Our choice has proved to be successful in the last two years of production with constant enhancements in the software re...

  14. Reflective equilibrium and empirical data: third person moral experiences in empirical medical ethics.

    Science.gov (United States)

    De Vries, Martine; Van Leeuwen, Evert

    2010-11-01

    In ethics, the use of empirical data has become more and more popular, leading to a distinct form of applied ethics, namely empirical ethics. This 'empirical turn' is especially visible in bioethics. There are various ways of combining empirical research and ethical reflection. In this paper we discuss the use of empirical data in a special form of Reflective Equilibrium (RE), namely the Network Model with Third Person Moral Experiences. In this model, the empirical data consist of the moral experiences of people in a practice. Although inclusion of these moral experiences in this specific model of RE can be well defended, their use in the application of the model still raises important questions. What precisely are moral experiences? How to determine relevance of experiences, in other words: should there be a selection of the moral experiences that are eventually used in the RE? How much weight should the empirical data have in the RE? And the key question: can the use of RE by empirical ethicists really produce answers to practical moral questions? In this paper we start to answer the above questions by giving examples taken from our research project on understanding the norm of informed consent in the field of pediatric oncology. We especially emphasize that incorporation of empirical data in a network model can reduce the risk of self-justification and bias and can increase the credibility of the RE reached. © 2009 Blackwell Publishing Ltd.

  15. Enabling Large-Scale Biomedical Analysis in the Cloud

    Directory of Open Access Journals (Sweden)

    Ying-Chih Lin

    2013-01-01

    Full Text Available Recent progress in high-throughput instrumentations has led to an astonishing growth in both volume and complexity of biomedical data collected from various sources. The planet-size data brings serious challenges to the storage and computing technologies. Cloud computing is an alternative to crack the nut because it gives concurrent consideration to enable storage and high-performance computing on large-scale data. This work briefly introduces the data intensive computing system and summarizes existing cloud-based resources in bioinformatics. These developments and applications would facilitate biomedical research to make the vast amount of diversification data meaningful and usable.

  16. Experience inheritance from famous specialists based on real-world clinical research paradigm of traditional Chinese medicine.

    Science.gov (United States)

    Song, Guanli; Wang, Yinghui; Zhang, Runshun; Liu, Baoyan; Zhou, Xuezhong; Zhou, Xiaji; Zhang, Hong; Guo, Yufeng; Xue, Yanxing; Xu, Lili

    2014-09-01

    The current modes of experience inheritance from famous specialists in traditional Chinese medicine (TCM) include master and disciple, literature review, clinical-epidemiology-based clinical research observation, and analysis and data mining via computer and database technologies. Each mode has its advantages and disadvantages. However, a scientific and instructive experience inheritance mode has not been developed. The advent of the big data era as well as the formation and practice accumulation of the TCM clinical research paradigm in the real world have provided new perspectives, techniques, and methods for inheriting experience from famous TCM specialists. Through continuous exploration and practice, the research group proposes the innovation research mode based on the real-world TCM clinical research paradigm, which involves the inheritance and innovation of the existing modes. This mode is formulated in line with its own development regularity of TCM and is expected to become the main mode of experience inheritance in the clinical field.

  17. Accelerating Translational Research through Open Science: The Neuro Experiment.

    Science.gov (United States)

    Gold, E Richard

    2016-12-01

    Translational research is often afflicted by a fundamental problem: a limited understanding of disease mechanisms prevents effective targeting of new treatments. Seeking to accelerate research advances and reimagine its role in the community, the Montreal Neurological Institute (Neuro) announced in the spring of 2016 that it is launching a five-year experiment during which it will adopt Open Science-open data, open materials, and no patenting-across the institution. The experiment seeks to examine two hypotheses. The first is whether the Neuro's Open Science initiative will attract new private partners. The second hypothesis is that the Neuro's institution-based approach will draw companies to the Montreal region, where the Neuro is based, leading to the creation of a local knowledge hub. This article explores why these hypotheses are likely to be true and describes the Neuro's approach to exploring them.

  18. Accelerating Translational Research through Open Science: The Neuro Experiment.

    Directory of Open Access Journals (Sweden)

    E Richard Gold

    2016-12-01

    Full Text Available Translational research is often afflicted by a fundamental problem: a limited understanding of disease mechanisms prevents effective targeting of new treatments. Seeking to accelerate research advances and reimagine its role in the community, the Montreal Neurological Institute (Neuro announced in the spring of 2016 that it is launching a five-year experiment during which it will adopt Open Science-open data, open materials, and no patenting-across the institution. The experiment seeks to examine two hypotheses. The first is whether the Neuro's Open Science initiative will attract new private partners. The second hypothesis is that the Neuro's institution-based approach will draw companies to the Montreal region, where the Neuro is based, leading to the creation of a local knowledge hub. This article explores why these hypotheses are likely to be true and describes the Neuro's approach to exploring them.

  19. Big Data and Dementia: Charting the Route Ahead for Research, Ethics, and Policy.

    Science.gov (United States)

    Ienca, Marcello; Vayena, Effy; Blasimme, Alessandro

    2018-01-01

    Emerging trends in pervasive computing and medical informatics are creating the possibility for large-scale collection, sharing, aggregation and analysis of unprecedented volumes of data, a phenomenon commonly known as big data. In this contribution, we review the existing scientific literature on big data approaches to dementia, as well as commercially available mobile-based applications in this domain. Our analysis suggests that big data approaches to dementia research and care hold promise for improving current preventive and predictive models, casting light on the etiology of the disease, enabling earlier diagnosis, optimizing resource allocation, and delivering more tailored treatments to patients with specific disease trajectories. Such promissory outlook, however, has not materialized yet, and raises a number of technical, scientific, ethical, and regulatory challenges. This paper provides an assessment of these challenges and charts the route ahead for research, ethics, and policy.

  20. To the Extremes! A Teacher Research Experience Program in the Polar Regions

    Science.gov (United States)

    Warburton, J.; Bartholow, S.

    2014-12-01

    PolarTREC-Teachers and Researchers Exploring and Collaborating, a teacher professional development program, began with the International Polar Year in 2004 and continues today in the United States. In 2007, the National Science Foundation designated PolarTREC as potentially transformative, meaning that the "research results often do not fit within established models or theories and may initially be unexpected or difficult to interpret; their transformative nature and utility might not be recognized until years later." PolarTREC brings U.S. K-12 educators and polar researchers together through an innovative teacher research experience model. Teachers spend three to six weeks in remote arctic and Antarctic field camps. Since 2007, over 100 teachers have been placed in field experiences throughout the Arctic and Antarctic and with half of them participating in field experiences in Antarctica. During their experience, teachers become research team members filling a variety of roles on the team. They also fulfil a unique role of public outreach officer, conducting live presentations about their field site and research as well as journaling, answering questions, and posting photos. Evaluation data collected over the past eight years on program participants shows that PolarTREC has clearly achieved it goals and strongly suggests programs that link teachers and researchers can have the potential to transform the nature of science education. By giving teachers the content knowledge, pedagogical tools, confidence, understanding of science in the broader society, and experiences with scientific inquiry, participating teachers are using authentic scientific research in their classrooms. Not surprisingly this has also led to increases in student interest and knowledge about the Polar Regions. In this presentation, we will highlight the best practices of teacher research experiences as well as discuss why it is vital to have teachers and researchers work together to communicate

  1. Collecting behavioural data using the world wide web: considerations for researchers.

    Science.gov (United States)

    Rhodes, S D; Bowie, D A; Hergenrather, K C

    2003-01-01

    To identify and describe advantages, challenges, and ethical considerations of web based behavioural data collection. This discussion is based on the authors' experiences in survey development and study design, respondent recruitment, and internet research, and on the experiences of others as found in the literature. The advantages of using the world wide web to collect behavioural data include rapid access to numerous potential respondents and previously hidden populations, respondent openness and full participation, opportunities for student research, and reduced research costs. Challenges identified include issues related to sampling and sample representativeness, competition for the attention of respondents, and potential limitations resulting from the much cited "digital divide", literacy, and disability. Ethical considerations include anonymity and privacy, providing and substantiating informed consent, and potential risks of malfeasance. Computer mediated communications, including electronic mail, the world wide web, and interactive programs will play an ever increasing part in the future of behavioural science research. Justifiable concerns regarding the use of the world wide web in research exist, but as access to, and use of, the internet becomes more widely and representatively distributed globally, the world wide web will become more applicable. In fact, the world wide web may be the only research tool able to reach some previously hidden population subgroups. Furthermore, many of the criticisms of online data collection are common to other survey research methodologies.

  2. Transforming paper-based assessment forms to a digital format: Exemplified by the Housing Enabler prototype app.

    Science.gov (United States)

    Svarre, Tanja; Lunn, Tine Bieber Kirkegaard; Helle, Tina

    2017-11-01

    The aim of this paper is to provide the reader with an overall impression of the stepwise user-centred design approach including the specific methods used and lessons learned when transforming paper-based assessment forms into a prototype app, taking the Housing Enabler as an example. Four design iterations were performed, building on a domain study, workshops, expert evaluation and controlled and realistic usability tests. The user-centred design process involved purposefully selected participants with different Housing Enabler knowledge and housing adaptation experience. The design iterations resulted in the development of a Housing Enabler prototype app. The prototype app has several features and options that are new compared with the original paper-based Housing Enabler assessment form. These new features include a user friendly overview of the assessment form; easy navigation by swiping back and forth between items; onsite data analysis; and ranking of the accessibility score, photo documentation and a data export facility. Based on the presented stepwise approach, a high-fidelity Housing Enabler prototype app was successfully developed. The development process has emphasized the importance of combining design participants' knowledge and experiences, and has shown that methods should seem relevant to participants to increase their engagement.

  3. GNSS CORS hardware and software enabling new science

    Science.gov (United States)

    Drummond, P.

    2009-12-01

    GNSS CORS networks are enabling new opportunities for science and public and private sector business. This paper will explore how the newest geodetic monitoring software and GNSS receiver hardware from Trimble Navigation Ltd are enabling new science. Technology trends and science opportunities will be explored. These trends include the installation of active GNSS control, automation of observations and processing, and the advantages of multi-observable and multi-constellation observations, all performed with the use of off the shelf products and industry standard open-source data formats. Also the possibilities with moving science from an after-the-fact postprocessed model to a real-time epoch-by-epoch solution will be explored. This presentation will also discuss the combination of existing GNSS CORS networks with project specific installations used for monitoring. Experience is showing GNSS is able to provide higher resolution data than previous methods, providing new tools for science, decision makers and financial planners.

  4. Designing Summer Research Experiences for Teachers and Students That Promote Classroom Science Inquiry Projects and Produce Research Results

    Science.gov (United States)

    George, L. A.; Parra, J.; Rao, M.; Offerman, L.

    2007-12-01

    Research experiences for science teachers are an important mechanism for increasing classroom teachers' science content knowledge and facility with "real world" research processes. We have developed and implemented a summer scientific research and education workshop model for high school teachers and students which promotes classroom science inquiry projects and produces important research results supporting our overarching scientific agenda. The summer training includes development of a scientific research framework, design and implementation of preliminary studies, extensive field research and training in and access to instruments, measurement techniques and statistical tools. The development and writing of scientific papers is used to reinforce the scientific research process. Using these skills, participants collaborate with scientists to produce research quality data and analysis. Following the summer experience, teachers report increased incorporation of research inquiry in their classrooms and student participation in science fair projects. This workshop format was developed for an NSF Biocomplexity Research program focused on the interaction of urban climates, air quality and human response and can be easily adapted for other scientific research projects.

  5. Research in Brief: Using Mobile Phones to Collect Daily Experience Data from College Undergraduates

    Science.gov (United States)

    Ravert, Russell D.; Calix, Shaun I.; Sullivan, Michael J.

    2010-01-01

    As mobile phone use and text messaging has continued to play a more central role in people's daily lives, some researchers and clinicians have sought to use the medium as a tool for interventions and data collection. Such efforts have included sending tailored health messages to college students who are trying to quit smoking. This research brief…

  6. SciDAC visualization and analytics center for enabling technology

    International Nuclear Information System (INIS)

    Bethel, E Wes; Johnson, Chris; Joy, Ken; Ahern, Sean; Pascucci, Valerio; Childs, Hank; Cohen, Jonathan; Duchaineau, Mark; Hamann, Bernd; Hansen, Charles; Laney, Dan; Lindstrom, Peter; Meredith, Jeremy; Ostrouchov, George; Parker, Steven; Silva, Claudio; Sanderson, Allen; Tricoche, Xavier

    2007-01-01

    The Visualization and Analytics Center for Enabling Technologies (VACET) focuses on leveraging scientific visualization and analytics software technology as an enabling technology for increasing scientific productivity and insight. Advances in computational technology have resulted in an 'information big bang,' which in turn has created a significant data understanding challenge. This challenge is widely acknowledged to be one of the primary bottlenecks in contemporary science. The vision of VACET is to adapt, extend, create when necessary, and deploy visual data analysis solutions that are responsive to the needs of DOE's computational and experimental scientists. Our center is engineered to be directly responsive to those needs and to deliver solutions for use in DOE's large open computing facilities. The research and development directly target data understanding problems provided by our scientific application stakeholders. VACET draws from a diverse set of visualization technology ranging from production quality applications and application frameworks to state-of-the-art algorithms for visualization, analysis, analytics, data manipulation, and data management

  7. tranSMART: An Open Source and Community-Driven Informatics and Data Sharing Platform for Clinical and Translational Research.

    Science.gov (United States)

    Athey, Brian D; Braxenthaler, Michael; Haas, Magali; Guo, Yike

    2013-01-01

    tranSMART is an emerging global open source public private partnership community developing a comprehensive informatics-based analysis and data-sharing cloud platform for clinical and translational research. The tranSMART consortium includes pharmaceutical and other companies, not-for-profits, academic entities, patient advocacy groups, and government stakeholders. The tranSMART value proposition relies on the concept that the global community of users, developers, and stakeholders are the best source of innovation for applications and for useful data. Continued development and use of the tranSMART platform will create a means to enable "pre-competitive" data sharing broadly, saving money and, potentially accelerating research translation to cures. Significant transformative effects of tranSMART includes 1) allowing for all its user community to benefit from experts globally, 2) capturing the best of innovation in analytic tools, 3) a growing 'big data' resource, 4) convergent standards, and 5) new informatics-enabled translational science in the pharma, academic, and not-for-profit sectors.

  8. Enabling smart retail settings via mobile augmented reality shopping apps

    OpenAIRE

    Dacko, Scott

    2017-01-01

    Retail settings are being challenged to become smarter and provide greater value to both consumers and retailers. An increasingly recognised approach having potential for enabling smart retail is mobile augmented reality (MAR) apps. In this research, we seek to describe and discover how, why and to what extent MAR apps contribute to smart retail settings by creating additional value to customers as well as benefiting retailers. In particular, by adopting a retail customer experience perspecti...

  9. Tracking Research Data Footprints via Integration with Research Graph

    Science.gov (United States)

    Evans, B. J. K.; Wang, J.; Aryani, A.; Conlon, M.; Wyborn, L. A.; Choudhury, S. A.

    2017-12-01

    The researcher of today is likely to be part of a team that will use subsets of data from at least one, if not more external repositories, and that same data could be used by multiple researchers for many different purposes. At best, the repositories that host this data will know who is accessing their data, but rarely what they are using it for, resulting in funders of data collecting programs and data repositories that store the data unlikely to know: 1) which research funding contributed to the collection and preservation of a dataset, and 2) which data contributed to high impact research and publications. In days of funding shortages there is a growing need to be able to trace the footprint a data set from the originator