Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling

Energy Technology Data Exchange (ETDEWEB)

Schussman, Greg; /SLAC

2010-08-25

In the Phase I SBIR we proposed a ParaView-based solution to provide an environment for individuals to actively collaborate in the visualization process. The technical objectives of Phase I were: (1) to determine the set of features required for an effect collaborative system; (2) to implement a two-person collaborative prototype; and (3) to implement key collaborative features such as control locking and annotation. Accordingly, we implemented a ParaView-based collaboration prototype with support for collaborating with up to four simultaneous clients. We also implemented collaborative features such as control locking, chatting, annotation etc. Due to in part of the flexibility provided by the ParaView framework and the design features implemented in the prototype, we were able to support collaboration with multiple views, instead of a simple give as initially proposed in Phase I. In this section we will summarize the results we obtained during the Phase I project. ParaView is complex, scalable, client-server application framework built on top of the VTK visualization engine. During the implementation of the Phase I prototype, we realized that the ParaView framework naturally supports collaboration technology; hence we were able to go beyond the proposed Phase I prototype in several ways. For example, we were able to support for multiple views, enable server-as well as client-side rendering, and manage up to four heterogeneous clients. The success we achieved with Phase I clearly demonstrated the technical feasibility of the ParaView based collaborative framework we are proposing in the Phase II effort. We also investigated using the web browser as one of the means of participating in a collaborative session. This would enable non-visualization experts to participate in the collaboration process without being intimidated by a complex application such as ParaView. Hence we also developed a prototype web visualization applet that makes it possible for interactive

Supporting interactive visual analytics of energy behavior in buildings through affine visualizations

DEFF Research Database (Denmark)

Nielsen, Matthias; Brewer, Robert S.; Grønbæk, Kaj

2016-01-01

Domain experts dealing with big data are typically not familiar with advanced data mining tools. This especially holds true for domain experts within energy management. In this paper, we introduce a visual analytics approach that empowers such users to visually analyze energy behavior based......Viz, that interactively maps data from real world buildings. It is an overview +detail inter-active visual analytics tool supporting both rapid ad hoc explorations and structured evaluation of hypotheses about patterns and anomalies in resource consumption data mixed with occupant survey data. We have evaluated...... the approach with five domain experts within energy management, and further with 10 data analytics experts and found that it was easily attainable and that it supported visual analysis of mixed consumption and survey data. Finally, we discuss future perspectives of affine visual analytics for mixed...

Rethinking Visual Analytics for Streaming Data Applications

Energy Technology Data Exchange (ETDEWEB)

Crouser, R. Jordan; Franklin, Lyndsey; Cook, Kris

2017-01-01

In the age of data science, the use of interactive information visualization techniques has become increasingly ubiquitous. From online scientific journals to the New York Times graphics desk, the utility of interactive visualization for both storytelling and analysis has become ever more apparent. As these techniques have become more readily accessible, the appeal of combining interactive visualization with computational analysis continues to grow. Arising out of a need for scalable, human-driven analysis, primary objective of visual analytics systems is to capitalize on the complementary strengths of human and machine analysis, using interactive visualization as a medium for communication between the two. These systems leverage developments from the fields of information visualization, computer graphics, machine learning, and human-computer interaction to support insight generation in areas where purely computational analyses fall short. Over the past decade, visual analytics systems have generated remarkable advances in many historically challenging analytical contexts. These include areas such as modeling political systems [Crouser et al. 2012], detecting financial fraud [Chang et al. 2008], and cybersecurity [Harrison et al. 2012]. In each of these contexts, domain expertise and human intuition is a necessary component of the analysis. This intuition is essential to building trust in the analytical products, as well as supporting the translation of evidence into actionable insight. In addition, each of these examples also highlights the need for scalable analysis. In each case, it is infeasible for a human analyst to manually assess the raw information unaided, and the communication overhead to divide the task between a large number of analysts makes simple parallelism intractable. Regardless of the domain, visual analytics tools strive to optimize the allocation of human analytical resources, and to streamline the sensemaking process on data that is massive

Rocinante, a virtual collaborative visualizer

International Nuclear Information System (INIS)

McDonald, M.J.

1996-01-01

With the goal of improving the ability of people around the world to share the development and use of intelligent systems, Sandia National Laboratories' Intelligent Systems and Robotics Center is developing new Virtual Collaborative Engineering (VCE) and Virtual Collaborative Control (VCC) technologies. A key area of VCE and VCC research is in shared visualization of virtual environments. This paper describes a Virtual Collaborative Visualizer (VCV), named Rocinante, that Sandia developed for VCE and VCC applications. Rocinante allows multiple participants to simultaneously view dynamic geometrically-defined environments. Each viewer can exclude extraneous detail or include additional information in the scene as desired. Shared information can be saved and later replayed in a stand-alone mode. Rocinante automatically scales visualization requirements with computer system capabilities. Models with 30,000 polygons and 4 Megabytes of texture display at 12 to 15 frames per second (fps) on an SGI Onyx and at 3 to 8 fps (without texture) on Indigo 2 Extreme computers. In its networked mode, Rocinante synchronizes its local geometric model with remote simulators and sensory systems by monitoring data transmitted through UDP packets. Rocinante's scalability and performance make it an ideal VCC tool. Users throughout the country can monitor robot motions and the thinking behind their motion planners and simulators

Rocinante, a virtual collaborative visualizer

Energy Technology Data Exchange (ETDEWEB)

McDonald, M.J. [Sandia National Labs., Albuquerque, NM (United States). Intelligent Systems and Robotics Center; Ice, L.G. [Univ. of New Mexico, Albuquerque, NM (United States)

1996-12-31

With the goal of improving the ability of people around the world to share the development and use of intelligent systems, Sandia National Laboratories` Intelligent Systems and Robotics Center is developing new Virtual Collaborative Engineering (VCE) and Virtual Collaborative Control (VCC) technologies. A key area of VCE and VCC research is in shared visualization of virtual environments. This paper describes a Virtual Collaborative Visualizer (VCV), named Rocinante, that Sandia developed for VCE and VCC applications. Rocinante allows multiple participants to simultaneously view dynamic geometrically-defined environments. Each viewer can exclude extraneous detail or include additional information in the scene as desired. Shared information can be saved and later replayed in a stand-alone mode. Rocinante automatically scales visualization requirements with computer system capabilities. Models with 30,000 polygons and 4 Megabytes of texture display at 12 to 15 frames per second (fps) on an SGI Onyx and at 3 to 8 fps (without texture) on Indigo 2 Extreme computers. In its networked mode, Rocinante synchronizes its local geometric model with remote simulators and sensory systems by monitoring data transmitted through UDP packets. Rocinante`s scalability and performance make it an ideal VCC tool. Users throughout the country can monitor robot motions and the thinking behind their motion planners and simulators.

Visual Analytics for MOOC Data.

Science.gov (United States)

Qu, Huamin; Chen, Qing

2015-01-01

With the rise of massive open online courses (MOOCs), tens of millions of learners can now enroll in more than 1,000 courses via MOOC platforms such as Coursera and edX. As a result, a huge amount of data has been collected. Compared with traditional education records, the data from MOOCs has much finer granularity and also contains new pieces of information. It is the first time in history that such comprehensive data related to learning behavior has become available for analysis. What roles can visual analytics play in this MOOC movement? The authors survey the current practice and argue that MOOCs provide an opportunity for visualization researchers and that visual analytics systems for MOOCs can benefit a range of end users such as course instructors, education researchers, students, university administrators, and MOOC providers.

Towards Collaborative Data Analytics for Smart Buildings

DEFF Research Database (Denmark)

Lazarova-Molnar, Sanja; Mohamed, Nader

2017-01-01

Smart buildings are buildings equipped with the latest technological and architectural solutions, controlled by Building Management Systems (BMS), operating in fulfillment of the typical goals of increasing occupants’ comfort and reducing buildings’ energy consumption. We witness a slow...... buildings that is available for further analytics to support meeting BMS’ performance goals. For a single building to benefit from this data-based analytics, it will take a long time. Collaboration of BMS in their data analytics processes can significantly shorten this time period. This paper makes two...

A graph algebra for scalable visual analytics.

Science.gov (United States)

Shaverdian, Anna A; Zhou, Hao; Michailidis, George; Jagadish, Hosagrahar V

2012-01-01

Visual analytics (VA), which combines analytical techniques with advanced visualization features, is fast becoming a standard tool for extracting information from graph data. Researchers have developed many tools for this purpose, suggesting a need for formal methods to guide these tools' creation. Increased data demands on computing requires redesigning VA tools to consider performance and reliability in the context of analysis of exascale datasets. Furthermore, visual analysts need a way to document their analyses for reuse and results justification. A VA graph framework encapsulated in a graph algebra helps address these needs. Its atomic operators include selection and aggregation. The framework employs a visual operator and supports dynamic attributes of data to enable scalable visual exploration of data.

Mixed Initiative Visual Analytics Using Task-Driven Recommendations

Energy Technology Data Exchange (ETDEWEB)

Cook, Kristin A.; Cramer, Nicholas O.; Israel, David; Wolverton, Michael J.; Bruce, Joseph R.; Burtner, Edwin R.; Endert, Alexander

2015-12-07

Visual data analysis is composed of a collection of cognitive actions and tasks to decompose, internalize, and recombine data to produce knowledge and insight. Visual analytic tools provide interactive visual interfaces to data to support tasks involved in discovery and sensemaking, including forming hypotheses, asking questions, and evaluating and organizing evidence. Myriad analytic models can be incorporated into visual analytic systems, at the cost of increasing complexity in the analytic discourse between user and system. Techniques exist to increase the usability of interacting with such analytic models, such as inferring data models from user interactions to steer the underlying models of the system via semantic interaction, shielding users from having to do so explicitly. Such approaches are often also referred to as mixed-initiative systems. Researchers studying the sensemaking process have called for development of tools that facilitate analytic sensemaking through a combination of human and automated activities. However, design guidelines do not exist for mixed-initiative visual analytic systems to support iterative sensemaking. In this paper, we present a candidate set of design guidelines and introduce the Active Data Environment (ADE) prototype, a spatial workspace supporting the analytic process via task recommendations invoked by inferences on user interactions within the workspace. ADE recommends data and relationships based on a task model, enabling users to co-reason with the system about their data in a single, spatial workspace. This paper provides an illustrative use case, a technical description of ADE, and a discussion of the strengths and limitations of the approach.

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

International Nuclear Information System (INIS)

Schroeder, William J.

2011-01-01

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannot be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally-intensive problem

Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling (Final Report)

Energy Technology Data Exchange (ETDEWEB)

William J. Schroeder

2011-11-13

This report contains the comprehensive summary of the work performed on the SBIR Phase II, Collaborative Visualization for Large-Scale Accelerator Electromagnetic Modeling at Kitware Inc. in collaboration with Stanford Linear Accelerator Center (SLAC). The goal of the work was to develop collaborative visualization tools for large-scale data as illustrated in the figure below. The solutions we proposed address the typical problems faced by geographicallyand organizationally-separated research and engineering teams, who produce large data (either through simulation or experimental measurement) and wish to work together to analyze and understand their data. Because the data is large, we expect that it cannot be easily transported to each team member's work site, and that the visualization server must reside near the data. Further, we also expect that each work site has heterogeneous resources: some with large computing clients, tiled (or large) displays and high bandwidth; others sites as simple as a team member on a laptop computer. Our solution is based on the open-source, widely used ParaView large-data visualization application. We extended this tool to support multiple collaborative clients who may locally visualize data, and then periodically rejoin and synchronize with the group to discuss their findings. Options for managing session control, adding annotation, and defining the visualization pipeline, among others, were incorporated. We also developed and deployed a Web visualization framework based on ParaView that enables the Web browser to act as a participating client in a collaborative session. The ParaView Web Visualization framework leverages various Web technologies including WebGL, JavaScript, Java and Flash to enable interactive 3D visualization over the web using ParaView as the visualization server. We steered the development of this technology by teaming with the SLAC National Accelerator Laboratory. SLAC has a computationally

Musician Map: visualizing music collaborations over time

Science.gov (United States)

Yim, Ji-Dong; Shaw, Chris D.; Bartram, Lyn

2009-01-01

In this paper we introduce Musician Map, a web-based interactive tool for visualizing relationships among popular musicians who have released recordings since 1950. Musician Map accepts search terms from the user, and in turn uses these terms to retrieve data from MusicBrainz.org and AudioScrobbler.net, and visualizes the results. Musician Map visualizes relationships of various kinds between music groups and individual musicians, such as band membership, musical collaborations, and linkage to other artists that are generally regarded as being similar in musical style. These relationships are plotted between artists using a new timeline-based visualization where a node in a traditional node-link diagram has been transformed into a Timeline-Node, which allows the visualization of an evolving entity over time, such as the membership in a band. This allows the user to pursue social trend queries such as "Do Hip-Hop artists collaborate differently than Rock artists".

The Evolving Leadership Path of Visual Analytics

Energy Technology Data Exchange (ETDEWEB)

Kluse, Michael; Peurrung, Anthony J.; Gracio, Deborah K.

2012-01-02

This is a requested book chapter for an internationally authored book on visual analytics and related fields, coordianted by a UK university and to be published by Springer in 2012. This chapter is an overview of the leadship strategies that PNNL's Jim Thomas and other stakeholders used to establish visual analytics as a field, and how those strategies may evolve in the future.

A Tool Supporting Collaborative Data Analytics Workflow Design and Management

Science.gov (United States)

Zhang, J.; Bao, Q.; Lee, T. J.

2016-12-01

Collaborative experiment design could significantly enhance the sharing and adoption of the data analytics algorithms and models emerged in Earth science. Existing data-oriented workflow tools, however, are not suitable to support collaborative design of such a workflow, to name a few, to support real-time co-design; to track how a workflow evolves over time based on changing designs contributed by multiple Earth scientists; and to capture and retrieve collaboration knowledge on workflow design (discussions that lead to a design). To address the aforementioned challenges, we have designed and developed a technique supporting collaborative data-oriented workflow composition and management, as a key component toward supporting big data collaboration through the Internet. Reproducibility and scalability are two major targets demanding fundamental infrastructural support. One outcome of the project os a software tool, supporting an elastic number of groups of Earth scientists to collaboratively design and compose data analytics workflows through the Internet. Instead of recreating the wheel, we have extended an existing workflow tool VisTrails into an online collaborative environment as a proof of concept.

Visualization analysis of author collaborations in schizophrenia research.

Science.gov (United States)

Wu, Ying; Duan, Zhiguang

2015-02-19

Schizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research. This study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from Science Citation Index Expanded (SCI Expanded) via Web of Science. CiteSpace III, an information visualization and analysis software, was used to make a visual analysis. Collaborative author networks within the field of schizophrenia were determined using published documents. We found that external author collaboration networks were more scattered while potential author collaboration networks were more compact. Results from hierarchical clustering analysis showed that the main collaborative field was genetic research in schizophrenia. Based on the results, authors belonging to different institutions and in different countries should be encouraged to collaborate in schizophrenia research. This will help researchers focus their studies on key issues, and allow each other to offer reasonable suggestions for making polices and providing scientific evidence to effectively diagnose, prevent, and cure schizophrenia.

Visual Analytics and Storytelling through Video

Energy Technology Data Exchange (ETDEWEB)

Wong, Pak C.; Perrine, Kenneth A.; Mackey, Patrick S.; Foote, Harlan P.; Thomas, Jim

2005-10-31

This paper supplements a video clip submitted to the Video Track of IEEE Symposium on Information Visualization 2005. The original video submission applies a two-way storytelling approach to demonstrate the visual analytics capabilities of a new visualization technique. The paper presents our video production philosophy, describes the plot of the video, explains the rationale behind the plot, and finally, shares our production experiences with our readers.

TrajAnalytics: An Open-Source, Web-Based Visual Analytics Software of Urban Trajectory Data

OpenAIRE

Zhao, Ye

2018-01-01

We developed a software system named TrajAnalytics, which explicitly supports interactive visual analytics of the emerging trajectory data. It offers data management capability and support various data queries by leveraging web-based computing platforms. It allows users to visually conduct queries and make sense of massive trajectory data.

The Case for Visual Analytics of Arsenic Concentrations in Foods

Directory of Open Access Journals (Sweden)

Omotayo R. Awofolu

2010-04-01

Full Text Available Arsenic is a naturally occurring toxic metal and its presence in food could be a potential risk to the health of both humans and animals. Prolonged ingestion of arsenic contaminated water may result in manifestations of toxicity in all systems of the body. Visual Analytics is a multidisciplinary field that is defined as the science of analytical reasoning facilitated by interactive visual interfaces. The concentrations of arsenic vary in foods making it impractical and impossible to provide regulatory limit for each food. This review article presents a case for the use of visual analytics approaches to provide comparative assessment of arsenic in various foods. The topics covered include (i metabolism of arsenic in the human body; (ii arsenic concentrations in various foods; (ii factors affecting arsenic uptake in plants; (ii introduction to visual analytics; and (iv benefits of visual analytics for comparative assessment of arsenic concentration in foods. Visual analytics can provide an information superstructure of arsenic in various foods to permit insightful comparative risk assessment of the diverse and continually expanding data on arsenic in food groups in the context of country of study or origin, year of study, method of analysis and arsenic species.

SeeDB: Efficient Data-Driven Visualization Recommendations to Support Visual Analytics.

Science.gov (United States)

Vartak, Manasi; Rahman, Sajjadur; Madden, Samuel; Parameswaran, Aditya; Polyzotis, Neoklis

2015-09-01

Data analysts often build visualizations as the first step in their analytical workflow. However, when working with high-dimensional datasets, identifying visualizations that show relevant or desired trends in data can be laborious. We propose SeeDB, a visualization recommendation engine to facilitate fast visual analysis: given a subset of data to be studied, SeeDB intelligently explores the space of visualizations, evaluates promising visualizations for trends, and recommends those it deems most "useful" or "interesting". The two major obstacles in recommending interesting visualizations are (a) scale : evaluating a large number of candidate visualizations while responding within interactive time scales, and (b) utility : identifying an appropriate metric for assessing interestingness of visualizations. For the former, SeeDB introduces pruning optimizations to quickly identify high-utility visualizations and sharing optimizations to maximize sharing of computation across visualizations. For the latter, as a first step, we adopt a deviation-based metric for visualization utility, while indicating how we may be able to generalize it to other factors influencing utility. We implement SeeDB as a middleware layer that can run on top of any DBMS. Our experiments show that our framework can identify interesting visualizations with high accuracy. Our optimizations lead to multiple orders of magnitude speedup on relational row and column stores and provide recommendations at interactive time scales. Finally, we demonstrate via a user study the effectiveness of our deviation-based utility metric and the value of recommendations in supporting visual analytics.

Interactive Collaborative Visualization in the Geosciences

Science.gov (United States)

Bollig, E. F.; Kadlec, B. J.; Erlebacher, G.; Yuen, D. A.; Palchuk, Y. M.

2004-12-01

Datasets in the earth sciences continue growing in size due to higher experimental resolving power, and numerical simulations at higher resolutions. Over the last several years, an increasing number of scientists have turned to visualization to represent their vast datasets in a meaningful fashion. In most cases, datasets are downloaded and then visualized on a local workstation with 2D or 3D software packages. However, it becomes inconvenient to download datasets of several gigabytes unless network bandwidth is sufficiently high (10 Gbits/sec). We are investigating the use of Virtual Network Computing (VNC) to provide interactive three-dimensional visualization services to the user community. Specialized software [1,2] enables OpenGL-based visualization software to capitalize on the hardware capabilities of modern graphics cards and transfer session information to clients through the VNC protocol. The virtue of this software is that it does not require any changes to visualization software. Session information is displayed within java applets, enabling the use of a wide variety of clients, including hand-held devices. The VNC protocol makes collaboration and interaction between multiple users possible. We demonstrate the collaborative VNC system with the commercial 3D visualization system Amira (http://www.tgs.com) and the open source VTK (http://www.vtk.org) over a 100 Mbit network. We also present ongoing work for integrating VNC within the Naradabrokering Grid environment. [1] Stegmaier, S. and Magallon, M. and T. Ertl, "A Generic Solution for Hardware-Accelerated Remote Visualization," Joint Eurographics -- IEEE TCVG Symposium on Visualization, 2002. [2] VirtualGL--3D without boundaries http://virtualgl.sourceforge.net/installation.htm

Web-based Visual Analytics for Extreme Scale Climate Science

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; Evans, Katherine J [ORNL; Harney, John F [ORNL; Jewell, Brian C [ORNL; Shipman, Galen M [ORNL; Smith, Brian E [ORNL; Thornton, Peter E [ORNL; Williams, Dean N. [Lawrence Livermore National Laboratory (LLNL)

2014-01-01

In this paper, we introduce a Web-based visual analytics framework for democratizing advanced visualization and analysis capabilities pertinent to large-scale earth system simulations. We address significant limitations of present climate data analysis tools such as tightly coupled dependencies, ineffi- cient data movements, complex user interfaces, and static visualizations. Our Web-based visual analytics framework removes critical barriers to the widespread accessibility and adoption of advanced scientific techniques. Using distributed connections to back-end diagnostics, we minimize data movements and leverage HPC platforms. We also mitigate system dependency issues by employing a RESTful interface. Our framework embraces the visual analytics paradigm via new visual navigation techniques for hierarchical parameter spaces, multi-scale representations, and interactive spatio-temporal data mining methods that retain details. Although generalizable to other science domains, the current work focuses on improving exploratory analysis of large-scale Community Land Model (CLM) and Community Atmosphere Model (CAM) simulations.

Approximated and User Steerable tSNE for Progressive Visual Analytics

NARCIS (Netherlands)

Pezzotti, N.; Lelieveldt, B.P.F.; van der Maaten, L.J.P.; Hollt, T.; Eisemann, E.; Vilanova Bartroli, A.

2016-01-01

Progressive Visual Analytics aims at improving the interactivity in existing analytics techniques by means of visualization as well as interaction with intermediate results. One key method for data analysis is dimensionality reduction, for example, to produce 2D embeddings that can be visualized and

Applying Pragmatics Principles for Interaction with Visual Analytics.

Science.gov (United States)

Hoque, Enamul; Setlur, Vidya; Tory, Melanie; Dykeman, Isaac

2018-01-01

Interactive visual data analysis is most productive when users can focus on answering the questions they have about their data, rather than focusing on how to operate the interface to the analysis tool. One viable approach to engaging users in interactive conversations with their data is a natural language interface to visualizations. These interfaces have the potential to be both more expressive and more accessible than other interaction paradigms. We explore how principles from language pragmatics can be applied to the flow of visual analytical conversations, using natural language as an input modality. We evaluate the effectiveness of pragmatics support in our system Evizeon, and present design considerations for conversation interfaces to visual analytics tools.

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

TideGrapher: Visual Analytics of Tactical Situations for Rugby Matches

Directory of Open Access Journals (Sweden)

Yusuke Ishikawa

2018-03-01

Full Text Available Various attempts at exploiting information visualization for sports have recently been reported in the literature, although it is still challenging to analyze continuous ball matches. In this paper, we propose a novel visual analytics system, called TideGrapher, to track the transition of tactile situations in a rugby match. With a particular focus on the side position of the ball, we designed a dedicated spatial substrate based on the spatio-temporal trajectory of the ball and provided a set of basic interactions. Quantitative analysis was strengthened by adding a new index, called initiative, to commonly used possession (ball occupation and territory (dominance of territory. The feasibility of the proposed visual analytics system was proven empirically through application to datasets from real amateur and professional matches. Keywords: Information visualization, Sports visualization, Quantitative analysis, Visual analytics

NECTAR: Simulation and Visualization in a 3D Collaborative Environment

NARCIS (Netherlands)

Law, Y.W.; Chan, K.Y.

For simulation and visualization in a 3D collaborative environment, an architecture called the Nanyang Experimental CollaboraTive ARchitecture (NECTAR) has been developed. The objective is to support multi-user collaboration in a virtual environment with an emphasis on cost-effectiveness and

Visual analytics in medical education: impacting analytical reasoning and decision making for quality improvement.

Science.gov (United States)

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2015-01-01

The medical curriculum is the main tool representing the entire undergraduate medical education. Due to its complexity and multilayered structure it is of limited use to teachers in medical education for quality improvement purposes. In this study we evaluated three visualizations of curriculum data from a pilot course, using teachers from an undergraduate medical program and applying visual analytics methods. We found that visual analytics can be used to positively impacting analytical reasoning and decision making in medical education through the realization of variables capable to enhance human perception and cognition on complex curriculum data. The positive results derived from our evaluation of a medical curriculum and in a small scale, signify the need to expand this method to an entire medical curriculum. As our approach sustains low levels of complexity it opens a new promising direction in medical education informatics research.

Real-time analytics techniques to analyze and visualize streaming data

CERN Document Server

Ellis, Byron

2014-01-01

Construct a robust end-to-end solution for analyzing and visualizing streaming data Real-time analytics is the hottest topic in data analytics today. In Real-Time Analytics: Techniques to Analyze and Visualize Streaming Data, expert Byron Ellis teaches data analysts technologies to build an effective real-time analytics platform. This platform can then be used to make sense of the constantly changing data that is beginning to outpace traditional batch-based analysis platforms. The author is among a very few leading experts in the field. He has a prestigious background in research, development,

Case Study : Visual Analytics in Software Product Assessments

NARCIS (Netherlands)

Telea, Alexandru; Voinea, Lucian; Lanza, M; Storey, M; Muller, H

2009-01-01

We present how a combination of static source code analysis, repository analysis, and visualization techniques has been used to effectively get and communicate insight in the development and project management problems of a large industrial code base. This study is an example of how visual analytics

VRML and Collaborative Environments: New Tools for Networked Visualization

Science.gov (United States)

Crutcher, R. M.; Plante, R. L.; Rajlich, P.

We present two new applications that engage the network as a tool for astronomical research and/or education. The first is a VRML server which allows users over the Web to interactively create three-dimensional visualizations of FITS images contained in the NCSA Astronomy Digital Image Library (ADIL). The server's Web interface allows users to select images from the ADIL, fill in processing parameters, and create renderings featuring isosurfaces, slices, contours, and annotations; the often extensive computations are carried out on an NCSA SGI supercomputer server without the user having an individual account on the system. The user can then download the 3D visualizations as VRML files, which may be rotated and manipulated locally on virtually any class of computer. The second application is the ADILBrowser, a part of the NCSA Horizon Image Data Browser Java package. ADILBrowser allows a group of participants to browse images from the ADIL within a collaborative session. The collaborative environment is provided by the NCSA Habanero package which includes text and audio chat tools and a white board. The ADILBrowser is just an example of a collaborative tool that can be built with the Horizon and Habanero packages. The classes provided by these packages can be assembled to create custom collaborative applications that visualize data either from local disk or from anywhere on the network.

IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics.

Science.gov (United States)

Hoyt, Robert Eugene; Snider, Dallas; Thompson, Carla; Mantravadi, Sarita

2016-10-11

We live in an era of explosive data generation that will continue to grow and involve all industries. One of the results of this explosion is the need for newer and more efficient data analytics procedures. Traditionally, data analytics required a substantial background in statistics and computer science. In 2015, International Business Machines Corporation (IBM) released the IBM Watson Analytics (IBMWA) software that delivered advanced statistical procedures based on the Statistical Package for the Social Sciences (SPSS). The latest entry of Watson Analytics into the field of analytical software products provides users with enhanced functions that are not available in many existing programs. For example, Watson Analytics automatically analyzes datasets, examines data quality, and determines the optimal statistical approach. Users can request exploratory, predictive, and visual analytics. Using natural language processing (NLP), users are able to submit additional questions for analyses in a quick response format. This analytical package is available free to academic institutions (faculty and students) that plan to use the tools for noncommercial purposes. To report the features of IBMWA and discuss how this software subjectively and objectively compares to other data mining programs. The salient features of the IBMWA program were examined and compared with other common analytical platforms, using validated health datasets. Using a validated dataset, IBMWA delivered similar predictions compared with several commercial and open source data mining software applications. The visual analytics generated by IBMWA were similar to results from programs such as Microsoft Excel and Tableau Software. In addition, assistance with data preprocessing and data exploration was an inherent component of the IBMWA application. Sensitivity and specificity were not included in the IBMWA predictive analytics results, nor were odds ratios, confidence intervals, or a confusion matrix

GenoSets: visual analytic methods for comparative genomics.

Directory of Open Access Journals (Sweden)

Aurora A Cain

Full Text Available Many important questions in biology are, fundamentally, comparative, and this extends to our analysis of a growing number of sequenced genomes. Existing genomic analysis tools are often organized around literal views of genomes as linear strings. Even when information is highly condensed, these views grow cumbersome as larger numbers of genomes are added. Data aggregation and summarization methods from the field of visual analytics can provide abstracted comparative views, suitable for sifting large multi-genome datasets to identify critical similarities and differences. We introduce a software system for visual analysis of comparative genomics data. The system automates the process of data integration, and provides the analysis platform to identify and explore features of interest within these large datasets. GenoSets borrows techniques from business intelligence and visual analytics to provide a rich interface of interactive visualizations supported by a multi-dimensional data warehouse. In GenoSets, visual analytic approaches are used to enable querying based on orthology, functional assignment, and taxonomic or user-defined groupings of genomes. GenoSets links this information together with coordinated, interactive visualizations for both detailed and high-level categorical analysis of summarized data. GenoSets has been designed to simplify the exploration of multiple genome datasets and to facilitate reasoning about genomic comparisons. Case examples are included showing the use of this system in the analysis of 12 Brucella genomes. GenoSets software and the case study dataset are freely available at http://genosets.uncc.edu. We demonstrate that the integration of genomic data using a coordinated multiple view approach can simplify the exploration of large comparative genomic data sets, and facilitate reasoning about comparisons and features of interest.

Art-Science-Technology collaboration through immersive, interactive 3D visualization

Science.gov (United States)

Kellogg, L. H.

2014-12-01

At the W. M. Keck Center for Active Visualization in Earth Sciences (KeckCAVES), a group of geoscientists and computer scientists collaborate to develop and use of interactive, immersive, 3D visualization technology to view, manipulate, and interpret data for scientific research. The visual impact of immersion in a CAVE environment can be extremely compelling, and from the outset KeckCAVES scientists have collaborated with artists to bring this technology to creative works, including theater and dance performance, installations, and gamification. The first full-fledged collaboration designed and produced a performance called "Collapse: Suddenly falling down", choreographed by Della Davidson, which investigated the human and cultural response to natural and man-made disasters. Scientific data (lidar scans of disaster sites, such as landslides and mine collapses) were fully integrated into the performance by the Sideshow Physical Theatre. This presentation will discuss both the technological and creative characteristics of, and lessons learned from the collaboration. Many parallels between the artistic and scientific process emerged. We observed that both artists and scientists set out to investigate a topic, solve a problem, or answer a question. Refining that question or problem is an essential part of both the creative and scientific workflow. Both artists and scientists seek understanding (in this case understanding of natural disasters). Differences also emerged; the group noted that the scientists sought clarity (including but not limited to quantitative measurements) as a means to understanding, while the artists embraced ambiguity, also as a means to understanding. Subsequent art-science-technology collaborations have responded to evolving technology for visualization and include gamification as a means to explore data, and use of augmented reality for informal learning in museum settings.

WetDATA Hub: Democratizing Access to Water Data to Accelerate Innovation through Data Visualization, Predictive Analytics and Artificial Intelligence Applications

Science.gov (United States)

Sarni, W.

2017-12-01

Water scarcity and poor quality impacts economic development, business growth, and social well-being. Water has become, in our generation, the foremost critical local, regional, and global issue of our time. Despite these needs, there is no water hub or water technology accelerator solely dedicated to water data and tools. There is a need by the public and private sectors for vastly improved data management and visualization tools. This is the WetDATA opportunity - to develop a water data tech hub dedicated to water data acquisition, analytics, and visualization tools for informed policy and business decisions. WetDATA's tools will help incubate disruptive water data technologies and accelerate adoption of current water data solutions. WetDATA is a Colorado-based (501c3), global hub for water data analytics and technology innovation. WetDATA's vision is to be a global leader in water information, data technology innovation and collaborate with other US and global water technology hubs. ROADMAP * Portal (www.wetdata.org) to provide stakeholders with tools/resources to understand related water risks. * The initial activities will provide education, awareness and tools to stakeholders to support the implementation of the Colorado State Water Plan. * Leverage the Western States Water Council Water Data Exchange database. * Development of visualization, predictive analytics and AI tools to engage with stakeholders and provide actionable data and information. TOOLS Education: Provide information on water issues and risks at the local, state, national and global scale. Visualizations: Development of data analytics and visualization tools based upon the 2030 Water Resources Group methodology to support the implementation of the Colorado State Water Plan. Predictive Analytics: Accessing publically available water databases and using machine learning to develop water availability forecasting tools, and time lapse images to support city / urban planning.

Towards academic generativity: working collaboratively with visual ...

African Journals Online (AJOL)

We follow this with a collaborative reflection, in which we explain how we have noticed similarities in both the connotative and denotative histories of our artefacts and gained an alternative perspective on our interests and practices as educational researchers. The article demonstrates how, by working with visual artefacts ...

SciDAC Visualization and Analytics Center for Enabling Technologies

Energy Technology Data Exchange (ETDEWEB)

Joy, Kenneth I. [Univ. of California, Davis, CA (United States)

2014-09-14

This project 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 for our Center is to respond directly to that challenge by adapting, extending, creating when necessary and deploying visualization and data understanding technologies for our science stakeholders. Using an organizational model as a Visualization and Analytics Center for Enabling Technologies (VACET), we are well positioned to be responsive to the needs of a diverse set of scientific stakeholders in a coordinated fashion using a range of visualization, mathematics, statistics, computer and computational science and data management technologies.

A Flexible Framework for Collaborative Visualization Applications using JAVASPACES

National Research Council Canada - National Science Library

Butler, Sean

2001-01-01

...(Trademark), a high-level network programming API. This thesis describes a tool for developing collaborative visualization software using JavaSpaces-an application framework and accompanying toolkit...

Guided Text Search Using Adaptive Visual Analytics

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; Symons, Christopher T [ORNL; Senter, James K [ORNL; DeNap, Frank A [ORNL

2012-10-01

This research demonstrates the promise of augmenting interactive visualizations with semi- supervised machine learning techniques to improve the discovery of significant associations and insights in the search and analysis of textual information. More specifically, we have developed a system called Gryffin that hosts a unique collection of techniques that facilitate individualized investigative search pertaining to an ever-changing set of analytical questions over an indexed collection of open-source documents related to critical national infrastructure. The Gryffin client hosts dynamic displays of the search results via focus+context record listings, temporal timelines, term-frequency views, and multiple coordinate views. Furthermore, as the analyst interacts with the display, the interactions are recorded and used to label the search records. These labeled records are then used to drive semi-supervised machine learning algorithms that re-rank the unlabeled search records such that potentially relevant records are moved to the top of the record listing. Gryffin is described in the context of the daily tasks encountered at the US Department of Homeland Security s Fusion Center, with whom we are collaborating in its development. The resulting system is capable of addressing the analysts information overload that can be directly attributed to the deluge of information that must be addressed in the search and investigative analysis of textual information.

Big data in medical informatics: improving education through visual analytics.

Science.gov (United States)

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

A continuous effort to improve healthcare education today is currently driven from the need to create competent health professionals able to meet healthcare demands. Limited research reporting how educational data manipulation can help in healthcare education improvement. The emerging research field of visual analytics has the advantage to combine big data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognise visual patterns. The aim of this study was therefore to explore novel ways of representing curriculum and educational data using visual analytics. Three approaches of visualization and representation of educational data were presented. Five competencies at undergraduate medical program level addressed in courses were identified to inaccurately correspond to higher education board competencies. Different visual representations seem to have a potential in impacting on the ability to perceive entities and connections in the curriculum data.

Geo-social visual analytics

Directory of Open Access Journals (Sweden)

Wei Luo

2014-06-01

Full Text Available Spatial analysis and social network analysis typically consider social processes in their own specific contexts, either geographical or network space. Both approaches demonstrate strong conceptual overlaps. For example, actors close to each other tend to have greater similarity than those far apart; this phenomenon has different labels in geography (spatial autocorrelation and in network science (homophily. In spite of those conceptual and observed overlaps, the integration of geography and social network context has not received the attention needed in order to develop a comprehensive understanding of their interaction or their impact on outcomes of interest, such as population health behaviors, information dissemination, or human behavior in a crisis. In order to address this gap, this paper discusses the integration of geographic with social network perspectives applied to understanding social processes in place from two levels: the theoretical level and the methodological level. At the theoretical level, this paper argues that the concepts of nearness and relationship in terms of a possible extension of the First Law of Geography are a matter of both geographical and social network distance, relationship, and interaction. At the methodological level, the integration of geography and social network contexts are framed within a new interdisciplinary field:~visual analytics, in which three major application-oriented subfields (data exploration, decision-making, and predictive analysis are used to organize discussion. In each subfield, this paper presents a theoretical framework first, and then reviews what has been achieved regarding geo-social visual analytics in order to identify potential future research.

Spatial Game Analytics and Visualization

DEFF Research Database (Denmark)

Drachen, Anders; Schubert, Matthias

2013-01-01

, techniques for spatial analysis had their share in these developments. However, the methods for analyzing and visualizing spatial and spatio-temporal patterns in player behavior being used by the game industry are not as diverse as the range of techniques utilized in game research, leaving room...... for a continuing development. This paper presents a review of current work on spatial and spatio-temporal game analytics across industry and research, describing and defining the key terminology, outlining current techniques and their application. We summarize the current problems and challenges in the field......The recently emerged field of game analytics and the development and adaptation of business intelligence techniques to support game design and development has given data-driven techniques a direct role in game development. Given that all digital games contain some sort of spatial operation...

Communicating Climate Change through ICT-Based Visualization: Towards an Analytical Framework

Directory of Open Access Journals (Sweden)

Björn-Ola Linnér

2013-11-01

Full Text Available The difficulties in communicating climate change science to the general public are often highlighted as one of the hurdles for support of enhanced climate action. The advances of interactive visualization using information and communication technology (ICT are claimed to be a game-changer in our ability to communicate complex issues. However, new analytical frameworks are warranted to analyse the role of such technologies. This paper develops a novel framework for analyzing the content, form, context and relevance of ICT-based visualization of climate change, based on insights from literature on climate change communication. Thereafter, we exemplify the analytical framework by applying it to a pilot case of ICT-based climate visualization in a GeoDome. Possibilities to use affordable advanced ICT-based visualization devices in science and policy communication are rapidly expanding. We thus see wider implications and applications of the analytical framework not only for other ICT environments but also other issue areas in sustainability communication.

A Visual Analytics Technique for Identifying Heat Spots in Transportation Networks

Directory of Open Access Journals (Sweden)

Marian Sorin Nistor

2016-12-01

Full Text Available The decision takers of the public transportation system, as part of urban critical infrastructures, need to increase the system resilience. For doing so, we identified analysis tools for biological networks as an adequate basis for visual analytics in that domain. In the paper at hand we therefore translate such methods for transportation systems and show the benefits by applying them on the Munich subway network. Here, visual analytics is used to identify vulnerable stations from different perspectives. The applied technique is presented step by step. Furthermore, the key challenges in applying this technique on transportation systems are identified. Finally, we propose the implementation of the presented features in a management cockpit to integrate the visual analytics mantra for an adequate decision support on transportation systems.

Visual Analytics for Heterogeneous Geoscience Data

Science.gov (United States)

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

2017-12-01

Geoscience data obtained from diverse sources have been routinely leveraged by scientists to study various phenomena. The principal data sources include observations and model simulation outputs. These data are characterized by spatiotemporal heterogeneity originated from different instrument design specifications and/or computational model requirements used in data generation processes. Such inherent heterogeneity poses several challenges in exploring and analyzing geoscience data. First, scientists often wish to identify features or patterns co-located among multiple data sources to derive and validate certain hypotheses. Heterogeneous data make it a tedious task to search such features in dissimilar datasets. Second, features of geoscience data are typically multivariate. It is challenging to tackle the high dimensionality of geoscience data and explore the relations among multiple variables in a scalable fashion. Third, there is a lack of transparency in traditional automated approaches, such as feature detection or clustering, in that scientists cannot intuitively interact with their analysis processes and interpret results. To address these issues, we present a new scalable approach that can assist scientists in analyzing voluminous and diverse geoscience data. We expose a high-level query interface that allows users to easily express their customized queries to search features of interest across multiple heterogeneous datasets. For identified features, we develop a visualization interface that enables interactive exploration and analytics in a linked-view manner. Specific visualization techniques such as scatter plots to parallel coordinates are employed in each view to allow users to explore various aspects of features. Different views are linked and refreshed according to user interactions in any individual view. In such a manner, a user can interactively and iteratively gain understanding into the data through a variety of visual analytics operations. We

Ultrascale collaborative visualization using a display-rich global cyberinfrastructure.

Science.gov (United States)

Jeong, Byungil; Leigh, Jason; Johnson, Andrew; Renambot, Luc; Brown, Maxine; Jagodic, Ratko; Nam, Sungwon; Hur, Hyejung

2010-01-01

The scalable adaptive graphics environment (SAGE) is high-performance graphics middleware for ultrascale collaborative visualization using a display-rich global cyberinfrastructure. Dozens of sites worldwide use this cyberinfrastructure middleware, which connects high-performance-computing resources over high-speed networks to distributed ultraresolution displays.

Development of collaborative-creative learning model using virtual laboratory media for instrumental analytical chemistry lectures

Science.gov (United States)

Zurweni, Wibawa, Basuki; Erwin, Tuti Nurian

2017-08-01

The framework for teaching and learning in the 21st century was prepared with 4Cs criteria. Learning providing opportunity for the development of students' optimal creative skills is by implementing collaborative learning. Learners are challenged to be able to compete, work independently to bring either individual or group excellence and master the learning material. Virtual laboratory is used for the media of Instrumental Analytical Chemistry (Vis, UV-Vis-AAS etc) lectures through simulations computer application and used as a substitution for the laboratory if the equipment and instruments are not available. This research aims to design and develop collaborative-creative learning model using virtual laboratory media for Instrumental Analytical Chemistry lectures, to know the effectiveness of this design model adapting the Dick & Carey's model and Hannafin & Peck's model. The development steps of this model are: needs analyze, design collaborative-creative learning, virtual laboratory media using macromedia flash, formative evaluation and test of learning model effectiveness. While, the development stages of collaborative-creative learning model are: apperception, exploration, collaboration, creation, evaluation, feedback. Development of collaborative-creative learning model using virtual laboratory media can be used to improve the quality learning in the classroom, overcome the limitation of lab instruments for the real instrumental analysis. Formative test results show that the Collaborative-Creative Learning Model developed meets the requirements. The effectiveness test of students' pretest and posttest proves significant at 95% confidence level, t-test higher than t-table. It can be concluded that this learning model is effective to use for Instrumental Analytical Chemistry lectures.

DOE's SciDAC Visualization and Analytics Center for EnablingTechnologies -- Strategy for Petascale Visual Data Analysis Success

Energy Technology Data Exchange (ETDEWEB)

Bethel, E Wes; Johnson, Chris; Aragon, Cecilia; Rubel, Oliver; Weber, Gunther; Pascucci, Valerio; Childs, Hank; Bremer, Peer-Timo; Whitlock, Brad; Ahern, Sean; Meredith, Jeremey; Ostrouchov, George; Joy, Ken; Hamann, Bernd; Garth, Christoph; Cole, Martin; Hansen, Charles; Parker, Steven; Sanderson, Allen; Silva, Claudio; Tricoche, Xavier

2007-10-01

The focus of this article is on how one group of researchersthe DOE SciDAC Visualization and Analytics Center for EnablingTechnologies (VACET) is tackling the daunting task of enabling knowledgediscovery through visualization and analytics on some of the world slargest and most complex datasets and on some of the world's largestcomputational platforms. As a Center for Enabling Technology, VACET smission is the creation of usable, production-quality visualization andknowledge discovery software infrastructure that runs on large, parallelcomputer systems at DOE's Open Computing facilities and that providessolutions to challenging visual data exploration and knowledge discoveryneeds of modern science, particularly the DOE sciencecommunity.

TrajAnalytics: A Web-Based Visual Analytics Software of Urban Trajectory

OpenAIRE

Zhao, Ye; AL-Dohuki, Shamal; Eynon, Thomas; Kamw, Farah; Sheets, David; Ma, Chao; Ye, Xinyue; Hu, Yueqi; Feng, Tinghao; Yang, Jing

2017-01-01

Advanced technologies in sensing and computing have created urban trajectory datasets of humans and vehicles travelling over urban road networks. Understanding and analyzing the large-scale, complex data reflecting city dynamics is of great importance to enhance both human lives and urban environments. Domain practitioners, researchers, and decision-makers need to store, manage, query and visualize such big datasets. We develop a software system named TrajAnalytics, which explicitly supports ...

Big data and visual analytics in anaesthesia and health care.

Science.gov (United States)

Simpao, A F; Ahumada, L M; Rehman, M A

2015-09-01

Advances in computer technology, patient monitoring systems, and electronic health record systems have enabled rapid accumulation of patient data in electronic form (i.e. big data). Organizations such as the Anesthesia Quality Institute and Multicenter Perioperative Outcomes Group have spearheaded large-scale efforts to collect anaesthesia big data for outcomes research and quality improvement. Analytics--the systematic use of data combined with quantitative and qualitative analysis to make decisions--can be applied to big data for quality and performance improvements, such as predictive risk assessment, clinical decision support, and resource management. Visual analytics is the science of analytical reasoning facilitated by interactive visual interfaces, and it can facilitate performance of cognitive activities involving big data. Ongoing integration of big data and analytics within anaesthesia and health care will increase demand for anaesthesia professionals who are well versed in both the medical and the information sciences. © The Author 2015. Published by Oxford University Press on behalf of the British Journal of Anaesthesia. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

TimeBench: a data model and software library for visual analytics of time-oriented data.

Science.gov (United States)

Rind, Alexander; Lammarsch, Tim; Aigner, Wolfgang; Alsallakh, Bilal; Miksch, Silvia

2013-12-01

Time-oriented data play an essential role in many Visual Analytics scenarios such as extracting medical insights from collections of electronic health records or identifying emerging problems and vulnerabilities in network traffic. However, many software libraries for Visual Analytics treat time as a flat numerical data type and insufficiently tackle the complexity of the time domain such as calendar granularities and intervals. Therefore, developers of advanced Visual Analytics designs need to implement temporal foundations in their application code over and over again. We present TimeBench, a software library that provides foundational data structures and algorithms for time-oriented data in Visual Analytics. Its expressiveness and developer accessibility have been evaluated through application examples demonstrating a variety of challenges with time-oriented data and long-term developer studies conducted in the scope of research and student projects.

Creative Organizational Vision Building through Collaborative, Visual-Metaphorical Thought.

Science.gov (United States)

Ambrose, Don

1998-01-01

Describes use of collaborative metaphorical discussions, mind mapping, and imaginative visual thinking by the faculty of the Rider University School of Education to produce an idealistic vision of the college's future. This vision is expressed as a fanciful metaphorical drawing surrounded by a mind map and accompanied by a story connecting symbols…

Examining the Use of a Visual Analytics System for Sensemaking Tasks: Case Studies with Domain Experts.

Science.gov (United States)

Kang, Youn-Ah; Stasko, J

2012-12-01

While the formal evaluation of systems in visual analytics is still relatively uncommon, particularly rare are case studies of prolonged system use by domain analysts working with their own data. Conducting case studies can be challenging, but it can be a particularly effective way to examine whether visual analytics systems are truly helping expert users to accomplish their goals. We studied the use of a visual analytics system for sensemaking tasks on documents by six analysts from a variety of domains. We describe their application of the system along with the benefits, issues, and problems that we uncovered. Findings from the studies identify features that visual analytics systems should emphasize as well as missing capabilities that should be addressed. These findings inform design implications for future systems.

Changes in Visual/Spatial and Analytic Strategy Use in Organic Chemistry with the Development of Expertise

Science.gov (United States)

Vlacholia, Maria; Vosniadou, Stella; Roussos, Petros; Salta, Katerina; Kazi, Smaragda; Sigalas, Michael; Tzougraki, Chryssa

2017-01-01

We present two studies that investigated the adoption of visual/spatial and analytic strategies by individuals at different levels of expertise in the area of organic chemistry, using the Visual Analytic Chemistry Task (VACT). The VACT allows the direct detection of analytic strategy use without drawing inferences about underlying mental…

VACET: Proposed SciDAC2 Visualization and Analytics Center for Enabling Technologies

International Nuclear Information System (INIS)

Bethel, W; Johnson, C; Hansen, C; Parker, S; Sanderson, A; Silva, C; Tricoche, X; Pascucci, V; Childs, H; Cohen, J; Duchaineau, M; Laney, D; Lindstrom, P; Ahern, S; Meredith, J; Ostrouchov, G; Joy, K; Hamann, B

2006-01-01

This project 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 for our Center is to respond directly to that challenge by adapting, extending, creating when necessary and deploying visualization and data understanding technologies for our science stakeholders. Using an organizational model as a Visualization and Analytics Center for Enabling Technologies (VACET), we are well positioned to be responsive to the needs of a diverse set of scientific stakeholders in a coordinated fashion using a range of visualization, mathematics, statistics, computer and computational science and data management technologies

Analytics and Visualization Pipelines for Big ­Data on the NASA Earth Exchange (NEX) and OpenNEX

Science.gov (United States)

Chaudhary, A.; Votava, P.; Nemani, R. R.; Michaelis, A.; Kotfila, C.

2016-12-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

Collaborative Research between Malaysian and Australian Universities on Learning Analytics: Challenges and Strategies

OpenAIRE

Z. Tasir; S. N. Kew; D. West; Z. Abdullah; D. Toohey

2016-01-01

Research on Learning Analytics is progressively developing in the higher education field by concentrating on the process of students' learning. Therefore, a research project between Malaysian and Australian Universities was initiated in 2015 to look at the use of Learning Analytics to support the development of teaching practice. The focal point of this article is to discuss and share the experiences of Malaysian and Australian universities in the process of developing the collaborative resea...

Visual analytics of surveillance data on foodborne vibriosis, United States, 1973-2010.

Science.gov (United States)

Sims, Jennifer N; Isokpehi, Raphael D; Cooper, Gabrielle A; Bass, Michael P; Brown, Shyretha D; St John, Alison L; Gulig, Paul A; Cohly, Hari H P

2011-01-01

Foodborne illnesses caused by microbial and chemical contaminants in food are a substantial health burden worldwide. In 2007, human vibriosis (non-cholera Vibrio infections) became a notifiable disease in the United States. In addition, Vibrio species are among the 31 major known pathogens transmitted through food in the United States. Diverse surveillance systems for foodborne pathogens also track outbreaks, illnesses, hospitalization and deaths due to non-cholera vibrios. Considering the recognition of vibriosis as a notifiable disease in the United States and the availability of diverse surveillance systems, there is a need for the development of easily deployed visualization and analysis approaches that can combine diverse data sources in an interactive manner. Current efforts to address this need are still limited. Visual analytics is an iterative process conducted via visual interfaces that involves collecting information, data preprocessing, knowledge representation, interaction, and decision making. We have utilized public domain outbreak and surveillance data sources covering 1973 to 2010, as well as visual analytics software to demonstrate integrated and interactive visualizations of data on foodborne outbreaks and surveillance of Vibrio species. Through the data visualization, we were able to identify unique patterns and/or novel relationships within and across datasets regarding (i) causative agent; (ii) foodborne outbreaks and illness per state; (iii) location of infection; (iv) vehicle (food) of infection; (v) anatomical site of isolation of Vibrio species; (vi) patients and complications of vibriosis; (vii) incidence of laboratory-confirmed vibriosis and V. parahaemolyticus outbreaks. The additional use of emerging visual analytics approaches for interaction with data on vibriosis, including non-foodborne related disease, can guide disease control and prevention as well as ongoing outbreak investigations.

Visualized and Interacted Life: Personal Analytics and Engagements with Data Doubles

Directory of Open Access Journals (Sweden)

Minna Ruckenstein

2014-02-01

Full Text Available A field of personal analytics has emerged around self-monitoring practices, which includes the visualization and interpretation of the data produced. This paper explores personal analytics from the perspective of self-optimization, arguing that the ways in which people confront and engage with visualized personal data are as significant as the technology itself. The paper leans on the concept of the “data double”: the conversion of human bodies and minds into data flows that can be figuratively reassembled for the purposes of personal reflection and interaction. Based on an empirical study focusing on heart-rate variability measurement, the discussion underlines that a distanced theorizing of personal analytics is not sufficient if one wants to capture affective encounters between humans and their data doubles. Research outcomes suggest that these explanations can produce permanence and stability while also profoundly changing ways in which people reflect on themselves, on others and on their daily lives.

Cloud-Based Social Media Visual Analytics Disaster Response System, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — We propose a next-generation cloud-based social media visual analytics disaster response system that will enable decision-makers and first-responders to obtain...

A Visual Analytics Approach for Station-Based Air Quality Data

Directory of Open Access Journals (Sweden)

Yi Du

2016-12-01

Full Text Available With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

A Visual Analytics Approach for Station-Based Air Quality Data.

Science.gov (United States)

Du, Yi; Ma, Cuixia; Wu, Chao; Xu, Xiaowei; Guo, Yike; Zhou, Yuanchun; Li, Jianhui

2016-12-24

With the deployment of multi-modality and large-scale sensor networks for monitoring air quality, we are now able to collect large and multi-dimensional spatio-temporal datasets. For these sensed data, we present a comprehensive visual analysis approach for air quality analysis. This approach integrates several visual methods, such as map-based views, calendar views, and trends views, to assist the analysis. Among those visual methods, map-based visual methods are used to display the locations of interest, and the calendar and the trends views are used to discover the linear and periodical patterns. The system also provides various interaction tools to combine the map-based visualization, trends view, calendar view and multi-dimensional view. In addition, we propose a self-adaptive calendar-based controller that can flexibly adapt the changes of data size and granularity in trends view. Such a visual analytics system would facilitate big-data analysis in real applications, especially for decision making support.

Decision Exploration Lab : A Visual Analytics Solution for Decision Management

NARCIS (Netherlands)

Broeksema, Bertjan; Baudel, Thomas; Telea, Alex; Crisafulli, Paolo

2013-01-01

We present a visual analytics solution designed to address prevalent issues in the area of Operational Decision Management (ODM). In ODM, which has its roots in Artificial Intelligence (Expert Systems) and Management Science, it is increasingly important to align business decisions with business

Visual Analytics of Surveillance Data on Foodborne Vibriosis, United States, 1973–2010

Science.gov (United States)

Sims, Jennifer N.; Isokpehi, Raphael D.; Cooper, Gabrielle A.; Bass, Michael P.; Brown, Shyretha D.; St John, Alison L.; Gulig, Paul A.; Cohly, Hari H.P.

2011-01-01

Foodborne illnesses caused by microbial and chemical contaminants in food are a substantial health burden worldwide. In 2007, human vibriosis (non-cholera Vibrio infections) became a notifiable disease in the United States. In addition, Vibrio species are among the 31 major known pathogens transmitted through food in the United States. Diverse surveillance systems for foodborne pathogens also track outbreaks, illnesses, hospitalization and deaths due to non-cholera vibrios. Considering the recognition of vibriosis as a notifiable disease in the United States and the availability of diverse surveillance systems, there is a need for the development of easily deployed visualization and analysis approaches that can combine diverse data sources in an interactive manner. Current efforts to address this need are still limited. Visual analytics is an iterative process conducted via visual interfaces that involves collecting information, data preprocessing, knowledge representation, interaction, and decision making. We have utilized public domain outbreak and surveillance data sources covering 1973 to 2010, as well as visual analytics software to demonstrate integrated and interactive visualizations of data on foodborne outbreaks and surveillance of Vibrio species. Through the data visualization, we were able to identify unique patterns and/or novel relationships within and across datasets regarding (i) causative agent; (ii) foodborne outbreaks and illness per state; (iii) location of infection; (iv) vehicle (food) of infection; (v) anatomical site of isolation of Vibrio species; (vi) patients and complications of vibriosis; (vii) incidence of laboratory-confirmed vibriosis and V. parahaemolyticus outbreaks. The additional use of emerging visual analytics approaches for interaction with data on vibriosis, including non-foodborne related disease, can guide disease control and prevention as well as ongoing outbreak investigations. PMID:22174586

WebViz:A Web-based Collaborative Interactive Visualization System for large-Scale Data Sets

Science.gov (United States)

Yuen, D. A.; McArthur, E.; Weiss, R. M.; Zhou, J.; Yao, B.

2010-12-01

WebViz is a web-based application designed to conduct collaborative, interactive visualizations of large data sets for multiple users, allowing researchers situated all over the world to utilize the visualization services offered by the University of Minnesota’s Laboratory for Computational Sciences and Engineering (LCSE). This ongoing project has been built upon over the last 3 1/2 years .The motivation behind WebViz lies primarily with the need to parse through an increasing amount of data produced by the scientific community as a result of larger and faster multicore and massively parallel computers coming to the market, including the use of general purpose GPU computing. WebViz allows these large data sets to be visualized online by anyone with an account. The application allows users to save time and resources by visualizing data ‘on the fly’, wherever he or she may be located. By leveraging AJAX via the Google Web Toolkit (http://code.google.com/webtoolkit/), we are able to provide users with a remote, web portal to LCSE's (http://www.lcse.umn.edu) large-scale interactive visualization system already in place at the University of Minnesota. LCSE’s custom hierarchical volume rendering software provides high resolution visualizations on the order of 15 million pixels and has been employed for visualizing data primarily from simulations in astrophysics to geophysical fluid dynamics . In the current version of WebViz, we have implemented a highly extensible back-end framework built around HTTP "server push" technology. The web application is accessible via a variety of devices including netbooks, iPhones, and other web and javascript-enabled cell phones. Features in the current version include the ability for users to (1) securely login (2) launch multiple visualizations (3) conduct collaborative visualization sessions (4) delegate control aspects of a visualization to others and (5) engage in collaborative chats with other users within the user interface

Using Visualization to Motivate Student Participation in Collaborative Online Learning Environments

Science.gov (United States)

Jin, Sung-Hee

2017-01-01

Online participation in collaborative online learning environments is instrumental in motivating students to learn and promoting their learning satisfaction, but there has been little research on the technical supports for motivating students' online participation. The purpose of this study was to develop a visualization tool to motivate learners…

Web GIS in practice IX: a demonstration of geospatial visual analytics using Microsoft Live Labs Pivot technology and WHO mortality data.

Science.gov (United States)

Kamel Boulos, Maged N; Viangteeravat, Teeradache; Anyanwu, Matthew N; Ra Nagisetty, Venkateswara; Kuscu, Emin

2011-03-16

The goal of visual analytics is to facilitate the discourse between the user and the data by providing dynamic displays and versatile visual interaction opportunities with the data that can support analytical reasoning and the exploration of data from multiple user-customisable aspects. This paper introduces geospatial visual analytics, a specialised subtype of visual analytics, and provides pointers to a number of learning resources about the subject, as well as some examples of human health, surveillance, emergency management and epidemiology-related geospatial visual analytics applications and examples of free software tools that readers can experiment with, such as Google Public Data Explorer. The authors also present a practical demonstration of geospatial visual analytics using partial data for 35 countries from a publicly available World Health Organization (WHO) mortality dataset and Microsoft Live Labs Pivot technology, a free, general purpose visual analytics tool that offers a fresh way to visually browse and arrange massive amounts of data and images online and also supports geographic and temporal classifications of datasets featuring geospatial and temporal components. Interested readers can download a Zip archive (included with the manuscript as an additional file) containing all files, modules and library functions used to deploy the WHO mortality data Pivot collection described in this paper.

Scientific Visualization for Atmospheric Data Analysis in Collaborative Virtual Environments

Science.gov (United States)

Engelke, Wito; Flatken, Markus; Garcia, Arturo S.; Bar, Christian; Gerndt, Andreas

2016-04-01

1 INTRODUCTION The three year European research project CROSS DRIVE (Collaborative Rover Operations and Planetary Science Analysis System based on Distributed Remote and Interactive Virtual Environments) started in January 2014. The research and development within this project is motivated by three use case studies: landing site characterization, atmospheric science and rover target selection [1]. Currently the implementation for the second use case is in its final phase [2]. Here, the requirements were generated based on the domain experts input and lead to development and integration of appropriate methods for visualization and analysis of atmospheric data. The methods range from volume rendering, interactive slicing, iso-surface techniques to interactive probing. All visualization methods are integrated in DLR's Terrain Rendering application. With this, the high resolution surface data visualization can be enriched with additional methods appropriate for atmospheric data sets. This results in an integrated virtual environment where the scientist has the possibility to interactively explore his data sets directly within the correct context. The data sets include volumetric data of the martian atmosphere, precomputed two dimensional maps and vertical profiles. In most cases the surface data as well as the atmospheric data has global coverage and is of time dependent nature. Furthermore, all interaction is synchronized between different connected application instances, allowing for collaborative sessions between distant experts. 2 VISUALIZATION TECHNIQUES Also the application is currently used for visualization of data sets related to Mars the techniques can be used for other data sets as well. Currently the prototype is capable of handling 2 and 2.5D surface data as well as 4D atmospheric data. Specifically, the surface data is presented using an LoD approach which is based on the HEALPix tessellation of a sphere [3, 4, 5] and can handle data sets in the order of

Visual Analytics of Complex Genomics Data to Guide Effective Treatment Decisions

Directory of Open Access Journals (Sweden)

Quang Vinh Nguyen

2016-09-01

Full Text Available In cancer biology, genomics represents a big data problem that needs accurate visual data processing and analytics. The human genome is very complex with thousands of genes that contain the information about the individual patients and the biological mechanisms of their disease. Therefore, when building a framework for personalised treatment, the complexity of the genome must be captured in meaningful and actionable ways. This paper presents a novel visual analytics framework that enables effective analysis of large and complex genomics data. By providing interactive visualisations from the overview of the entire patient cohort to the detail view of individual genes, our work potentially guides effective treatment decisions for childhood cancer patients. The framework consists of multiple components enabling the complete analytics supporting personalised medicines, including similarity space construction, automated analysis, visualisation, gene-to-gene comparison and user-centric interaction and exploration based on feature selection. In addition to the traditional way to visualise data, we utilise the Unity3D platform for developing a smooth and interactive visual presentation of the information. This aims to provide better rendering, image quality, ergonomics and user experience to non-specialists or young users who are familiar with 3D gaming environments and interfaces. We illustrate the effectiveness of our approach through case studies with datasets from childhood cancers, B-cell Acute Lymphoblastic Leukaemia (ALL and Rhabdomyosarcoma (RMS patients, on how to guide the effective treatment decision in the cohort.

Just-in-time Time Data Analytics and Visualization of Climate Simulations using the Bellerophon Framework

Science.gov (United States)

Anantharaj, V. G.; Venzke, J.; Lingerfelt, E.; Messer, B.

2015-12-01

Climate model simulations are used to understand the evolution and variability of earth's climate. Unfortunately, high-resolution multi-decadal climate simulations can take days to weeks to complete. Typically, the simulation results are not analyzed until the model runs have ended. During the course of the simulation, the output may be processed periodically to ensure that the model is preforming as expected. However, most of the data analytics and visualization are not performed until the simulation is finished. The lengthy time period needed for the completion of the simulation constrains the productivity of climate scientists. Our implementation of near real-time data visualization analytics capabilities allows scientists to monitor the progress of their simulations while the model is running. Our analytics software executes concurrently in a co-scheduling mode, monitoring data production. When new data are generated by the simulation, a co-scheduled data analytics job is submitted to render visualization artifacts of the latest results. These visualization output are automatically transferred to Bellerophon's data server located at ORNL's Compute and Data Environment for Science (CADES) where they are processed and archived into Bellerophon's database. During the course of the experiment, climate scientists can then use Bellerophon's graphical user interface to view animated plots and their associated metadata. The quick turnaround from the start of the simulation until the data are analyzed permits research decisions and projections to be made days or sometimes even weeks sooner than otherwise possible! The supercomputer resources used to run the simulation are unaffected by co-scheduling the data visualization jobs, so the model runs continuously while the data are visualized. Our just-in-time data visualization software looks to increase climate scientists' productivity as climate modeling moves into exascale era of computing.

IN13B-1660: Analytics and Visualization Pipelines for Big Data on the NASA Earth Exchange (NEX) and OpenNEX

Science.gov (United States)

Chaudhary, Aashish; Votava, Petr; Nemani, Ramakrishna R.; Michaelis, Andrew; Kotfila, Chris

2016-01-01

We are developing capabilities for an integrated petabyte-scale Earth science collaborative analysis and visualization environment. The ultimate goal is to deploy this environment within the NASA Earth Exchange (NEX) and OpenNEX in order to enhance existing science data production pipelines in both high-performance computing (HPC) and cloud environments. Bridging of HPC and cloud is a fairly new concept under active research and this system significantly enhances the ability of the scientific community to accelerate analysis and visualization of Earth science data from NASA missions, model outputs and other sources. We have developed a web-based system that seamlessly interfaces with both high-performance computing (HPC) and cloud environments, providing tools that enable science teams to develop and deploy large-scale analysis, visualization and QA pipelines of both the production process and the data products, and enable sharing results with the community. Our project is developed in several stages each addressing separate challenge - workflow integration, parallel execution in either cloud or HPC environments and big-data analytics or visualization. This work benefits a number of existing and upcoming projects supported by NEX, such as the Web Enabled Landsat Data (WELD), where we are developing a new QA pipeline for the 25PB system.

A Collaborative Education Network for Advancing Climate Literacy using Data Visualization Technology

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McDougall, C.; Russell, E. L.; Murray, M.; Bendel, W. B.

2013-12-01

One of the more difficult issues in engaging broad audiences with scientific research is to present it in a way that is intuitive, captivating and up-to-date. Over the past ten years, the National Oceanic and Atmospheric Administration (NOAA) has made significant progress in this area through Science On a Sphere(R) (SOS). SOS is a room-sized, global display system that uses computers and video projectors to display Earth systems data onto a six-foot diameter sphere, analogous to a giant animated globe. This well-crafted data visualization system serves as a way to integrate and display global change phenomena; including polar ice melt, projected sea level rise, ocean acidification and global climate models. Beyond a display for individual data sets, SOS provides a holistic global perspective that highlights the interconnectedness of Earth systems, nations and communities. SOS is now a featured exhibit at more than 100 science centers, museums, universities, aquariums and other institutions around the world reaching more than 33 million visitors every year. To facilitate the development of how this data visualization technology and these visualizations could be used with public audiences, we recognized the need for the exchange of information among the users. To accomplish this, we established the SOS Users Collaborative Network. This network consists of the institutions that have an SOS system or partners who are creating content and educational programming for SOS. When we began the Network in 2005, many museums had limited capacity to both incorporate real-time, authentic scientific data about the Earth system and interpret global change visualizations. They needed not only the visualization platform and the scientific content, but also assistance with methods of approach. We needed feedback from these users on how to craft understandable visualizations and how to further develop the SOS platform to support learning. Through this Network and the collaboration

Advancing Collaboration through Hydrologic Data and Model Sharing

Science.gov (United States)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Band, L. E.; Merwade, V.; Couch, A.; Hooper, R. P.; Maidment, D. R.; Dash, P. K.; Stealey, M.; Yi, H.; Gan, T.; Castronova, A. M.; Miles, B.; Li, Z.; Morsy, M. M.

2015-12-01

HydroShare is an online, collaborative system for open sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined primarily by standardized metadata, content data models for each resource type, and an overarching resource data model based on the Open Archives Initiative's Object Reuse and Exchange (OAI-ORE) standard and a hierarchical file packaging system called "BagIt". HydroShare expands the data sharing capability of the CUAHSI Hydrologic Information System by broadening the classes of data accommodated to include geospatial and multidimensional space-time datasets commonly used in hydrology. HydroShare also includes new capability for sharing models, model components, and analytical tools and will take advantage of emerging social media functionality to enhance information about and collaboration around hydrologic data and models. It also supports web services and server/cloud based computation operating on resources for the execution of hydrologic models and analysis and visualization of hydrologic data. HydroShare uses iRODS as a network file system for underlying storage of datasets and models. Collaboration is enabled by casting datasets and models as "social objects". Social functions include both private and public sharing, formation of collaborative groups of users, and value-added annotation of shared datasets and models. The HydroShare web interface and social media functions were developed using the Django web application framework coupled to iRODS. Data visualization and analysis is supported through the Tethys Platform web GIS software stack. Links to external systems are supported by RESTful web service interfaces to HydroShare's content. This presentation will introduce the HydroShare functionality developed to date and describe ongoing development of functionality to support collaboration and integration of data and models.

Matisse: A Visual Analytics System for Exploring Emotion Trends in Social Media Text Streams

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; Drouhard, Margaret MEG G [ORNL; Beaver, Justin M [ORNL; Pyle, Joshua M [ORNL; BogenII, Paul L. [Google Inc.

2015-01-01

Dynamically mining textual information streams to gain real-time situational awareness is especially challenging with social media systems where throughput and velocity properties push the limits of a static analytical approach. In this paper, we describe an interactive visual analytics system, called Matisse, that aids with the discovery and investigation of trends in streaming text. Matisse addresses the challenges inherent to text stream mining through the following technical contributions: (1) robust stream data management, (2) automated sentiment/emotion analytics, (3) interactive coordinated visualizations, and (4) a flexible drill-down interaction scheme that accesses multiple levels of detail. In addition to positive/negative sentiment prediction, Matisse provides fine-grained emotion classification based on Valence, Arousal, and Dominance dimensions and a novel machine learning process. Information from the sentiment/emotion analytics are fused with raw data and summary information to feed temporal, geospatial, term frequency, and scatterplot visualizations using a multi-scale, coordinated interaction model. After describing these techniques, we conclude with a practical case study focused on analyzing the Twitter sample stream during the week of the 2013 Boston Marathon bombings. The case study demonstrates the effectiveness of Matisse at providing guided situational awareness of significant trends in social media streams by orchestrating computational power and human cognition.

SmartR: an open-source platform for interactive visual analytics for translational research data.

Science.gov (United States)

Herzinger, Sascha; Gu, Wei; Satagopam, Venkata; Eifes, Serge; Rege, Kavita; Barbosa-Silva, Adriano; Schneider, Reinhard

2017-07-15

In translational research, efficient knowledge exchange between the different fields of expertise is crucial. An open platform that is capable of storing a multitude of data types such as clinical, pre-clinical or OMICS data combined with strong visual analytical capabilities will significantly accelerate the scientific progress by making data more accessible and hypothesis generation easier. The open data warehouse tranSMART is capable of storing a variety of data types and has a growing user community including both academic institutions and pharmaceutical companies. tranSMART, however, currently lacks interactive and dynamic visual analytics and does not permit any post-processing interaction or exploration. For this reason, we developed SmartR , a plugin for tranSMART, that equips the platform not only with several dynamic visual analytical workflows, but also provides its own framework for the addition of new custom workflows. Modern web technologies such as D3.js or AngularJS were used to build a set of standard visualizations that were heavily improved with dynamic elements. The source code is licensed under the Apache 2.0 License and is freely available on GitHub: https://github.com/transmart/SmartR . reinhard.schneider@uni.lu. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Employing socially driven techniques for framing, contextualization, and collaboration in complex analytical threads

Science.gov (United States)

Wollocko, Arthur; Danczyk, Jennifer; Farry, Michael; Jenkins, Michael; Voshell, Martin

2015-05-01

The proliferation of sensor technologies continues to impact Intelligence Analysis (IA) work domains. Historical procurement focus on sensor platform development and acquisition has resulted in increasingly advanced collection systems; however, such systems often demonstrate classic data overload conditions by placing increased burdens on already overtaxed human operators and analysts. Support technologies and improved interfaces have begun to emerge to ease that burden, but these often focus on single modalities or sensor platforms rather than underlying operator and analyst support needs, resulting in systems that do not adequately leverage their natural human attentional competencies, unique skills, and training. One particular reason why emerging support tools often fail is due to the gap between military applications and their functions, and the functions and capabilities afforded by cutting edge technology employed daily by modern knowledge workers who are increasingly "digitally native." With the entry of Generation Y into these workplaces, "net generation" analysts, who are familiar with socially driven platforms that excel at giving users insight into large data sets while keeping cognitive burdens at a minimum, are creating opportunities for enhanced workflows. By using these ubiquitous platforms, net generation analysts have trained skills in discovering new information socially, tracking trends among affinity groups, and disseminating information. However, these functions are currently under-supported by existing tools. In this paper, we describe how socially driven techniques can be contextualized to frame complex analytical threads throughout the IA process. This paper focuses specifically on collaborative support technology development efforts for a team of operators and analysts. Our work focuses on under-supported functions in current working environments, and identifies opportunities to improve a team's ability to discover new information and

3D Visualization of Engendering Collaborative Leadership in the Space

Directory of Open Access Journals (Sweden)

Aini-Kristiina Jäppinen

2012-12-01

Full Text Available The paper focuses on collaborative leadership in education and how to illustrate its engendering process in a three-dimensional space. This complex and fluid process is examined as distributed and pedagogical within a Finnish vocational upper secondary educational organization. As a consequence, the notion of distributed pedagogical leadership is used when collaborative leadership in education is studied. Collaborative leadership is argued to consist of the innermost substance of a professional learning community, as attributes of a group of people working together for specific purposes. Therefore, collaborative leadership naturally involves actors, activities, and context. However, the innermost substance of the community is the crux of leadership. It is here presented in the form of ten "keys", as ten attributes with several operational nuances. The keys are highly interdependent and a movement in one of them has an effect both on every other key and the whole. Within this framework, the paper provides a presentation of selected study results by means of the 3D program Strata. The visualizations illustrate concrete examples of how the keys relate to the reality in the vocational education organization in question. For this, a novel analysis called Wave is used, based on natural laws and rules of physics.

Collaborative Visualization Project: shared-technology learning environments for science learning

Science.gov (United States)

Pea, Roy D.; Gomez, Louis M.

1993-01-01

Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.

A Location Aware Middleware Framework for Collaborative Visual Information Discovery and Retrieval

Science.gov (United States)

2017-09-14

scalable location-aware distributed indexing to enable the leveraging of collaborative effort for the construction and maintenance of world-scale visual... Maintenance . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 3.1 Related Works...build an image-based database for road navigation, Google hires cars to drive and take pictures along roads . For this effort to have complete global

Exploring Multi-Scale Spatiotemporal Twitter User Mobility Patterns with a Visual-Analytics Approach

Directory of Open Access Journals (Sweden)

Junjun Yin

2016-10-01

Full Text Available Understanding human mobility patterns is of great importance for urban planning, traffic management, and even marketing campaign. However, the capability of capturing detailed human movements with fine-grained spatial and temporal granularity is still limited. In this study, we extracted high-resolution mobility data from a collection of over 1.3 billion geo-located Twitter messages. Regarding the concerns of infringement on individual privacy, such as the mobile phone call records with restricted access, the dataset is collected from publicly accessible Twitter data streams. In this paper, we employed a visual-analytics approach to studying multi-scale spatiotemporal Twitter user mobility patterns in the contiguous United States during the year 2014. Our approach included a scalable visual-analytics framework to deliver efficiency and scalability in filtering large volume of geo-located tweets, modeling and extracting Twitter user movements, generating space-time user trajectories, and summarizing multi-scale spatiotemporal user mobility patterns. We performed a set of statistical analysis to understand Twitter user mobility patterns across multi-level spatial scales and temporal ranges. In particular, Twitter user mobility patterns measured by the displacements and radius of gyrations of individuals revealed multi-scale or multi-modal Twitter user mobility patterns. By further studying such mobility patterns in different temporal ranges, we identified both consistency and seasonal fluctuations regarding the distance decay effects in the corresponding mobility patterns. At the same time, our approach provides a geo-visualization unit with an interactive 3D virtual globe web mapping interface for exploratory geo-visual analytics of the multi-level spatiotemporal Twitter user movements.

PAVA: Physiological and Anatomical Visual Analytics for Mapping of Tissue-Specific Concentration and Time-Course Data

Science.gov (United States)

We describe the development and implementation of a Physiological and Anatomical Visual Analytics tool (PAVA), a web browser-based application, used to visualize experimental/simulated chemical time-course data (dosimetry), epidemiological data and Physiologically-Annotated Data ...

Understanding the International Space Station Crew Perspective following Long-Duration Missions through Data Analytics & Visualization of Crew Feedback

Science.gov (United States)

Bryant, Cody; Meza, David; Schoenstein, Nicole; Schuh, Susan

2017-01-01

The International Space Station (ISS) first became a home and research laboratory for NASA and International Partner crewmembers over 16 years ago. Each ISS mission lasts approximately 6 months and consists of three to six crewmembers. After returning to Earth, most crewmembers participate in an extensive series of 30+ debriefs intended to further understand life onboard ISS and allow crews to reflect on their experiences. Examples of debrief data collected include ISS crew feedback about sleep, dining, payload science, scheduling and time planning, health & safety, and maintenance. The Flight Crew Integration (FCI) Operational Habitability (OpsHab) team, based at Johnson Space Center (JSC), is a small group of Human Factors engineers and one stenographer that has worked collaboratively with the NASA Astronaut office and ISS Program to collect, maintain, disseminate and analyze this data. The database provides an exceptional and unique resource for understanding the "crew perspective" on long duration space missions. Data is formatted and categorized to allow for ease of search, reporting, and ultimately trending, in order to understand lessons learned, recurring issues and efficiencies gained over time. Recently, the FCI OpsHab team began collaborating with the NASA JSC Knowledge Management team to provide analytical analysis and visualization of these over 75,000 crew comments in order to better ascertain the crew's perspective on long duration spaceflight and gain insight on changes over time. In this initial phase of study, a text mining framework was used to cluster similar comments and develop measures of similarity useful for identifying relevant topics affecting crew health or performance, locating similar comments when a particular issue or item of operational interest is identified, and providing search capabilities to identify information pertinent to future spaceflight systems and processes for things like procedure development and training. In addition

The Usability of a GeoVisual Analytics Environment for the Exploration and Analysis of Different Datasets

DEFF Research Database (Denmark)

Kveladze, Irma; Kraak, Menno-Jan; van Elzakker, C. P. J. M.

2017-01-01

for pattern recognition, decision-making or analytical reasoning. However, the question is whether those visual representations are suitable for visualization of different types of data to perform similar tasks. The limited usability studies that have been done on interactive analytical environments have...... failed to yield a definite answer. Therefore, this paper presents an evaluation experiment on how an interactive GVA environment can be designed that will effectively support similar task execution processes for different use cases. In the GVA environment investigated, four graphic representations...

Urban Space Explorer: A Visual Analytics System for Urban Planning.

Science.gov (United States)

Karduni, Alireza; Cho, Isaac; Wessel, Ginette; Ribarsky, William; Sauda, Eric; Dou, Wenwen

2017-01-01

Understanding people's behavior is fundamental to many planning professions (including transportation, community development, economic development, and urban design) that rely on data about frequently traveled routes, places, and social and cultural practices. Based on the results of a practitioner survey, the authors designed Urban Space Explorer, a visual analytics system that utilizes mobile social media to enable interactive exploration of public-space-related activity along spatial, temporal, and semantic dimensions.

A Visual Analytics Approach for Correlation, Classification, and Regression Analysis

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; SwanII, J. Edward [Mississippi State University (MSU); Fitzpatrick, Patrick J. [Mississippi State University (MSU); Jankun-Kelly, T.J. [Mississippi State University (MSU)

2012-02-01

New approaches that combine the strengths of humans and machines are necessary to equip analysts with the proper tools for exploring today's increasing complex, multivariate data sets. In this paper, a novel visual data mining framework, called the Multidimensional Data eXplorer (MDX), is described that addresses the challenges of today's data by combining automated statistical analytics with a highly interactive parallel coordinates based canvas. In addition to several intuitive interaction capabilities, this framework offers a rich set of graphical statistical indicators, interactive regression analysis, visual correlation mining, automated axis arrangements and filtering, and data classification techniques. The current work provides a detailed description of the system as well as a discussion of key design aspects and critical feedback from domain experts.

Explorative visual analytics on interval-based genomic data and their metadata.

Science.gov (United States)

Jalili, Vahid; Matteucci, Matteo; Masseroli, Marco; Ceri, Stefano

2017-12-04

With the wide-spreading of public repositories of NGS processed data, the availability of user-friendly and effective tools for data exploration, analysis and visualization is becoming very relevant. These tools enable interactive analytics, an exploratory approach for the seamless "sense-making" of data through on-the-fly integration of analysis and visualization phases, suggested not only for evaluating processing results, but also for designing and adapting NGS data analysis pipelines. This paper presents abstractions for supporting the early analysis of NGS processed data and their implementation in an associated tool, named GenoMetric Space Explorer (GeMSE). This tool serves the needs of the GenoMetric Query Language, an innovative cloud-based system for computing complex queries over heterogeneous processed data. It can also be used starting from any text files in standard BED, BroadPeak, NarrowPeak, GTF, or general tab-delimited format, containing numerical features of genomic regions; metadata can be provided as text files in tab-delimited attribute-value format. GeMSE allows interactive analytics, consisting of on-the-fly cycling among steps of data exploration, analysis and visualization that help biologists and bioinformaticians in making sense of heterogeneous genomic datasets. By means of an explorative interaction support, users can trace past activities and quickly recover their results, seamlessly going backward and forward in the analysis steps and comparative visualizations of heatmaps. GeMSE effective application and practical usefulness is demonstrated through significant use cases of biological interest. GeMSE is available at http://www.bioinformatics.deib.polimi.it/GeMSE/ , and its source code is available at https://github.com/Genometric/GeMSE under GPLv3 open-source license.

Network Traffic Analysis With Query Driven VisualizationSC 2005HPC Analytics Results

Energy Technology Data Exchange (ETDEWEB)

Stockinger, Kurt; Wu, Kesheng; Campbell, Scott; Lau, Stephen; Fisk, Mike; Gavrilov, Eugene; Kent, Alex; Davis, Christopher E.; Olinger,Rick; Young, Rob; Prewett, Jim; Weber, Paul; Caudell, Thomas P.; Bethel,E. Wes; Smith, Steve

2005-09-01

Our analytics challenge is to identify, characterize, and visualize anomalous subsets of large collections of network connection data. We use a combination of HPC resources, advanced algorithms, and visualization techniques. To effectively and efficiently identify the salient portions of the data, we rely on a multi-stage workflow that includes data acquisition, summarization (feature extraction), novelty detection, and classification. Once these subsets of interest have been identified and automatically characterized, we use a state-of-the-art-high-dimensional query system to extract data subsets for interactive visualization. Our approach is equally useful for other large-data analysis problems where it is more practical to identify interesting subsets of the data for visualization than to render all data elements. By reducing the size of the rendering workload, we enable highly interactive and useful visualizations. As a result of this work we were able to analyze six months worth of data interactively with response times two orders of magnitude shorter than with conventional methods.

Visual analytics for semantic queries of TerraSAR-X image content

Science.gov (United States)

Espinoza-Molina, Daniela; Alonso, Kevin; Datcu, Mihai

2015-10-01

With the continuous image product acquisition of satellite missions, the size of the image archives is considerably increasing every day as well as the variety and complexity of their content, surpassing the end-user capacity to analyse and exploit them. Advances in the image retrieval field have contributed to the development of tools for interactive exploration and extraction of the images from huge archives using different parameters like metadata, key-words, and basic image descriptors. Even though we count on more powerful tools for automated image retrieval and data analysis, we still face the problem of understanding and analyzing the results. Thus, a systematic computational analysis of these results is required in order to provide to the end-user a summary of the archive content in comprehensible terms. In this context, visual analytics combines automated analysis with interactive visualizations analysis techniques for an effective understanding, reasoning and decision making on the basis of very large and complex datasets. Moreover, currently several researches are focused on associating the content of the images with semantic definitions for describing the data in a format to be easily understood by the end-user. In this paper, we present our approach for computing visual analytics and semantically querying the TerraSAR-X archive. Our approach is mainly composed of four steps: 1) the generation of a data model that explains the information contained in a TerraSAR-X product. The model is formed by primitive descriptors and metadata entries, 2) the storage of this model in a database system, 3) the semantic definition of the image content based on machine learning algorithms and relevance feedback, and 4) querying the image archive using semantic descriptors as query parameters and computing the statistical analysis of the query results. The experimental results shows that with the help of visual analytics and semantic definitions we are able to explain

The Role of Teamwork in the Analysis of Big Data: A Study of Visual Analytics and Box Office Prediction.

Science.gov (United States)

Buchanan, Verica; Lu, Yafeng; McNeese, Nathan; Steptoe, Michael; Maciejewski, Ross; Cooke, Nancy

2017-03-01

Historically, domains such as business intelligence would require a single analyst to engage with data, develop a model, answer operational questions, and predict future behaviors. However, as the problems and domains become more complex, organizations are employing teams of analysts to explore and model data to generate knowledge. Furthermore, given the rapid increase in data collection, organizations are struggling to develop practices for intelligence analysis in the era of big data. Currently, a variety of machine learning and data mining techniques are available to model data and to generate insights and predictions, and developments in the field of visual analytics have focused on how to effectively link data mining algorithms with interactive visuals to enable analysts to explore, understand, and interact with data and data models. Although studies have explored the role of single analysts in the visual analytics pipeline, little work has explored the role of teamwork and visual analytics in the analysis of big data. In this article, we present an experiment integrating statistical models, visual analytics techniques, and user experiments to study the role of teamwork in predictive analytics. We frame our experiment around the analysis of social media data for box office prediction problems and compare the prediction performance of teams, groups, and individuals. Our results indicate that a team's performance is mediated by the team's characteristics such as openness of individual members to others' positions and the type of planning that goes into the team's analysis. These findings have important implications for how organizations should create teams in order to make effective use of information from their analytic models.

Social Network: a Cytoscape app for visualizing co-authorship networks.

Science.gov (United States)

Kofia, Victor; Isserlin, Ruth; Buchan, Alison M J; Bader, Gary D

2015-01-01

Networks that represent connections between individuals can be valuable analytic tools. The Social Network Cytoscape app is capable of creating a visual summary of connected individuals automatically. It does this by representing relationships as networks where each node denotes an individual and an edge linking two individuals represents a connection. The app focuses on creating visual summaries of individuals connected by co-authorship links in academia, created from bibliographic databases like PubMed, Scopus and InCites. The resulting co-authorship networks can be visualized and analyzed to better understand collaborative research networks or to communicate the extent of collaboration and publication productivity among a group of researchers, like in a grant application or departmental review report. It can also be useful as a research tool to identify important research topics, researchers and papers in a subject area.

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization.

Science.gov (United States)

Bernal-Rusiel, Jorge L; Rannou, Nicolas; Gollub, Randy L; Pieper, Steve; Murphy, Shawn; Robertson, Richard; Grant, Patricia E; Pienaar, Rudolph

2017-01-01

In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView , a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education

Directory of Open Access Journals (Sweden)

Christos Vaitsis

2014-11-01

Full Text Available Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education.Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them.Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i learning outcomes and teaching methods, (ii examination and learning outcomes, and (iii teaching methods, learning outcomes, examination results, and gap analysis.Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to

Visual analytics in healthcare education: exploring novel ways to analyze and represent big data in undergraduate medical education.

Science.gov (United States)

Vaitsis, Christos; Nilsson, Gunnar; Zary, Nabil

2014-01-01

Introduction. The big data present in the medical curriculum that informs undergraduate medical education is beyond human abilities to perceive and analyze. The medical curriculum is the main tool used by teachers and directors to plan, design, and deliver teaching and assessment activities and student evaluations in medical education in a continuous effort to improve it. Big data remains largely unexploited for medical education improvement purposes. The emerging research field of visual analytics has the advantage of combining data analysis and manipulation techniques, information and knowledge representation, and human cognitive strength to perceive and recognize visual patterns. Nevertheless, there is a lack of research on the use and benefits of visual analytics in medical education. Methods. The present study is based on analyzing the data in the medical curriculum of an undergraduate medical program as it concerns teaching activities, assessment methods and learning outcomes in order to explore visual analytics as a tool for finding ways of representing big data from undergraduate medical education for improvement purposes. Cytoscape software was employed to build networks of the identified aspects and visualize them. Results. After the analysis of the curriculum data, eleven aspects were identified. Further analysis and visualization of the identified aspects with Cytoscape resulted in building an abstract model of the examined data that presented three different approaches; (i) learning outcomes and teaching methods, (ii) examination and learning outcomes, and (iii) teaching methods, learning outcomes, examination results, and gap analysis. Discussion. This study identified aspects of medical curriculum that play an important role in how medical education is conducted. The implementation of visual analytics revealed three novel ways of representing big data in the undergraduate medical education context. It appears to be a useful tool to explore such data

Proactive Spatiotemporal Resource Allocation and Predictive Visual Analytics for Community Policing and Law Enforcement.

Science.gov (United States)

Malik, Abish; Maciejewski, Ross; Towers, Sherry; McCullough, Sean; Ebert, David S

2014-12-01

In this paper, we present a visual analytics approach that provides decision makers with a proactive and predictive environment in order to assist them in making effective resource allocation and deployment decisions. The challenges involved with such predictive analytics processes include end-users' understanding, and the application of the underlying statistical algorithms at the right spatiotemporal granularity levels so that good prediction estimates can be established. In our approach, we provide analysts with a suite of natural scale templates and methods that enable them to focus and drill down to appropriate geospatial and temporal resolution levels. Our forecasting technique is based on the Seasonal Trend decomposition based on Loess (STL) method, which we apply in a spatiotemporal visual analytics context to provide analysts with predicted levels of future activity. We also present a novel kernel density estimation technique we have developed, in which the prediction process is influenced by the spatial correlation of recent incidents at nearby locations. We demonstrate our techniques by applying our methodology to Criminal, Traffic and Civil (CTC) incident datasets.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 4 : web-based bridge information database--visualization analytics and distributed sensing.

Science.gov (United States)

2012-03-01

This report introduces the design and implementation of a Web-based bridge information visual analytics system. This : project integrates Internet, multiple databases, remote sensing, and other visualization technologies. The result : combines a GIS ...

A Visual Analytics Approach for Extracting Spatio-Temporal Urban Mobility Information from Mobile Network Traffic

Directory of Open Access Journals (Sweden)

Euro Beinat

2012-11-01

Full Text Available In this paper we present a visual analytics approach for deriving spatio-temporal patterns of collective human mobility from a vast mobile network traffic data set. More than 88 million movements between pairs of radio cells—so-called handovers—served as a proxy for more than two months of mobility within four urban test areas in Northern Italy. In contrast to previous work, our approach relies entirely on visualization and mapping techniques, implemented in several software applications. We purposefully avoid statistical or probabilistic modeling and, nonetheless, reveal characteristic and exceptional mobility patterns. The results show, for example, surprising similarities and symmetries amongst the total mobility and people flows between the test areas. Moreover, the exceptional patterns detected can be associated to real-world events such as soccer matches. We conclude that the visual analytics approach presented can shed new light on large-scale collective urban mobility behavior and thus helps to better understand the “pulse” of dynamic urban systems.

What's Going on in This Picture? Visual Thinking Strategies and Adult Learning

Science.gov (United States)

Landorf, Hilary

2006-01-01

The Visual Thinking Strategies (VTS) curriculum and teaching method uses art to help students think critically, listen attentively, communicate, and collaborate. VTS has been proven to enhance reading, writing, comprehension, and creative and analytical skills among students of all ages. The origins and procedures of the VTS curriculum are…

Reusable Client-Side JavaScript Modules for Immersive Web-Based Real-Time Collaborative Neuroimage Visualization

Directory of Open Access Journals (Sweden)

Jorge L. Bernal-Rusiel

2017-05-01

Full Text Available In this paper we present a web-based software solution to the problem of implementing real-time collaborative neuroimage visualization. In both clinical and research settings, simple and powerful access to imaging technologies across multiple devices is becoming increasingly useful. Prior technical solutions have used a server-side rendering and push-to-client model wherein only the server has the full image dataset. We propose a rich client solution in which each client has all the data and uses the Google Drive Realtime API for state synchronization. We have developed a small set of reusable client-side object-oriented JavaScript modules that make use of the XTK toolkit, a popular open-source JavaScript library also developed by our team, for the in-browser rendering and visualization of brain image volumes. Efficient realtime communication among the remote instances is achieved by using just a small JSON object, comprising a representation of the XTK image renderers' state, as the Google Drive Realtime collaborative data model. The developed open-source JavaScript modules have already been instantiated in a web-app called MedView, a distributed collaborative neuroimage visualization application that is delivered to the users over the web without requiring the installation of any extra software or browser plugin. This responsive application allows multiple physically distant physicians or researchers to cooperate in real time to reach a diagnosis or scientific conclusion. It also serves as a proof of concept for the capabilities of the presented technological solution.

Text Stream Trend Analysis using Multiscale Visual Analytics with Applications to Social Media Systems

Energy Technology Data Exchange (ETDEWEB)

Steed, Chad A [ORNL; Beaver, Justin M [ORNL; BogenII, Paul L. [Google Inc.; Drouhard, Margaret MEG G [ORNL; Pyle, Joshua M [ORNL

2015-01-01

In this paper, we introduce a new visual analytics system, called Matisse, that allows exploration of global trends in textual information streams with specific application to social media platforms. Despite the potential for real-time situational awareness using these services, interactive analysis of such semi-structured textual information is a challenge due to the high-throughput and high-velocity properties. Matisse addresses these challenges through the following contributions: (1) robust stream data management, (2) automated sen- timent/emotion analytics, (3) inferential temporal, geospatial, and term-frequency visualizations, and (4) a flexible drill-down interaction scheme that progresses from macroscale to microscale views. In addition to describing these contributions, our work-in-progress paper concludes with a practical case study focused on the analysis of Twitter 1% sample stream information captured during the week of the Boston Marathon bombings.

The Solid* toolset for software visual analytics of program structure and metrics comprehension : From research prototype to product

NARCIS (Netherlands)

Reniers, Dennie; Voinea, Lucian; Ersoy, Ozan; Telea, Alexandru

2014-01-01

Software visual analytics (SVA) tools combine static program analysis and fact extraction with information visualization to support program comprehension. However, building efficient and effective SVA tools is highly challenging, as it involves extensive software development in program analysis,

XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data

Science.gov (United States)

2015-01-01

Background Though cluster analysis has become a routine analytic task for bioinformatics research, it is still arduous for researchers to assess the quality of a clustering result. To select the best clustering method and its parameters for a dataset, researchers have to run multiple clustering algorithms and compare them. However, such a comparison task with multiple clustering results is cognitively demanding and laborious. Results In this paper, we present XCluSim, a visual analytics tool that enables users to interactively compare multiple clustering results based on the Visual Information Seeking Mantra. We build a taxonomy for categorizing existing techniques of clustering results visualization in terms of the Gestalt principles of grouping. Using the taxonomy, we choose the most appropriate interactive visualizations for presenting individual clustering results from different types of clustering algorithms. The efficacy of XCluSim is shown through case studies with a bioinformatician. Conclusions Compared to other relevant tools, XCluSim enables users to compare multiple clustering results in a more scalable manner. Moreover, XCluSim supports diverse clustering algorithms and dedicated visualizations and interactions for different types of clustering results, allowing more effective exploration of details on demand. Through case studies with a bioinformatics researcher, we received positive feedback on the functionalities of XCluSim, including its ability to help identify stably clustered items across multiple clustering results. PMID:26328893

Multi-Intelligence Analytics for Next Generation Analysts (MIAGA)

Science.gov (United States)

Blasch, Erik; Waltz, Ed

2016-05-01

Current analysts are inundated with large volumes of data from which extraction, exploitation, and indexing are required. A future need for next-generation analysts is an appropriate balance between machine analytics from raw data and the ability of the user to interact with information through automation. Many quantitative intelligence tools and techniques have been developed which are examined towards matching analyst opportunities with recent technical trends such as big data, access to information, and visualization. The concepts and techniques summarized are derived from discussions with real analysts, documented trends of technical developments, and methods to engage future analysts with multiintelligence services. For example, qualitative techniques should be matched against physical, cognitive, and contextual quantitative analytics for intelligence reporting. Future trends include enabling knowledge search, collaborative situational sharing, and agile support for empirical decision-making and analytical reasoning.

Leveraging spatial abstraction in traffic analysis and forecasting with visual analytics

OpenAIRE

Andrienko, N.; Andrienko, G.; Rinzivillo, S.

2016-01-01

A spatially abstracted transportation network is a graph where nodes are territory compartments (areas in geographic space) and edges, or links, are abstract constructs, each link representing all possible paths between two neighboring areas. By applying visual analytics techniques to vehicle traffic data from different territories, we discovered that the traffic intensity (a.k.a. traffic flow or traffic flux) and the mean velocity are interrelated in a spatially abstracted transportation net...

GeoVisual Analytics for the Exploration of Complex Movement Patterns on Arterial Roads

DEFF Research Database (Denmark)

Kveladze, Irma; Agerholm, Niels

2018-01-01

Visualization of complex spatio-temporal traffic movements on the road network is a challenging task since it requires simultaneous representation of vehicle measurement characteristics and traffic network regulation rules. Previously proposed visual representations addressed issues related....... Arterial roads are important for the mobility and connectivity of modern society, but they also have traffic regulations that are not always followed by the vulnerable road users. In order to understand complex movement behaviors between vehicle drivers and pedestrians on the arterial roads, a Geo......Visual Analytics approach was developed in dialog with traffic experts. The exploratory interactive tools have assisted experts to extract unknown information about movement patterns from large traffic data at different levels of details. The results of the analysis revealed detailed patterns of speed variations...

ProteoLens: a visual analytic tool for multi-scale database-driven biological network data mining.

Science.gov (United States)

Huan, Tianxiao; Sivachenko, Andrey Y; Harrison, Scott H; Chen, Jake Y

2008-08-12

New systems biology studies require researchers to understand how interplay among myriads of biomolecular entities is orchestrated in order to achieve high-level cellular and physiological functions. Many software tools have been developed in the past decade to help researchers visually navigate large networks of biomolecular interactions with built-in template-based query capabilities. To further advance researchers' ability to interrogate global physiological states of cells through multi-scale visual network explorations, new visualization software tools still need to be developed to empower the analysis. A robust visual data analysis platform driven by database management systems to perform bi-directional data processing-to-visualizations with declarative querying capabilities is needed. We developed ProteoLens as a JAVA-based visual analytic software tool for creating, annotating and exploring multi-scale biological networks. It supports direct database connectivity to either Oracle or PostgreSQL database tables/views, on which SQL statements using both Data Definition Languages (DDL) and Data Manipulation languages (DML) may be specified. The robust query languages embedded directly within the visualization software help users to bring their network data into a visualization context for annotation and exploration. ProteoLens supports graph/network represented data in standard Graph Modeling Language (GML) formats, and this enables interoperation with a wide range of other visual layout tools. The architectural design of ProteoLens enables the de-coupling of complex network data visualization tasks into two distinct phases: 1) creating network data association rules, which are mapping rules between network node IDs or edge IDs and data attributes such as functional annotations, expression levels, scores, synonyms, descriptions etc; 2) applying network data association rules to build the network and perform the visual annotation of graph nodes and edges

MediaCommons for cultural heritage: Applied mixed media visualization storytelling for high resolution collaborative cyberarchaeological displays

KAUST Repository

Mangan, John

2013-10-01

Archaeology is a discipline that studies time through an understanding of space and objects in that space; archaeology is ultimately, therefore, an intersection where the visualization of space and the visualization of time meet. Archaeology has long utilized visualization as a technique to analyze and disseminate information; however, comprehensive and collaborative analysis and storytelling with this visual data has always been limited by the capacity of the systems, which create and display it. To present the most complete narrative of the past, one must seek the \\'big picture\\' by assembling the disparate pieces of data, which reflect the lives of the humans we study. This paper presents a framework for the visualization of and interaction with rich data collections in high resolution, networked, tiled-display environments, called the MediaCommons Framework. © 2013 IEEE.

The challenge of big data in public health: an opportunity for visual analytics.

Science.gov (United States)

Ola, Oluwakemi; Sedig, Kamran

2014-01-01

Public health (PH) data can generally be characterized as big data. The efficient and effective use of this data determines the extent to which PH stakeholders can sufficiently address societal health concerns as they engage in a variety of work activities. As stakeholders interact with data, they engage in various cognitive activities such as analytical reasoning, decision-making, interpreting, and problem solving. Performing these activities with big data is a challenge for the unaided mind as stakeholders encounter obstacles relating to the data's volume, variety, velocity, and veracity. Such being the case, computer-based information tools are needed to support PH stakeholders. Unfortunately, while existing computational tools are beneficial in addressing certain work activities, they fall short in supporting cognitive activities that involve working with large, heterogeneous, and complex bodies of data. This paper presents visual analytics (VA) tools, a nascent category of computational tools that integrate data analytics with interactive visualizations, to facilitate the performance of cognitive activities involving big data. Historically, PH has lagged behind other sectors in embracing new computational technology. In this paper, we discuss the role that VA tools can play in addressing the challenges presented by big data. In doing so, we demonstrate the potential benefit of incorporating VA tools into PH practice, in addition to highlighting the need for further systematic and focused research.

Progressive Learning of Topic Modeling Parameters: A Visual Analytics Framework.

Science.gov (United States)

El-Assady, Mennatallah; Sevastjanova, Rita; Sperrle, Fabian; Keim, Daniel; Collins, Christopher

2018-01-01

Topic modeling algorithms are widely used to analyze the thematic composition of text corpora but remain difficult to interpret and adjust. Addressing these limitations, we present a modular visual analytics framework, tackling the understandability and adaptability of topic models through a user-driven reinforcement learning process which does not require a deep understanding of the underlying topic modeling algorithms. Given a document corpus, our approach initializes two algorithm configurations based on a parameter space analysis that enhances document separability. We abstract the model complexity in an interactive visual workspace for exploring the automatic matching results of two models, investigating topic summaries, analyzing parameter distributions, and reviewing documents. The main contribution of our work is an iterative decision-making technique in which users provide a document-based relevance feedback that allows the framework to converge to a user-endorsed topic distribution. We also report feedback from a two-stage study which shows that our technique results in topic model quality improvements on two independent measures.

LongLine: Visual Analytics System for Large-scale Audit Logs

Directory of Open Access Journals (Sweden)

Seunghoon Yoo

2018-03-01

Full Text Available Audit logs are different from other software logs in that they record the most primitive events (i.e., system calls in modern operating systems. Audit logs contain a detailed trace of an operating system, and thus have received great attention from security experts and system administrators. However, the complexity and size of audit logs, which increase in real time, have hindered analysts from understanding and analyzing them. In this paper, we present a novel visual analytics system, LongLine, which enables interactive visual analyses of large-scale audit logs. LongLine lowers the interpretation barrier of audit logs by employing human-understandable representations (e.g., file paths and commands instead of abstract indicators of operating systems (e.g., file descriptors as well as revealing the temporal patterns of the logs in a multi-scale fashion with meaningful granularity of time in mind (e.g., hourly, daily, and weekly. LongLine also streamlines comparative analysis between interesting subsets of logs, which is essential in detecting anomalous behaviors of systems. In addition, LongLine allows analysts to monitor the system state in a streaming fashion, keeping the latency between log creation and visualization less than one minute. Finally, we evaluate our system through a case study and a scenario analysis with security experts.

Second International Workshop on Teaching Analytics

DEFF Research Database (Denmark)

Vatrapu, Ravi; Reimann, Peter; Halb, Wolfgang

2013-01-01

Teaching Analytics is conceived as a subfield of learning analytics that focuses on the design, development, evaluation, and education of visual analytics methods and tools for teachers in primary, secondary, and tertiary educational settings. The Second International Workshop on Teaching Analytics...... (IWTA) 2013 seeks to bring together researchers and practitioners in the fields of education, learning sciences, learning analytics, and visual analytics to investigate the design, development, use, evaluation, and impact of visual analytical methods and tools for teachers’ dynamic diagnostic decision...

Visual analytics of inherently noisy crowdsourced data on ultra high resolution displays

Science.gov (United States)

Huynh, Andrew; Ponto, Kevin; Lin, Albert Yu-Min; Kuester, Falko

The increasing prevalence of distributed human microtasking, crowdsourcing, has followed the exponential increase in data collection capabilities. The large scale and distributed nature of these microtasks produce overwhelming amounts of information that is inherently noisy due to the nature of human input. Furthermore, these inputs create a constantly changing dataset with additional information added on a daily basis. Methods to quickly visualize, filter, and understand this information over temporal and geospatial constraints is key to the success of crowdsourcing. This paper present novel methods to visually analyze geospatial data collected through crowdsourcing on top of remote sensing satellite imagery. An ultra high resolution tiled display system is used to explore the relationship between human and satellite remote sensing data at scale. A case study is provided that evaluates the presented technique in the context of an archaeological field expedition. A team in the field communicated in real-time with and was guided by researchers in the remote visual analytics laboratory, swiftly sifting through incoming crowdsourced data to identify target locations that were identified as viable archaeological sites.

A visual analytics system for optimizing the performance of large-scale networks in supercomputing systems

Directory of Open Access Journals (Sweden)

Takanori Fujiwara

2018-03-01

Full Text Available The overall efficiency of an extreme-scale supercomputer largely relies on the performance of its network interconnects. Several of the state of the art supercomputers use networks based on the increasingly popular Dragonfly topology. It is crucial to study the behavior and performance of different parallel applications running on Dragonfly networks in order to make optimal system configurations and design choices, such as job scheduling and routing strategies. However, in order to study these temporal network behavior, we would need a tool to analyze and correlate numerous sets of multivariate time-series data collected from the Dragonfly’s multi-level hierarchies. This paper presents such a tool–a visual analytics system–that uses the Dragonfly network to investigate the temporal behavior and optimize the communication performance of a supercomputer. We coupled interactive visualization with time-series analysis methods to help reveal hidden patterns in the network behavior with respect to different parallel applications and system configurations. Our system also provides multiple coordinated views for connecting behaviors observed at different levels of the network hierarchies, which effectively helps visual analysis tasks. We demonstrate the effectiveness of the system with a set of case studies. Our system and findings can not only help improve the communication performance of supercomputing applications, but also the network performance of next-generation supercomputers. Keywords: Supercomputing, Parallel communication network, Dragonfly networks, Time-series data, Performance analysis, Visual analytics

TrajGraph: A Graph-Based Visual Analytics Approach to Studying Urban Network Centralities Using Taxi Trajectory Data.

Science.gov (United States)

Huang, Xiaoke; Zhao, Ye; Yang, Jing; Zhang, Chong; Ma, Chao; Ye, Xinyue

2016-01-01

We propose TrajGraph, a new visual analytics method, for studying urban mobility patterns by integrating graph modeling and visual analysis with taxi trajectory data. A special graph is created to store and manifest real traffic information recorded by taxi trajectories over city streets. It conveys urban transportation dynamics which can be discovered by applying graph analysis algorithms. To support interactive, multiscale visual analytics, a graph partitioning algorithm is applied to create region-level graphs which have smaller size than the original street-level graph. Graph centralities, including Pagerank and betweenness, are computed to characterize the time-varying importance of different urban regions. The centralities are visualized by three coordinated views including a node-link graph view, a map view and a temporal information view. Users can interactively examine the importance of streets to discover and assess city traffic patterns. We have implemented a fully working prototype of this approach and evaluated it using massive taxi trajectories of Shenzhen, China. TrajGraph's capability in revealing the importance of city streets was evaluated by comparing the calculated centralities with the subjective evaluations from a group of drivers in Shenzhen. Feedback from a domain expert was collected. The effectiveness of the visual interface was evaluated through a formal user study. We also present several examples and a case study to demonstrate the usefulness of TrajGraph in urban transportation analysis.

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

Science.gov (United States)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

A visual analytics design for studying rhythm patterns from human daily movement data

Directory of Open Access Journals (Sweden)

Wei Zeng

2017-06-01

Full Text Available Human’s daily movements exhibit high regularity in a space–time context that typically forms circadian rhythms. Understanding the rhythms for human daily movements is of high interest to a variety of parties from urban planners, transportation analysts, to business strategists. In this paper, we present an interactive visual analytics design for understanding and utilizing data collected from tracking human’s movements. The resulting system identifies and visually presents frequent human movement rhythms to support interactive exploration and analysis of the data over space and time. Case studies using real-world human movement data, including massive urban public transportation data in Singapore and the MIT reality mining dataset, and interviews with transportation researches were conducted to demonstrate the effectiveness and usefulness of our system.

A Novel Application of a Hybrid Delphi-Analytic Hierarchy Process (AHP) Technique: Identifying Key Success Factors in the Strategic Alignment of Collaborative Heterarchical Transportation Networks for Supply Chains

OpenAIRE

Yasanur Kayikci; Volker Stix; Larry J. LeBlanc; Michael R. Bartolacci

2014-01-01

This research studies heterarchical collaboration in logistical transport. Specifically, it utilizes a hybrid Delphi-Analytic Hierarchy Process (AHP) approach to explore the relevant criteria for the formation and maintenance of a strategic alignment for heterarchical transport collaboration. The importance of this work is that it applies a novel hybrid approach for identifying criteria for success to a little-studied form of supply chain collaboration: heterarchical collaborative transport. ...

Cytobank: providing an analytics platform for community cytometry data analysis and collaboration.

Science.gov (United States)

Chen, Tiffany J; Kotecha, Nikesh

2014-01-01

Cytometry is used extensively in clinical and laboratory settings to diagnose and track cell subsets in blood and tissue. High-throughput, single-cell approaches leveraging cytometry are developed and applied in the computational and systems biology communities by researchers, who seek to improve the diagnosis of human diseases, map the structures of cell signaling networks, and identify new cell types. Data analysis and management present a bottleneck in the flow of knowledge from bench to clinic. Multi-parameter flow and mass cytometry enable identification of signaling profiles of patient cell samples. Currently, this process is manual, requiring hours of work to summarize multi-dimensional data and translate these data for input into other analysis programs. In addition, the increase in the number and size of collaborative cytometry studies as well as the computational complexity of analytical tools require the ability to assemble sufficient and appropriately configured computing capacity on demand. There is a critical need for platforms that can be used by both clinical and basic researchers who routinely rely on cytometry. Recent advances provide a unique opportunity to facilitate collaboration and analysis and management of cytometry data. Specifically, advances in cloud computing and virtualization are enabling efficient use of large computing resources for analysis and backup. An example is Cytobank, a platform that allows researchers to annotate, analyze, and share results along with the underlying single-cell data.

Visualization and analytics tools for infectious disease epidemiology: a systematic review.

Science.gov (United States)

Carroll, Lauren N; Au, Alan P; Detwiler, Landon Todd; Fu, Tsung-Chieh; Painter, Ian S; Abernethy, Neil F

2014-10-01

use. As the volume and complexity of infectious disease data increases, public health professionals must synthesize highly disparate data to facilitate communication with the public and inform decisions regarding measures to protect the public's health. Our review identified several themes: consideration of users' needs, preferences, and computer literacy; integration of tools into routine workflow; complications associated with understanding and use of visualizations; and the role of user trust and organizational support in the adoption of these tools. Interoperability also emerged as a prominent theme, highlighting challenges associated with the increasingly collaborative and interdisciplinary nature of infectious disease control and prevention. Future work should address methods for representing uncertainty and missing data to avoid misleading users as well as strategies to minimize cognitive overload. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.

Using visual art and collaborative reflection to explore medical attitudes toward vulnerable persons.

Science.gov (United States)

Kidd, Monica; Nixon, Lara; Rosenal, Tom; Jackson, Roberta; Pereles, Laurie; Mitchell, Ian; Bendiak, Glenda; Hughes, Lisa

2016-01-01

Vulnerable persons often face stigma-related barriers while seeking health care. Innovative education and professional development methods are needed to help change this. We describe an interdisciplinary group workshop designed around a discomfiting oil portrait, intended to trigger provocative conversations among health care students and practitioners, and we present our mixed methods analysis of participant reflections. After the workshop, participants were significantly more likely to endorse the statements that the observation and interpretive skills involved in viewing visual art are relevant to patient care and that visual art should be used in medical education to improve students' observational skills, narrative skills, and empathy with their patients. Subsequent to the workshop, significantly more participants agreed that art interpretation should be required curriculum for health care students. Qualitative comments from two groups from two different education and professional contexts were examined for themes; conversations focused on issues of power, body image/self-esteem, and lessons for clinical practice. We argue that difficult conversations about affective responses to vulnerable persons are possible in a collaborative context using well-chosen works of visual art that can stand in for a patient.

Using visual art and collaborative reflection to explore medical attitudes toward vulnerable persons

Directory of Open Access Journals (Sweden)

Monica Kidd

2016-04-01

Full Text Available Background: Vulnerable persons often face stigma-related barriers while seeking health care. Innovative education and professional development methods are needed to help change this. Method: We describe an interdisciplinary group workshop designed around a discomfiting oil portrait, intended to trigger provocative conversations among health care students and practitioners, and we present our mixed methods analysis of participant reflections. Results: After the workshop, participants were significantly more likely to endorse the statements that the observation and interpretive skills involved in viewing visual art are relevant to patient care and that visual art should be used in medical education to improve students’ observational skills, narrative skills, and empathy with their patients.  Subsequent to the workshop, significantly more participants agreed that art interpretation should be required curriculum for health care students. Qualitative comments from two groups from two different education and professional contexts were examined for themes; conversations focused on issues of power, body image/self-esteem, and lessons for clinical practice.    Conclusions: We argue that difficult conversations about affective responses to vulnerable persons are possible in a collaborative context using well-chosen works of visual art that can stand in for a patient.

Visual programming for next-generation sequencing data analytics.

Science.gov (United States)

Milicchio, Franco; Rose, Rebecca; Bian, Jiang; Min, Jae; Prosperi, Mattia

2016-01-01

High-throughput or next-generation sequencing (NGS) technologies have become an established and affordable experimental framework in biological and medical sciences for all basic and translational research. Processing and analyzing NGS data is challenging. NGS data are big, heterogeneous, sparse, and error prone. Although a plethora of tools for NGS data analysis has emerged in the past decade, (i) software development is still lagging behind data generation capabilities, and (ii) there is a 'cultural' gap between the end user and the developer. Generic software template libraries specifically developed for NGS can help in dealing with the former problem, whilst coupling template libraries with visual programming may help with the latter. Here we scrutinize the state-of-the-art low-level software libraries implemented specifically for NGS and graphical tools for NGS analytics. An ideal developing environment for NGS should be modular (with a native library interface), scalable in computational methods (i.e. serial, multithread, distributed), transparent (platform-independent), interoperable (with external software interface), and usable (via an intuitive graphical user interface). These characteristics should facilitate both the run of standardized NGS pipelines and the development of new workflows based on technological advancements or users' needs. We discuss in detail the potential of a computational framework blending generic template programming and visual programming that addresses all of the current limitations. In the long term, a proper, well-developed (although not necessarily unique) software framework will bridge the current gap between data generation and hypothesis testing. This will eventually facilitate the development of novel diagnostic tools embedded in routine healthcare.

Oak Ridge Bio-surveillance Toolkit (ORBiT): Integrating Big-Data Analytics with Visual Analysis for Public Health Dynamics

Energy Technology Data Exchange (ETDEWEB)

Ramanathan, Arvind [ORNL; Pullum, Laura L [ORNL; Steed, Chad A [ORNL; Chennubhotla, Chakra [University of Pittsburgh School of Medicine, Pittsburgh PA; Quinn, Shannon [University of Pittsburgh School of Medicine, Pittsburgh PA

2013-01-01

In this position paper, we describe the design and implementation of the Oak Ridge Bio-surveillance Toolkit (ORBiT): a collection of novel statistical and machine learning tools implemented for (1) integrating heterogeneous traditional (e.g. emergency room visits, prescription sales data, etc.) and non-traditional (social media such as Twitter and Instagram) data sources, (2) analyzing large-scale datasets and (3) presenting the results from the analytics as a visual interface for the end-user to interact and provide feedback. We present examples of how ORBiT can be used to summarize ex- tremely large-scale datasets effectively and how user interactions can translate into the data analytics process for bio-surveillance. We also present a strategy to estimate parameters relevant to dis- ease spread models from near real time data feeds and show how these estimates can be integrated with disease spread models for large-scale populations. We conclude with a perspective on how integrating data and visual analytics could lead to better forecasting and prediction of disease spread as well as improved awareness of disease susceptible regions.

Exploiting Spatial Abstraction in Predictive Analytics of Vehicle Traffic

Directory of Open Access Journals (Sweden)

Natalia Andrienko

2015-04-01

Full Text Available By applying visual analytics techniques to vehicle traffic data, we found a way to visualize and study the relationships between the traffic intensity and movement speed on links of a spatially abstracted transportation network. We observed that the traffic intensities and speeds in an abstracted network are interrelated in the same way as they are in a detailed street network at the level of street segments. We developed interactive visual interfaces that support representing these interdependencies by mathematical models. To test the possibility of utilizing them for performing traffic simulations on the basis of abstracted transportation networks, we devised a prototypical simulation algorithm employing these dependency models. The algorithm is embedded in an interactive visual environment for defining traffic scenarios, running simulations, and exploring their results. Our research demonstrates a principal possibility of performing traffic simulations on the basis of spatially abstracted transportation networks using dependency models derived from real traffic data. This possibility needs to be comprehensively investigated and tested in collaboration with transportation domain specialists.

Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 4 : use of knowledge integrated visual analytics system in supporting bridge management.

Science.gov (United States)

2009-12-01

The goals of integration should be: Supporting domain oriented data analysis through the use of : knowledge augmented visual analytics system. In this project, we focus on: : Providing interactive data exploration for bridge managements. : ...

Be the Data: Embodied Visual Analytics

Science.gov (United States)

Chen, Xin; Self, Jessica Zeitz; House, Leanna; Wenskovitch, John; Sun, Maoyuan; Wycoff, Nathan; Evia, Jane Robertson; Leman, Scotland; North, Chris

2018-01-01

With the rise of big data, it is becoming increasingly important to educate groups of students at many educational levels about data analytics. In particular, students without a strong mathematical background may have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods,…

Mapping the research on scientific collaboration

Institute of Scientific and Technical Information of China (English)

HOU Jianhua; CHEN Chaomei; YAN Jianxin

2010-01-01

The aim of this paper was to identify the trends and hot topics in the study of scientific collaboration via scientometric analysis.Information visualization and knowledge domain visualization techniques were adopted to determine how the study of scientific collaboration has evolved.A total of 1,455 articles on scientific cooperation published between 1993 and 2007 were retrieved from the SCI,SSCI and A&HCI databases with a topic search of scientific collaboration or scientific cooperation for the analysis.By using CiteSpace,the knowledge bases,research foci,and research fronts in the field of scientific collaboration were studied.The results indicated that research fronts and research foci are highly consistent in terms of the concept,origin,measurement,and theory of scientific collaboration.It also revealed that research fronts included scientific collaboration networks,international scientific collaboration,social network analysis and techniques,and applications of bibliometrical indicators,webmetrics,and health care related areas.

Enabling distributed collaborative science

DEFF Research Database (Denmark)

Hudson, T.; Sonnenwald, Diane H.; Maglaughlin, K.

2000-01-01

To enable collaboration over distance, a collaborative environment that uses a specialized scientific instrument called a nanoManipulator is evaluated. The nanoManipulator incorporates visualization and force feedback technology to allow scientists to see, feel, and modify biological samples bein...

Visualization analysis of author collaborations in schizophrenia research

OpenAIRE

Wu, Ying; Duan, Zhiguang

2015-01-01

Background Schizophrenia is a serious mental illness that levies a heavy medical toll and cost burden throughout the world. Scientific collaborations are necessary for progress in psychiatric research. However, there have been few publications on scientific collaborations in schizophrenia. The aim of this study was to investigate the extent of author collaborations in schizophrenia research. Methods This study used 58,107 records on schizophrenia from 2003 to 2012 which were downloaded from S...

Podium: Ranking Data Using Mixed-Initiative Visual Analytics.

Science.gov (United States)

Wall, Emily; Das, Subhajit; Chawla, Ravish; Kalidindi, Bharath; Brown, Eli T; Endert, Alex

2018-01-01

People often rank and order data points as a vital part of making decisions. Multi-attribute ranking systems are a common tool used to make these data-driven decisions. Such systems often take the form of a table-based visualization in which users assign weights to the attributes representing the quantifiable importance of each attribute to a decision, which the system then uses to compute a ranking of the data. However, these systems assume that users are able to quantify their conceptual understanding of how important particular attributes are to a decision. This is not always easy or even possible for users to do. Rather, people often have a more holistic understanding of the data. They form opinions that data point A is better than data point B but do not necessarily know which attributes are important. To address these challenges, we present a visual analytic application to help people rank multi-variate data points. We developed a prototype system, Podium, that allows users to drag rows in the table to rank order data points based on their perception of the relative value of the data. Podium then infers a weighting model using Ranking SVM that satisfies the user's data preferences as closely as possible. Whereas past systems help users understand the relationships between data points based on changes to attribute weights, our approach helps users to understand the attributes that might inform their understanding of the data. We present two usage scenarios to describe some of the potential uses of our proposed technique: (1) understanding which attributes contribute to a user's subjective preferences for data, and (2) deconstructing attributes of importance for existing rankings. Our proposed approach makes powerful machine learning techniques more usable to those who may not have expertise in these areas.

Supporting exploration awareness for visual analytics

NARCIS (Netherlands)

Shrinivasan, Y.B.; Wijk, van J.J.

2008-01-01

While exploring data using information visualization, analysts try to make sense of the data, build cases, and present them to others. However, if the exploration is long or done in multiple sessions, it can be hard for analysts to remember all interesting visualizations and the relationships among

SIMON: Remote collaboration system based on large scale simulation

International Nuclear Information System (INIS)

Sugawara, Akihiro; Kishimoto, Yasuaki

2003-01-01

Development of SIMON (SImulation MONitoring) system is described. SIMON aims to investigate many physical phenomena of tokamak type nuclear fusion plasma by simulation and to exchange information and to carry out joint researches with scientists in the world using internet. The characteristics of SIMON are followings; 1) decrease load of simulation by trigger sending method, 2) visualization of simulation results and hierarchical structure of analysis, 3) decrease of number of license by using command line when software is used, 4) improvement of support for using network of simulation data output by use of HTML (Hyper Text Markup Language), 5) avoidance of complex built-in work in client part and 6) small-sized and portable software. The visualization method of large scale simulation, remote collaboration system by HTML, trigger sending method, hierarchical analytical method, introduction into three-dimensional electromagnetic transportation code and technologies of SIMON system are explained. (S.Y.)

Collaborative Interactive Visualization Exploratory Concept

Science.gov (United States)

2015-06-01

virtual reality, spatial computing, virtual assistants that are capable of operating at high cognitive levels, extensible work spaces, conferencing ...process of communication using electronic assets and accompanying software designed for use in remote locations. Recent technological advancements in...collaborative possibilities. Newest generations of hand-held electronic devices feature video, audio, and on- screen drawing in addition to capabilities

Visualizing Decision Trees in Games to Support Children's Analytic Reasoning: Any Negative Effects on Gameplay?

OpenAIRE

Haworth, Robert; Tagh Bostani, Sousan Sheida; Sedig, Kamran

2010-01-01

The popularity and usage of digital games has increased in recent years, bringing further attention to their design. Some digital games require a significant use of higher order thought processes, such as problem solving and reflective and analytical thinking. Through the use of appropriate and interactive representations, these thought processes could be supported. A visualization of the game's internal structure is an example of this. However, it is unknown whether including these extra rep...

Map Archive Mining: Visual-Analytical Approaches to Explore Large Historical Map Collections

Directory of Open Access Journals (Sweden)

Johannes H. Uhl

2018-04-01

Full Text Available Historical maps are unique sources of retrospective geographical information. Recently, several map archives containing map series covering large spatial and temporal extents have been systematically scanned and made available to the public. The geographical information contained in such data archives makes it possible to extend geospatial analysis retrospectively beyond the era of digital cartography. However, given the large data volumes of such archives (e.g., more than 200,000 map sheets in the United States Geological Survey topographic map archive and the low graphical quality of older, manually-produced map sheets, the process to extract geographical information from these map archives needs to be automated to the highest degree possible. To understand the potential challenges (e.g., salient map characteristics and data quality variations in automating large-scale information extraction tasks for map archives, it is useful to efficiently assess spatio-temporal coverage, approximate map content, and spatial accuracy of georeferenced map sheets at different map scales. Such preliminary analytical steps are often neglected or ignored in the map processing literature but represent critical phases that lay the foundation for any subsequent computational processes including recognition. Exemplified for the United States Geological Survey topographic map and the Sanborn fire insurance map archives, we demonstrate how such preliminary analyses can be systematically conducted using traditional analytical and cartographic techniques, as well as visual-analytical data mining tools originating from machine learning and data science.

Reflexive Learning through Visual Methods

DEFF Research Database (Denmark)

Frølunde, Lisbeth

2014-01-01

What. This chapter concerns how visual methods and visual materials can support visually oriented, collaborative, and creative learning processes in education. The focus is on facilitation (guiding, teaching) with visual methods in learning processes that are designerly or involve design. Visual...... methods are exemplified through two university classroom cases about collaborative idea generation processes. The visual methods and materials in the cases are photo elicitation using photo cards, and modeling with LEGO Serious Play sets. Why. The goal is to encourage the reader, whether student...... or professional, to facilitate with visual methods in a critical, reflective, and experimental way. The chapter offers recommendations for facilitating with visual methods to support playful, emergent designerly processes. The chapter also has a critical, situated perspective. Where. This chapter offers case...

Exploring Vaccine Hesitancy Through an Artist-Scientist Collaboration : Visualizing Vaccine-Critical Parents' Health Beliefs.

Science.gov (United States)

Koski, Kaisu; Holst, Johan

2017-09-01

This project explores vaccine hesitancy through an artist-scientist collaboration. It aims to create better understanding of vaccine hesitant parents' health beliefs and how these influence their vaccine-critical decisions. The project interviews vaccine-hesitant parents in the Netherlands and Finland and develops experimental visual-narrative means to analyse the interview data. Vaccine-hesitant parents' health beliefs are, in this study, expressed through stories, and they are paralleled with so-called illness narratives. The study explores the following four main health beliefs originating from the parents' interviews: (1) perceived benefits of illness, (2) belief in the body's intelligence and self-healing capacity, (3) beliefs about the "inside-outside" flow of substances in the body, and (4) view of death as a natural part of life. These beliefs are interpreted through arts-based diagrammatic representations. These diagrams, merging multiple aspects of the parents' narratives, are subsequently used in a collaborative meaning-making dialogue between the artist and the scientist. The resulting dialogue contrasts the health beliefs behind vaccine hesitancy with scientific knowledge, as well as the authors' personal, and differing, attitudes toward these.

Social Set Visualizer

DEFF Research Database (Denmark)

Flesch, Benjamin; Hussain, Abid; Vatrapu, Ravi

2015-01-01

-edge open source visual analytics libraries from D3.js and creation of new visualizations (ac-tor mobility across time, conversational comets etc). Evaluation of the dashboard consisting of technical testing, usability testing, and domain-specific testing with CSR students and yielded positive results.......This paper presents a state-of-the art visual analytics dash-board, Social Set Visualizer (SoSeVi), of approximately 90 million Facebook actions from 11 different companies that have been mentioned in the traditional media in relation to garment factory accidents in Bangladesh. The enterprise...

Distance collaborations with industry

Energy Technology Data Exchange (ETDEWEB)

Peskin, A.; Swyler, K.

1998-06-01

The college industry relationship has been identified as a key policy issue in Engineering Education. Collaborations between academic institutions and the industrial sector have a long history and a bright future. For Engineering and Engineering Technology programs in particular, industry has played a crucial role in many areas including advisement, financial support, and practical training of both faculty and students. Among the most important and intimate interactions are collaborative projects and formal cooperative education arrangements. Most recently, such collaborations have taken on a new dimension, as advances in technology have made possible meaningful technical collaboration at a distance. There are several obvious technology areas that have contributed significantly to this trend. Foremost is the ubiquitous presence of the Internet. Perhaps almost as important are advances in computer based imaging. Because visual images offer a compelling user experience, it affords greater knowledge transfer efficiency than other modes of delivery. Furthermore, the quality of the image appears to have a strongly correlated effect on insight. A good visualization facility offers both a means for communication and a shared information space for the subjects, which are among the essential features of both peer collaboration and distance learning.

Supporting tactical intelligence using collaborative environments and social networking

Science.gov (United States)

Wollocko, Arthur B.; Farry, Michael P.; Stark, Robert F.

2013-05-01

Modern military environments place an increased emphasis on the collection and analysis of intelligence at the tactical level. The deployment of analytical tools at the tactical level helps support the Warfighter's need for rapid collection, analysis, and dissemination of intelligence. However, given the lack of experience and staffing at the tactical level, most of the available intelligence is not exploited. Tactical environments are staffed by a new generation of intelligence analysts who are well-versed in modern collaboration environments and social networking. An opportunity exists to enhance tactical intelligence analysis by exploiting these personnel strengths, but is dependent on appropriately designed information sharing technologies. Existing social information sharing technologies enable users to publish information quickly, but do not unite or organize information in a manner that effectively supports intelligence analysis. In this paper, we present an alternative approach to structuring and supporting tactical intelligence analysis that combines the benefits of existing concepts, and provide detail on a prototype system embodying that approach. Since this approach employs familiar collaboration support concepts from social media, it enables new-generation analysts to identify the decision-relevant data scattered among databases and the mental models of other personnel, increasing the timeliness of collaborative analysis. Also, the approach enables analysts to collaborate visually to associate heterogeneous and uncertain data within the intelligence analysis process, increasing the robustness of collaborative analyses. Utilizing this familiar dynamic collaboration environment, we hope to achieve a significant reduction of time and skill required to glean actionable intelligence in these challenging operational environments.

The Space-Time Cube as part of a GeoVisual Analytics Environment to support the understanding of movement data

DEFF Research Database (Denmark)

Kveladze, Irma; Kraak, M. J.; van Elzakker, C. P. J. M.

2015-01-01

This paper reports the results of an empirical usability experiment on the performance of the space-time cube in a GeoVisual analytics environment. It was developed to explore movement data based on the requirements of human geographers. The interactive environment consists of multiple coordinated...

Social Set Visualizer (SoSeVi) II

DEFF Research Database (Denmark)

Flesch, Benjamin; Vatrapu, Ravi

2016-01-01

This paper reports the second iteration of the Social Set Visualizer (SoSeVi), a set theoretical visual analytics dashboard of big social data. In order to further demonstrate its usefulness in large-scale visual analytics tasks of individual and collective behavior of actors in social networks......, the current iteration of the Social Set Visualizer (SoSeVi) in version II builds on recent advancements in visualizing set intersections. The development of the SoSeVi dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility...

GANViz: A Visual Analytics Approach to Understand the Adversarial Game.

Science.gov (United States)

Wang, Junpeng; Gou, Liang; Yang, Hao; Shen, Han-Wei

2018-06-01

Generative models bear promising implications to learn data representations in an unsupervised fashion with deep learning. Generative Adversarial Nets (GAN) is one of the most popular frameworks in this arena. Despite the promising results from different types of GANs, in-depth understanding on the adversarial training process of the models remains a challenge to domain experts. The complexity and the potential long-time training process of the models make it hard to evaluate, interpret, and optimize them. In this work, guided by practical needs from domain experts, we design and develop a visual analytics system, GANViz, aiming to help experts understand the adversarial process of GANs in-depth. Specifically, GANViz evaluates the model performance of two subnetworks of GANs, provides evidence and interpretations of the models' performance, and empowers comparative analysis with the evidence. Through our case studies with two real-world datasets, we demonstrate that GANViz can provide useful insight into helping domain experts understand, interpret, evaluate, and potentially improve GAN models.

An Application Server for Collaborative Work

International Nuclear Information System (INIS)

Dr. Stevetiana Shasharina

2000-01-01

Remote collaboration involving development and execution of applications is currently difficult. Joint remote data visualization is often carried out through file transfers followed by separate viewing without coordination or collaborative capability. Joint editing of files, as is needed for code development or document generation, is also difficult. Additionally, asynchronous collaboration capabilities are needed

Comparing the Effect of Audio and Visual Notifications on Workspace Awareness using Head-Mounted Displays for Remote Collaboration in Augmented Reality

NARCIS (Netherlands)

Cidota, M.A.; Lukosch, S.G.; Datcu, D.; Lukosch, H.K.

2016-01-01

In many fields of activity, working in teams is necessary for completing tasks in a proper manner and often requires visual context-related information to be exchanged between team members. In such a collaborative environment, awareness of other people’s activity is an important feature of

Collaboration between student art teachers and communication and digital media students promoting subject specific didactics in digital visual learning design

DEFF Research Database (Denmark)

Skov, Kirsten; Buhl, Mie

into account. Our discussion of the potential for developing digital learning application from a collaborative approach is based on the visual design products, interviews and written reports, as well as shared experiences from the stakeholders in the project. Results: The project revealed three digital visual......=pdf Dunleavy, M. & Dede, C. (2014). Augmented reality teaching and learning. in. J.M. Spector, M.D. Merrill, J. Elen & M.J. Bishop (eds), The handbook og research for educational communications and technology New York: Springer http://isites.harvard.edu/fs/docs/icb.topic1116077.files....../DunleavyDedeARfinal.pdf Rasmussen, H. (2015). Digital Picture Production and Picture aesthetic Competency in It-didactic Design. Risk and opportunities for visual arts education in Europe. Proceedings, InSEA conferene, Lisbon, Portugal...

Advanced Data Analytics and Visualisation for the Management of Human Perception of Safety and Security in Urban Spaces

OpenAIRE

Melas , Panos; Correndo , Gianluca; Middleton , Lee; Sabeur , Zoheir ,

2015-01-01

Part 7: Analytics and Visualization; International audience; The genesis of this work began during the DESURBS project. The scope of the project was to help build a collaborative decision-support system portal where spatial planning professionals could learn about designing much more secure and safer spaces in urban areas. The portal achieved this via integrating a number of tools under a common, simple to use, interface. However, the deficiencies in the project became apparent with subsequen...

An Analysis of Machine- and Human-Analytics in Classification.

Science.gov (United States)

Tam, Gary K L; Kothari, Vivek; Chen, Min

2017-01-01

In this work, we present a study that traces the technical and cognitive processes in two visual analytics applications to a common theoretic model of soft knowledge that may be added into a visual analytics process for constructing a decision-tree model. Both case studies involved the development of classification models based on the "bag of features" approach. Both compared a visual analytics approach using parallel coordinates with a machine-learning approach using information theory. Both found that the visual analytics approach had some advantages over the machine learning approach, especially when sparse datasets were used as the ground truth. We examine various possible factors that may have contributed to such advantages, and collect empirical evidence for supporting the observation and reasoning of these factors. We propose an information-theoretic model as a common theoretic basis to explain the phenomena exhibited in these two case studies. Together we provide interconnected empirical and theoretical evidence to support the usefulness of visual analytics.

Widget, widget as you lead, I am performing well indeed! Using results from an exploratory offline study to inform an empirical online study about a learning analytics widget in a collaborative learning environment

NARCIS (Netherlands)

Scheffel, Maren; Drachsler, Hendrik; Kreijns, Karel; De Kraker, Joop; Specht, Marcus

2017-01-01

The collaborative learning processes of students in online learning environments can be supported by providing learning analytics-based visualisations that foster awareness and reflection about an individual's as well as the team's behaviour and their learning and collaboration processes. For this

A study on haptic collaborative game in shared virtual environment

Science.gov (United States)

Lu, Keke; Liu, Guanyang; Liu, Lingzhi

2013-03-01

A study on collaborative game in shared virtual environment with haptic feedback over computer networks is introduced in this paper. A collaborative task was used where the players located at remote sites and played the game together. The player can feel visual and haptic feedback in virtual environment compared to traditional networked multiplayer games. The experiment was desired in two conditions: visual feedback only and visual-haptic feedback. The goal of the experiment is to assess the impact of force feedback on collaborative task performance. Results indicate that haptic feedback is beneficial for performance enhancement for collaborative game in shared virtual environment. The outcomes of this research can have a powerful impact on the networked computer games.

Analyzing Earth Science Research Networking through Visualizations

Science.gov (United States)

Hasnain, S.; Stephan, R.; Narock, T.

2017-12-01

Using D3.js we visualize collaboration amongst several geophysical science organizations, such as the American Geophysical Union (AGU) and the Federation of Earth Science Information Partners (ESIP). We look at historical trends in Earth Science research topics, cross-domain collaboration, and topics of interest to the general population. The visualization techniques used provide an effective way for non-experts to easily explore distributed and heterogeneous Big Data. Analysis of these visualizations provides stakeholders with insights into optimizing meetings, performing impact evaluation, structuring outreach efforts, and identifying new opportunities for collaboration.

VAiRoma: A Visual Analytics System for Making Sense of Places, Times, and Events in Roman History.

Science.gov (United States)

Cho, Isaac; Dou, Wewnen; Wang, Derek Xiaoyu; Sauda, Eric; Ribarsky, William

2016-01-01

Learning and gaining knowledge of Roman history is an area of interest for students and citizens at large. This is an example of a subject with great sweep (with many interrelated sub-topics over, in this case, a 3,000 year history) that is hard to grasp by any individual and, in its full detail, is not available as a coherent story. In this paper, we propose a visual analytics approach to construct a data driven view of Roman history based on a large collection of Wikipedia articles. Extracting and enabling the discovery of useful knowledge on events, places, times, and their connections from large amounts of textual data has always been a challenging task. To this aim, we introduce VAiRoma, a visual analytics system that couples state-of-the-art text analysis methods with an intuitive visual interface to help users make sense of events, places, times, and more importantly, the relationships between them. VAiRoma goes beyond textual content exploration, as it permits users to compare, make connections, and externalize the findings all within the visual interface. As a result, VAiRoma allows users to learn and create new knowledge regarding Roman history in an informed way. We evaluated VAiRoma with 16 participants through a user study, with the task being to learn about roman piazzas through finding relevant articles and new relationships. Our study results showed that the VAiRoma system enables the participants to find more relevant articles and connections compared to Web searches and literature search conducted in a roman library. Subjective feedback on VAiRoma was also very positive. In addition, we ran two case studies that demonstrate how VAiRoma can be used for deeper analysis, permitting the rapid discovery and analysis of a small number of key documents even when the original collection contains hundreds of thousands of documents.

The global lambda visualization facility: An international ultra-high-definition wide-area visualization collaboratory

Science.gov (United States)

Leigh, J.; Renambot, L.; Johnson, Aaron H.; Jeong, B.; Jagodic, R.; Schwarz, N.; Svistula, D.; Singh, R.; Aguilera, J.; Wang, X.; Vishwanath, V.; Lopez, B.; Sandin, D.; Peterka, T.; Girado, J.; Kooima, R.; Ge, J.; Long, L.; Verlo, A.; DeFanti, T.A.; Brown, M.; Cox, D.; Patterson, R.; Dorn, P.; Wefel, P.; Levy, S.; Talandis, J.; Reitzer, J.; Prudhomme, T.; Coffin, T.; Davis, B.; Wielinga, P.; Stolk, B.; Bum, Koo G.; Kim, J.; Han, S.; Corrie, B.; Zimmerman, T.; Boulanger, P.; Garcia, M.

2006-01-01

The research outlined in this paper marks an initial global cooperative effort between visualization and collaboration researchers to build a persistent virtual visualization facility linked by ultra-high-speed optical networks. The goal is to enable the comprehensive and synergistic research and development of the necessary hardware, software and interaction techniques to realize the next generation of end-user tools for scientists to collaborate on the global Lambda Grid. This paper outlines some of the visualization research projects that were demonstrated at the iGrid 2005 workshop in San Diego, California.

HydroShare: A Platform for Collaborative Data and Model Sharing in Hydrology

Science.gov (United States)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Couch, A.; Hooper, R. P.; Dash, P. K.; Stealey, M.; Yi, H.; Bandaragoda, C.; Castronova, A. M.

2017-12-01

HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of and collaboration around "resources" which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting its use as a virtual environment supporting education and research. HydroShare has components that support: (1) resource storage, (2) resource exploration, and (3) web apps for actions on resources. The HydroShare data discovery, sharing and publishing functions as well as HydroShare web apps provide the capability to analyze data and execute models completely in the cloud (servers remote from the user) overcoming desktop platform limitations. The HydroShare GIS app provides a basic capability to visualize spatial data. The HydroShare JupyterHub Notebook app provides flexible and documentable execution of Python code snippets for analysis and modeling in a way that results can be shared among HydroShare users and groups to support research collaboration and education. We will discuss how these developments can be used to support different types of educational efforts in Hydrology where being completely web based is of value in an educational setting as students can all have access to the same functionality regardless of their computer.

SEURAT: visual analytics for the integrated analysis of microarray data.

Science.gov (United States)

Gribov, Alexander; Sill, Martin; Lück, Sonja; Rücker, Frank; Döhner, Konstanze; Bullinger, Lars; Benner, Axel; Unwin, Antony

2010-06-03

In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

SEURAT: Visual analytics for the integrated analysis of microarray data

Directory of Open Access Journals (Sweden)

Bullinger Lars

2010-06-01

Full Text Available Abstract Background In translational cancer research, gene expression data is collected together with clinical data and genomic data arising from other chip based high throughput technologies. Software tools for the joint analysis of such high dimensional data sets together with clinical data are required. Results We have developed an open source software tool which provides interactive visualization capability for the integrated analysis of high-dimensional gene expression data together with associated clinical data, array CGH data and SNP array data. The different data types are organized by a comprehensive data manager. Interactive tools are provided for all graphics: heatmaps, dendrograms, barcharts, histograms, eventcharts and a chromosome browser, which displays genetic variations along the genome. All graphics are dynamic and fully linked so that any object selected in a graphic will be highlighted in all other graphics. For exploratory data analysis the software provides unsupervised data analytics like clustering, seriation algorithms and biclustering algorithms. Conclusions The SEURAT software meets the growing needs of researchers to perform joint analysis of gene expression, genomical and clinical data.

Learning analytics dashboard applications

NARCIS (Netherlands)

Verbert, K.; Duval, E.; Klerkx, J.; Govaerts, S.; Santos, J.L.

2013-01-01

This article introduces learning analytics dashboards that visualize learning traces for learners and teachers. We present a conceptual framework that helps to analyze learning analytics applications for these kinds of users. We then present our own work in this area and compare with 15 related

Evaluating the use of programming games for building early analytical thinking skills

Directory of Open Access Journals (Sweden)

H. Tsalapatas

2015-11-01

Full Text Available Analytical thinking is a transversal skill that helps learners excel academically independently of theme area. It is on high demand in the world of work especially in innovation related sectors. It involves finding a viable solution to a problem by identifying goals, parameters, and resources available for deployment. These are strategy elements in game play. They further constitute good practices in programming. This work evaluates how serious games based on visual programming as a solution synthesis tool within exploration, inquiry, and collaboration can help learners build structured mindsets. It analyses how a visual programming environment that supports experimentation for building intuition on potential solutions to logical puzzles, and then encourages learners to synthesize a solution interactively, helps learners through gaming principles to build self-esteem on their problem solving ability, to develop algorithmic thinking capacity, and to stay engaged in learning.

Analytical Thinking, Analytical Action: Using Prelab Video Demonstrations and e-Quizzes to Improve Undergraduate Preparedness for Analytical Chemistry Practical Classes

Science.gov (United States)

Jolley, Dianne F.; Wilson, Stephen R.; Kelso, Celine; O'Brien, Glennys; Mason, Claire E.

2016-01-01

This project utilizes visual and critical thinking approaches to develop a higher-education synergistic prelab training program for a large second-year undergraduate analytical chemistry class, directing more of the cognitive learning to the prelab phase. This enabled students to engage in more analytical thinking prior to engaging in the…

Optimization of drug-drug interaction alert rules in a pediatric hospital's electronic health record system using a visual analytics dashboard.

Science.gov (United States)

Simpao, Allan F; Ahumada, Luis M; Desai, Bimal R; Bonafide, Christopher P; Gálvez, Jorge A; Rehman, Mohamed A; Jawad, Abbas F; Palma, Krisha L; Shelov, Eric D

2015-03-01

To develop and evaluate an electronic dashboard of hospital-wide electronic health record medication alerts for an alert fatigue reduction quality improvement project. We used visual analytics software to develop the dashboard. We collaborated with the hospital-wide Clinical Decision Support committee to perform three interventions successively deactivating clinically irrelevant drug-drug interaction (DDI) alert rules. We analyzed the impact of the interventions on care providers' and pharmacists' alert and override rates using an interrupted time series framework with piecewise regression. We evaluated 2 391 880 medication alerts between January 31, 2011 and January 26, 2014. For pharmacists, the median alert rate prior to the first DDI deactivation was 58.74 alerts/100 orders (IQR 54.98-60.48) and 25.11 alerts/100 orders (IQR 23.45-26.57) following the three interventions (pdashboard facilitated safe rapid-cycle reductions in alert burden that were temporally associated with lower pharmacist override rates in a subgroup of DDIs not directly affected by the interventions; meanwhile, the pharmacists' frequency of selecting the 'cancel' option increased. We hypothesize that reducing the alert burden enabled pharmacists to devote more attention to clinically relevant alerts. © The Author 2014. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Exploring communication of resistance in cross-sector collaboration:

DEFF Research Database (Denmark)

Plotnikof, Mie

his study addresses the role of resistance in cross-sector collaboration. It explores how resistance is communicated during collaboration to better understand not just its destructive, but also constructive effects on organizing cross-sector collaboration. In so doing, the paper conceptualizes...... to the process. Thereby, the study contributes with theorizing resistance and offers analytical insights on its dynamics and effects on organizing cross-sector collaboration....

Remote Collaboration With Mixed Reality Displays

DEFF Research Database (Denmark)

Müller, Jens; Rädle, Roman; Reiterer, Harald

2017-01-01

HCI research has demonstrated Mixed Reality (MR) as being beneficial for co-located collaborative work. For remote collaboration, however, the collaborators' visual contexts do not coincide due to their individual physical environments. The problem becomes apparent when collaborators refer...... to physical landmarks in their individual environments to guide each other's attention. In an experimental study with 16 dyads, we investigated how the provisioning of shared virtual landmarks (SVLs) influences communication behavior and user experience. A quantitative analysis revealed that participants used...

NASA's Spaceflight Visual Impairment and Intracranial Hypertension Research Plan: An accelerated Research Collaboration

Science.gov (United States)

Otto, Christian; Fogarty, J.; Grounds, D.; Davis, J.

2010-01-01

To date six long duration astronauts have experienced in flight visual changes and post flight signs of optic disc edema, globe flattening, choroidal folds, hyperoptic shifts and or raised intracranial pressure. In some cases the changes were transient while in others they are persistent with varying degrees of visual impairment. Given that all astronauts exposed to microgravity experience a cephalad fluid shift, and that both symptomatic and asymptomatic patients have exhibited optic nerve sheath edema on MRI, there is a high probability that all astronauts develop in-flight idiopathic intracranial hypertension to some degree. Those who are susceptible, have an increased likelihood of developing treatment resistant papilledema resulting in visual impairment and possible long-term vision loss. Such an acquired disability would have a profound mission impact and would be detrimental to the long term health of the astronaut. The visual impairment and increased intracranial pressure phenomenon appears to have multiple contributing factors. Consequently, the working "physiological fault bush" with elevated intracranial pressure at its center, is divided into ocular effects, and CNS and other effects. Some of these variables have been documented and or measured through operational data gathering, while others are unknown, undocumented and or hypothetical. Both the complexity of the problem and the urgency to find a solution require that a unique, non-traditional research model be employed such as the Accelerated Research Collaboration(TM) (ARC) model that has been pioneered by the Myelin Repair Foundation. In the ARC model a single entity facilitates and manages all aspects of the basic, translational, and clinical research, providing expert oversight for both scientific and managerial efforts. The result is a comprehensive research plan executed by a multidisciplinary team and the elimination of stove-piped research. The ARC model emphasizes efficient and effective

Visual Analytics for Pattern Discovery in Home Care

Science.gov (United States)

Monsen, Karen A.; Bae, Sung-Heui; Zhang, Wenhui

2016-01-01

Summary Background Visualization can reduce the cognitive load of information, allowing users to easily interpret and assess large amounts of data. The purpose of our study was to examine home health data using visual analysis techniques to discover clinically salient associations between patient characteristics with problem-oriented health outcomes of older adult home health patients during the home health service period. Methods Knowledge, Behavior and Status ratings at discharge as well as change from admission to discharge that was coded using the Omaha System was collected from a dataset on 988 de-identified patient data from 15 home health agencies. SPSS Visualization Designer v1.0 was used to visually analyze patterns between independent and outcome variables using heat maps and histograms. Visualizations suggesting clinical salience were tested for significance using correlation analysis. Results The mean age of the patients was 80 years, with the majority female (66%). Of the 150 visualizations, 69 potentially meaningful patterns were statistically evaluated through bivariate associations, revealing 21 significant associations. Further, 14 associations between episode length and Charlson co-morbidity index mainly with urinary related diagnoses and problems remained significant after adjustment analyses. Through visual analysis, the adverse association of the longer home health episode length and higher Charlson co-morbidity index with behavior or status outcomes for patients with impaired urinary function was revealed. Conclusions We have demonstrated the use of visual analysis to discover novel patterns that described high-needs subgroups among the older home health patient population. The effective presentation of these data patterns can allow clinicians to identify areas of patient improvement, and time periods that are most effective for implementing home health interventions to improve patient outcomes. PMID:27466053

EPIPOI: A user-friendly analytical tool for the extraction and visualization of temporal parameters from epidemiological time series

Directory of Open Access Journals (Sweden)

Alonso Wladimir J

2012-11-01

Full Text Available Abstract Background There is an increasing need for processing and understanding relevant information generated by the systematic collection of public health data over time. However, the analysis of those time series usually requires advanced modeling techniques, which are not necessarily mastered by staff, technicians and researchers working on public health and epidemiology. Here a user-friendly tool, EPIPOI, is presented that facilitates the exploration and extraction of parameters describing trends, seasonality and anomalies that characterize epidemiological processes. It also enables the inspection of those parameters across geographic regions. Although the visual exploration and extraction of relevant parameters from time series data is crucial in epidemiological research, until now it had been largely restricted to specialists. Methods EPIPOI is freely available software developed in Matlab (The Mathworks Inc that runs both on PC and Mac computers. Its friendly interface guides users intuitively through useful comparative analyses including the comparison of spatial patterns in temporal parameters. Results EPIPOI is able to handle complex analyses in an accessible way. A prototype has already been used to assist researchers in a variety of contexts from didactic use in public health workshops to the main analytical tool in published research. Conclusions EPIPOI can assist public health officials and students to explore time series data using a broad range of sophisticated analytical and visualization tools. It also provides an analytical environment where even advanced users can benefit by enabling a higher degree of control over model assumptions, such as those associated with detecting disease outbreaks and pandemics.

COLLABORATIVE TRIAL AND QUALITY CONTROL IN CHEMICAL ANALYSIS

Directory of Open Access Journals (Sweden)

Narsito Narsito

2010-06-01

Full Text Available Abstract                                                             This paper deals with some practical problems related to the quality of analytical chemical data usually met in practice. Special attention is given to the topic of quality control in analytical chemistry, since analytical data is one of the primary information from which some important scientifically based decision are to be made. The present paper starts with brief description on some fundamental aspects associated with quality of analytical data, such as sources of variation of analytical data, criteria for quality of analytical method, quality assurance in chemical analysis. The assessment of quality parameter for analytical method like the use of standard materials as well as standard methods is given. Concerning with the quality control of analytical data, the use of several techniques, such as control samples and control charts, in monitoring analytical data in quality control program are described qualitatively.  In the final part of this paper, some important remarks for the preparation of collaborative trials, including the evaluation of accuracy and reproducibility of analytical method are also given Keywords: collaborative trials, quality control, analytical data Abstract                                                             This paper deals with some practical problems related to the quality of analytical chemical data usually met in practice. Special attention is given to the topic of quality control in analytical chemistry, since analytical data is one of the primary information from which some important scientifically based decision are to be made. The present paper starts with brief description on some fundamental aspects associated with quality of analytical data, such as sources of variation of analytical data, criteria for quality of

Technical report on the Korea-Japan software collaboration

International Nuclear Information System (INIS)

Inamura, Yasuhiro; Nakajima, Kenji; Nakatani, Takeshi; Kajimoto, Ryoichi; Arai, Masatoshi; So, Ji-Yong; Moon, Myung-Kook; Lee, Chang-Hee; Suzuki, Jiro; Otomo, Toshiya; Yasu, Yoshiji; Nakayoshi, Kazuo; Sendai, Hiroshi; Nam, Uk-Won; Park, Je-Geun

2011-02-01

Both Materials and Life Science Experimental Facility (MLF) of J-PARC and HANARO of KAERI started new neutron facility projects in 2002 and 2003, respectively. As part of their projects, both institutes began developments of new Time-of-Flight (ToF) spectrometer including DC-TOF of HANARO, 4SEASONS and AMATERAS of MLF. With this new instrument development, we saw an opportunity for collaboration between Korea and Japan regarding ToF software. This Korea-Japan collaboration officially started in 2007 with an initially 6 items as its final goal. The 6 items include 1) basic data reduction software, 2) informative visualization software, 3) data visualization software, 4) decision making and optimization software, 5) single crystal alignment software, and 6) advanced analysis software. Using Manyo library developed at J-PARC as our software framework, we developed our software based on a combination of Python and C++ wrapped under SWIG. In August 2008 we successfully released a beta-version of basic data reduction software which has been tested at the 2 beamlines of MLF; 4SEASONS and AMATERAS, and regularly updated. Other 2 beta-versions of informative visualization software and data visualization software have also been released and are successfully used during experiments at 4SEASONS and AMATERAS. Although we have had several discussions on the 3 remaining topics of the original goal of this collaboration, progress has been rather limited on these items. Therefore, we decided to consider them as the subject of the next Korea-Japan collaboration. This report summarizes the 2-years (2007-2009) activities of Korea-Japan collaboration of chopper software development. Here we describe the background of the collaboration and the main part of our work. We also discuss briefly a future plan of our collaboration starting in 2010. Some of detailed descriptions on the activities of the collaboration as well as related information are given in appendix. (author)

The machine in multimedia analytics

NARCIS (Netherlands)

Zahálka, J.

2017-01-01

This thesis investigates the role of the machine in multimedia analytics, a discipline that combines visual analytics with multimedia analysis algorithms in order to unlock the potential of multimedia collections as sources of knowledge in scientific and applied domains. Specifically, the central

Using visualizations to support collaboration and coordination during computer-supported collaborative learning

NARCIS (Netherlands)

Janssen, J.J.H.M.

2008-01-01

This thesis addresses the topic of computer-supported collaborative learning (CSCL in short). In a CSCL-environment, students work in small groups on complex and challenging tasks. Although the teacher guides this process at a distance, students have to regulate and monitor their own learning

Attention and visual memory in visualization and computer graphics.

Science.gov (United States)

Healey, Christopher G; Enns, James T

2012-07-01

A fundamental goal of visualization is to produce images of data that support visual analysis, exploration, and discovery of novel insights. An important consideration during visualization design is the role of human visual perception. How we "see" details in an image can directly impact a viewer's efficiency and effectiveness. This paper surveys research on attention and visual perception, with a specific focus on results that have direct relevance to visualization and visual analytics. We discuss theories of low-level visual perception, then show how these findings form a foundation for more recent work on visual memory and visual attention. We conclude with a brief overview of how knowledge of visual attention and visual memory is being applied in visualization and graphics. We also discuss how challenges in visualization are motivating research in psychophysics.

Does the Medium Matter in Collaboration? Using Visually Supported Collaboration Technology in an Interior Design Studio

Science.gov (United States)

Cho, Ji Young; Cho, Moon-Heum; Kozinets, Nadya

2016-01-01

With the recognition of the importance of collaboration in a design studio and the advancement of technology, increasing numbers of design students collaborate with others in a technology-mediated learning environment (TMLE); however, not all students have positive experiences in TMLEs. One possible reason for unsatisfactory collaboration…

Entropy-based heavy tailed distribution transformation and visual analytics for monitoring massive network traffic

Science.gov (United States)

Han, Keesook J.; Hodge, Matthew; Ross, Virginia W.

2011-06-01

For monitoring network traffic, there is an enormous cost in collecting, storing, and analyzing network traffic datasets. Data mining based network traffic analysis has a growing interest in the cyber security community, but is computationally expensive for finding correlations between attributes in massive network traffic datasets. To lower the cost and reduce computational complexity, it is desirable to perform feasible statistical processing on effective reduced datasets instead of on the original full datasets. Because of the dynamic behavior of network traffic, traffic traces exhibit mixtures of heavy tailed statistical distributions or overdispersion. Heavy tailed network traffic characterization and visualization are important and essential tasks to measure network performance for the Quality of Services. However, heavy tailed distributions are limited in their ability to characterize real-time network traffic due to the difficulty of parameter estimation. The Entropy-Based Heavy Tailed Distribution Transformation (EHTDT) was developed to convert the heavy tailed distribution into a transformed distribution to find the linear approximation. The EHTDT linearization has the advantage of being amenable to characterize and aggregate overdispersion of network traffic in realtime. Results of applying the EHTDT for innovative visual analytics to real network traffic data are presented.

The role of 3-D interactive visualization in blind surveys of H I in galaxies

Science.gov (United States)

Punzo, D.; van der Hulst, J. M.; Roerdink, J. B. T. M.; Oosterloo, T. A.; Ramatsoku, M.; Verheijen, M. A. W.

2015-09-01

Upcoming H I surveys will deliver large datasets, and automated processing using the full 3-D information (two positional dimensions and one spectral dimension) to find and characterize H I objects is imperative. In this context, visualization is an essential tool for enabling qualitative and quantitative human control on an automated source finding and analysis pipeline. We discuss how Visual Analytics, the combination of automated data processing and human reasoning, creativity and intuition, supported by interactive visualization, enables flexible and fast interaction with the 3-D data, helping the astronomer to deal with the analysis of complex sources. 3-D visualization, coupled to modeling, provides additional capabilities helping the discovery and analysis of subtle structures in the 3-D domain. The requirements for a fully interactive visualization tool are: coupled 1-D/2-D/3-D visualization, quantitative and comparative capabilities, combined with supervised semi-automated analysis. Moreover, the source code must have the following characteristics for enabling collaborative work: open, modular, well documented, and well maintained. We review four state of-the-art, 3-D visualization packages assessing their capabilities and feasibility for use in the case of 3-D astronomical data.

Visual explorer facilitator's guide

CERN Document Server

Palus, Charles J

2010-01-01

Grounded in research and practice, the Visual Explorer™ Facilitator's Guide provides a method for supporting collaborative, creative conversations about complex issues through the power of images. The guide is available as a component in the Visual Explorer Facilitator's Letter-sized Set, Visual Explorer Facilitator's Post card-sized Set, Visual Explorer Playing Card-sized Set, and is also available as a stand-alone title for purchase to assist multiple tool users in an organization.

A Comprehensive Optimization Strategy for Real-time Spatial Feature Sharing and Visual Analytics in Cyberinfrastructure

Science.gov (United States)

Li, W.; Shao, H.

2017-12-01

For geospatial cyberinfrastructure enabled web services, the ability of rapidly transmitting and sharing spatial data over the Internet plays a critical role to meet the demands of real-time change detection, response and decision-making. Especially for the vector datasets which serve as irreplaceable and concrete material in data-driven geospatial applications, their rich geometry and property information facilitates the development of interactive, efficient and intelligent data analysis and visualization applications. However, the big-data issues of vector datasets have hindered their wide adoption in web services. In this research, we propose a comprehensive optimization strategy to enhance the performance of vector data transmitting and processing. This strategy combines: 1) pre- and on-the-fly generalization, which automatically determines proper simplification level through the introduction of appropriate distance tolerance (ADT) to meet various visualization requirements, and at the same time speed up simplification efficiency; 2) a progressive attribute transmission method to reduce data size and therefore the service response time; 3) compressed data transmission and dynamic adoption of a compression method to maximize the service efficiency under different computing and network environments. A cyberinfrastructure web portal was developed for implementing the proposed technologies. After applying our optimization strategies, substantial performance enhancement is achieved. We expect this work to widen the use of web service providing vector data to support real-time spatial feature sharing, visual analytics and decision-making.

VAMPS: a website for visualization and analysis of microbial population structures.

Science.gov (United States)

Huse, Susan M; Mark Welch, David B; Voorhis, Andy; Shipunova, Anna; Morrison, Hilary G; Eren, A Murat; Sogin, Mitchell L

2014-02-05

The advent of next-generation DNA sequencing platforms has revolutionized molecular microbial ecology by making the detailed analysis of complex communities over time and space a tractable research pursuit for small research groups. However, the ability to generate 10⁵-10⁸ reads with relative ease brings with it many downstream complications. Beyond the computational resources and skills needed to process and analyze data, it is difficult to compare datasets in an intuitive and interactive manner that leads to hypothesis generation and testing. We developed the free web service VAMPS (Visualization and Analysis of Microbial Population Structures, http://vamps.mbl.edu) to address these challenges and to facilitate research by individuals or collaborating groups working on projects with large-scale sequencing data. Users can upload marker gene sequences and associated metadata; reads are quality filtered and assigned to both taxonomic structures and to taxonomy-independent clusters. A simple point-and-click interface allows users to select for analysis any combination of their own or their collaborators' private data and data from public projects, filter these by their choice of taxonomic and/or abundance criteria, and then explore these data using a wide range of analytic methods and visualizations. Each result is extensively hyperlinked to other analysis and visualization options, promoting data exploration and leading to a greater understanding of data relationships. VAMPS allows researchers using marker gene sequence data to analyze the diversity of microbial communities and the relationships between communities, to explore these analyses in an intuitive visual context, and to download data, results, and images for publication. VAMPS obviates the need for individual research groups to make the considerable investment in computational infrastructure and bioinformatic support otherwise necessary to process, analyze, and interpret massive amounts of next

Evaluation methodology for comparing memory and communication of analytic processes in visual analytics

Energy Technology Data Exchange (ETDEWEB)

Ragan, Eric D [ORNL; Goodall, John R [ORNL

2014-01-01

Provenance tools can help capture and represent the history of analytic processes. In addition to supporting analytic performance, provenance tools can be used to support memory of the process and communication of the steps to others. Objective evaluation methods are needed to evaluate how well provenance tools support analyst s memory and communication of analytic processes. In this paper, we present several methods for the evaluation of process memory, and we discuss the advantages and limitations of each. We discuss methods for determining a baseline process for comparison, and we describe various methods that can be used to elicit process recall, step ordering, and time estimations. Additionally, we discuss methods for conducting quantitative and qualitative analyses of process memory. By organizing possible memory evaluation methods and providing a meta-analysis of the potential benefits and drawbacks of different approaches, this paper can inform study design and encourage objective evaluation of process memory and communication.

Cognitive Foundations for Visual Analytics

Energy Technology Data Exchange (ETDEWEB)

Greitzer, Frank L.; Noonan, Christine F.; Franklin, Lyndsey

2011-02-25

In this report, we provide an overview of scientific/technical literature on information visualization and VA. Topics discussed include an update and overview of the extensive literature search conducted for this study, the nature and purpose of the field, major research thrusts, and scientific foundations. We review methodologies for evaluating and measuring the impact of VA technologies as well as taxonomies that have been proposed for various purposes to support the VA community. A cognitive science perspective underlies each of these discussions.

Utility assessment of a map-based online geo-collaboration tool.

Science.gov (United States)

Sidlar, Christopher L; Rinner, Claus

2009-05-01

Spatial group decision-making processes often include both informal and analytical components. Discussions among stakeholders or planning experts are an example of an informal component. When participants discuss spatial planning projects they typically express concerns and comments by pointing to places on a map. The Argumentation Map model provides a conceptual basis for collaborative tools that enable explicit linkages of arguments to the places to which they refer. These tools allow for the input of explicitly geo-referenced arguments as well as the visual access to arguments through a map interface. In this paper, we will review previous utility studies in geo-collaboration and evaluate a case study of a Web-based Argumentation Map application. The case study was conducted in the summer of 2005 when student participants discussed planning issues on the University of Toronto St. George campus. During a one-week unmoderated discussion phase, 11 participants wrote 60 comments on issues such as safety, facilities, parking, and building aesthetics. By measuring the participants' use of geographic references, we draw conclusions on how well the software tool supported the potential of the underlying concept. This research aims to contribute to a scientific approach to geo-collaboration in which the engineering of novel spatial decision support methods is complemented by a critical assessment of their utility in controlled, realistic experiments.

ESIP Earth Sciences Data Analytics (ESDA) Cluster - Work in Progress

Science.gov (United States)

Kempler, Steven

2015-01-01

The purpose of this poster is to promote a common understanding of the usefulness of, and activities that pertain to, Data Analytics and more broadly, the Data Scientist; Facilitate collaborations to better understand the cross usage of heterogeneous datasets and to provide accommodating data analytics expertise, now and as the needs evolve into the future; Identify gaps that, once filled, will further collaborative activities. Objectives Provide a forum for Academic discussions that provides ESIP members a better understanding of the various aspects of Earth Science Data Analytics Bring in guest speakers to describe external efforts, and further teach us about the broader use of Data Analytics. Perform activities that:- Compile use cases generated from specific community needs to cross analyze heterogeneous data- Compile sources of analytics tools, in particular, to satisfy the needs of the above data users- Examine gaps between needs and sources- Examine gaps between needs and community expertise- Document specific data analytics expertise needed to perform Earth science data analytics Seek graduate data analytics Data Science student internship opportunities.

Social Set Visualizer

DEFF Research Database (Denmark)

Flesch, Benjamin; Vatrapu, Ravi; Mukkamala, Raghava Rao

2015-01-01

approach to computational social science mentioned above. The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard......Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data...

Enhancing collaborative innovation in the public sector

DEFF Research Database (Denmark)

Sørensen, Eva; Torfing, Jacob

2011-01-01

demand for public innovation, and demonstrates how it can be enhanced through multiactor collaboration. The case for collaborative innovation is supported by insights from three different social science theories. The theoretical discussion leads to the formulation of an analytical model that can be used......Encouraged by the proliferation of governance networks and the growing demands for public innovation, this article aims to advance “collaborative innovation” as a cross-disciplinary approach to studying and enhancing public innovation. The article explains the special conditions and the growing...... in future studies of collaborative innovation in the public sector....

Data Representations, Transformations, and Statistics for Visual Reasoning

CERN Document Server

Maciejewski, Ross

2011-01-01

Analytical reasoning techniques are methods by which users explore their data to obtain insight and knowledge that can directly support situational awareness and decision making. Recently, the analytical reasoning process has been augmented through the use of interactive visual representations and tools which utilize cognitive, design and perceptual principles. These tools are commonly referred to as visual analytics tools, and the underlying methods and principles have roots in a variety of disciplines. This chapter provides an introduction to young researchers as an overview of common visual

CasCADe: A Novel 4D Visualization System for Virtual Construction Planning.

Science.gov (United States)

Ivson, Paulo; Nascimento, Daniel; Celes, Waldemar; Barbosa, Simone Dj

2018-01-01

Building Information Modeling (BIM) provides an integrated 3D environment to manage large-scale engineering projects. The Architecture, Engineering and Construction (AEC) industry explores 4D visualizations over these datasets for virtual construction planning. However, existing solutions lack adequate visual mechanisms to inspect the underlying schedule and make inconsistencies readily apparent. The goal of this paper is to apply best practices of information visualization to improve 4D analysis of construction plans. We first present a review of previous work that identifies common use cases and limitations. We then consulted with AEC professionals to specify the main design requirements for such applications. These guided the development of CasCADe, a novel 4D visualization system where task sequencing and spatio-temporal simultaneity are immediately apparent. This unique framework enables the combination of diverse analytical features to create an information-rich analysis environment. We also describe how engineering collaborators used CasCADe to review the real-world construction plans of an Oil & Gas process plant. The system made evident schedule uncertainties, identified work-space conflicts and helped analyze other constructability issues. The results and contributions of this paper suggest new avenues for future research in information visualization for the AEC industry.

Combining Synchronous and Asynchronous Collaboration within 3D City Models

Science.gov (United States)

Klimke, Jan; Döllner, Jürgen

This paper presents an approach for combining spatially distributed synchronous and asynchronous collaboration within 3D city models. Software applications use these models as additional communication medium to facilitate communication of georeferenced and geospatial information. Collaboration tools should support both the communication with other collaborators and their awareness of the current collaboration context. To support collaborative knowledge construction and gathering, we have designed a collaboration system to facilitate (a) creation of annotations that have 3D references to the virtual 3D city model and (b) collection information about the context in which these annotations are created. Our approach supports synchronous collaboration in connection with the creation of non volatile, precisely georeferenced units of information allow for a comprehensible form of cooperation in spatially distributed settings. Storage and retrieval of this information is provided through a Web Feature Service, which eases integration of collaboration data into existing applications. We further introduce a visualization technique that integrates annotations as complex structured data into the 3D visualization. This avoids media breaks and disruptions in working processes and creates a spatial coherence between annotation and annotated feature or geometry.

LitPathExplorer: a confidence-based visual text analytics tool for exploring literature-enriched pathway models.

Science.gov (United States)

Soto, Axel J; Zerva, Chrysoula; Batista-Navarro, Riza; Ananiadou, Sophia

2018-04-15

Pathway models are valuable resources that help us understand the various mechanisms underpinning complex biological processes. Their curation is typically carried out through manual inspection of published scientific literature to find information relevant to a model, which is a laborious and knowledge-intensive task. Furthermore, models curated manually cannot be easily updated and maintained with new evidence extracted from the literature without automated support. We have developed LitPathExplorer, a visual text analytics tool that integrates advanced text mining, semi-supervised learning and interactive visualization, to facilitate the exploration and analysis of pathway models using statements (i.e. events) extracted automatically from the literature and organized according to levels of confidence. LitPathExplorer supports pathway modellers and curators alike by: (i) extracting events from the literature that corroborate existing models with evidence; (ii) discovering new events which can update models; and (iii) providing a confidence value for each event that is automatically computed based on linguistic features and article metadata. Our evaluation of event extraction showed a precision of 89% and a recall of 71%. Evaluation of our confidence measure, when used for ranking sampled events, showed an average precision ranging between 61 and 73%, which can be improved to 95% when the user is involved in the semi-supervised learning process. Qualitative evaluation using pair analytics based on the feedback of three domain experts confirmed the utility of our tool within the context of pathway model exploration. LitPathExplorer is available at http://nactem.ac.uk/LitPathExplorer_BI/. sophia.ananiadou@manchester.ac.uk. Supplementary data are available at Bioinformatics online.

Data visualization a guide to visual storytelling for libraries

CERN Document Server

2016-01-01

Data Visualization: A Guide to Visual Storytelling for Libraries is a practical guide to the skills and tools needed to create beautiful and meaningful visual stories through data visualization. Learn how to sift through complex datasets to better understand a variety of metrics, such as trends in user behavior and electronic resource usage, return on investment (ROI) and impact metrics, and learning and reference analytics. Sections include: .Identifying and interpreting datasets for visualization .Tools and technologies for creating meaningful visualizations .Case studies in data visualization and dashboards Understanding and communicating trends from your organization s data is essential. Whether you are looking to make more informed decisions by visualizing organizational data, or to tell the story of your library s impact on your community, this book will give you the tools to make it happen."

Communication and Energy Efficiency in Visual Sensor Networks for People Localization

Energy Technology Data Exchange (ETDEWEB)

Karakaya, Mahmut [ORNL; Qi, Hairong [ORNL

2012-01-01

This paper addresses the communication and energy efficiency in collaborative visual sensor networks (VSNs) for people localization, a challenging computer vision problem of its own. We focus on the design of a light-weight and energy efficient solution where people are localized based on distributed camera nodes integrating the so-called certainty map generated at each node, that records the target non-existence information within the camera s field of view. We first present a dynamic itinerary for certainty map integration where not only each sensor node transmits a very limited amount of data but that a limited number of camera nodes is involved. Then, we perform a comprehensive analytical study to evaluate communication and energy efficiency between different integration schemes, i.e., centralized and distributed integration. Based on results obtained from analytical study and real experiments, the distributed method shows effectiveness in detection accuracy as well as energy and bandwidth efficiency.

Visioning future emergency healthcare collaboration

DEFF Research Database (Denmark)

Söderholm, Hanna M.; Sonnenwald, Diane H.

2010-01-01

physicians, nurses, administrators, and information technology (IT) professionals working at large and small medical centers, and asked them to share their perspectives regarding 3DMC's potential benefits and disadvantages in emergency healthcare and its compatibility and/or lack thereof......New video technologies are emerging to facilitate collaboration in emergency healthcare. One such technology is 3D telepresence technology for medical consultation (3DMC) that may provide richer visual information to support collaboration between medical professionals to, ideally, enhance patient......, and resources. Both common and unique perceptions regarding 3DMC emerged,illustrating the need for 3DMC, and other collaboration technologies,to support interwoven situational awareness across different technological frames....

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

Science.gov (United States)

Wenhui, Ma; Yu, Wang

2017-06-01

Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

Exploring the Design Space of Immersive Urban Analytics

OpenAIRE

Chen, Zhutian; Wang, Yifang; Sun, Tianchen; Gao, Xiang; Chen, Wei; Pan, Zhigeng; Qu, Huamin; Wu, Yingcai

2017-01-01

Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft HoloLens. These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence. In this paper, we propose an theoretical model to characterize the visualizations in immersive urban analytics. Further more, based on our comprehensiv...

Surface computing and collaborative analysis work

CERN Document Server

Brown, Judith; Gossage, Stevenson; Hack, Chris

2013-01-01

Large surface computing devices (wall-mounted or tabletop) with touch interfaces and their application to collaborative data analysis, an increasingly important and prevalent activity, is the primary topic of this book. Our goals are to outline the fundamentals of surface computing (a still maturing technology), review relevant work on collaborative data analysis, describe frameworks for understanding collaborative processes, and provide a better understanding of the opportunities for research and development. We describe surfaces as display technologies with which people can interact directly, and emphasize how interaction design changes when designing for large surfaces. We review efforts to use large displays, surfaces or mixed display environments to enable collaborative analytic activity. Collaborative analysis is important in many domains, but to provide concrete examples and a specific focus, we frequently consider analysis work in the security domain, and in particular the challenges security personne...

Visualization rhetoric: framing effects in narrative visualization.

Science.gov (United States)

Hullman, Jessica; Diakopoulos, Nicholas

2011-12-01

Narrative visualizations combine conventions of communicative and exploratory information visualization to convey an intended story. We demonstrate visualization rhetoric as an analytical framework for understanding how design techniques that prioritize particular interpretations in visualizations that "tell a story" can significantly affect end-user interpretation. We draw a parallel between narrative visualization interpretation and evidence from framing studies in political messaging, decision-making, and literary studies. Devices for understanding the rhetorical nature of narrative information visualizations are presented, informed by the rigorous application of concepts from critical theory, semiotics, journalism, and political theory. We draw attention to how design tactics represent additions or omissions of information at various levels-the data, visual representation, textual annotations, and interactivity-and how visualizations denote and connote phenomena with reference to unstated viewing conventions and codes. Classes of rhetorical techniques identified via a systematic analysis of recent narrative visualizations are presented, and characterized according to their rhetorical contribution to the visualization. We describe how designers and researchers can benefit from the potentially positive aspects of visualization rhetoric in designing engaging, layered narrative visualizations and how our framework can shed light on how a visualization design prioritizes specific interpretations. We identify areas where future inquiry into visualization rhetoric can improve understanding of visualization interpretation. © 2011 IEEE

HEP visualization and video technology

International Nuclear Information System (INIS)

Lebrun, P.; Swoboda, D.

1994-01-01

The use of scientific visualization for HEP analysis is briefly reviewed. The applications are highly interactive and very dynamical in nature. At Fermilab, E687, in collaboration with Visual Media Services, has produced a 1/2 hour video tape demonstrating the capability of SGI-EXPLORER applied to a Dalitz Analysis of Charm decay. This short contribution describes the authors experience with visualization and video technologies

VAST Challenge 2016: Streaming Visual Analytics

Science.gov (United States)

2016-10-25

life (Fig. 6), earning them an honorable mention for Quality Aesthetics. Finally, TCS Research used iconic representation to help analysts understand...ventilation (bottom). Figure 7: Iconic representation of patterns inferred by TCS Research (#130). Top: an increase in number of employees in a...include both perceptual and cognitive considerations (i.e., visual channel capabilities, short-term memory capacity, etc.). An example of one such

Advanced engineering environment collaboration project.

Energy Technology Data Exchange (ETDEWEB)

Lamph, Jane Ann; Pomplun, Alan R.; Kiba, Grant W.; Dutra, Edward G.; Dankiewicz, Robert J.; Marburger, Scot J.

2008-12-01

The Advanced Engineering Environment (AEE) is a model for an engineering design and communications system that will enhance project collaboration throughout the nuclear weapons complex (NWC). Sandia National Laboratories and Parametric Technology Corporation (PTC) worked together on a prototype project to evaluate the suitability of a portion of PTC's Windchill 9.0 suite of data management, design and collaboration tools as the basis for an AEE. The AEE project team implemented Windchill 9.0 development servers in both classified and unclassified domains and used them to test and evaluate the Windchill tool suite relative to the needs of the NWC using weapons project use cases. A primary deliverable was the development of a new real time collaborative desktop design and engineering process using PDMLink (data management tool), Pro/Engineer (mechanical computer aided design tool) and ProductView Lite (visualization tool). Additional project activities included evaluations of PTC's electrical computer aided design, visualization, and engineering calculations applications. This report documents the AEE project work to share information and lessons learned with other NWC sites. It also provides PTC with recommendations for improving their products for NWC applications.

Advanced engineering environment collaboration project

International Nuclear Information System (INIS)

Lamph, Jane Ann; Pomplun, Alan R.; Kiba, Grant W.; Dutra, Edward G.; Dankiewicz, Robert J.; Marburger, Scot J.

2008-01-01

The Advanced Engineering Environment (AEE) is a model for an engineering design and communications system that will enhance project collaboration throughout the nuclear weapons complex (NWC). Sandia National Laboratories and Parametric Technology Corporation (PTC) worked together on a prototype project to evaluate the suitability of a portion of PTC's Windchill 9.0 suite of data management, design and collaboration tools as the basis for an AEE. The AEE project team implemented Windchill 9.0 development servers in both classified and unclassified domains and used them to test and evaluate the Windchill tool suite relative to the needs of the NWC using weapons project use cases. A primary deliverable was the development of a new real time collaborative desktop design and engineering process using PDMLink (data management tool), Pro/Engineer (mechanical computer aided design tool) and ProductView Lite (visualization tool). Additional project activities included evaluations of PTC's electrical computer aided design, visualization, and engineering calculations applications. This report documents the AEE project work to share information and lessons learned with other NWC sites. It also provides PTC with recommendations for improving their products for NWC applications

Understanding ill-structured engineering ethics problems through a collaborative learning and argument visualization approach.

Science.gov (United States)

Hoffmann, Michael; Borenstein, Jason

2014-03-01

As a committee of the National Academy of Engineering recognized, ethics education should foster the ability of students to analyze complex decision situations and ill-structured problems. Building on the NAE's insights, we report about an innovative teaching approach that has two main features: first, it places the emphasis on deliberation and on self-directed, problem-based learning in small groups of students; and second, it focuses on understanding ill-structured problems. The first innovation is motivated by an abundance of scholarly research that supports the value of deliberative learning practices. The second results from a critique of the traditional case-study approach in engineering ethics. A key problem with standard cases is that they are usually described in such a fashion that renders the ethical problem as being too obvious and simplistic. The practitioner, by contrast, may face problems that are ill-structured. In the collaborative learning environment described here, groups of students use interactive and web-based argument visualization software called "AGORA-net: Participate - Deliberate!". The function of the software is to structure communication and problem solving in small groups. Students are confronted with the task of identifying possible stakeholder positions and reconstructing their legitimacy by constructing justifications for these positions in the form of graphically represented argument maps. The argument maps are then presented in class so that these stakeholder positions and their respective justifications become visible and can be brought into a reasoned dialogue. Argument mapping provides an opportunity for students to collaborate in teams and to develop critical thinking and argumentation skills.

The Analysis of Task and Data Characteristic and the Collaborative Processing Method in Real-Time Visualization Pipeline of Urban 3DGIS

Directory of Open Access Journals (Sweden)

Dongbo Zhou

2017-03-01

Full Text Available Parallel processing in the real-time visualization of three-dimensional Geographic Information Systems (3DGIS has tended to concentrate on algorithm levels in recent years, and most of the existing methods employ multiple threads in a Central Processing Unit (CPU or kernel in a Graphics Processing Unit (GPU to improve efficiency in the computation of the Level of Details (LODs for three-dimensional (3D Models and in the display of Digital Elevation Models (DEMs and Digital Orthphoto Maps (DOMs. The systematic analysis of the task and data characteristics of parallelism in the real-time visualization of 3DGIS continues to fall behind the development of hardware. In this paper, the basic procedures of real-time visualization of urban 3DGIS are first reviewed, and then the real-time visualization pipeline is analyzed. Further, the pipeline is decomposed into different task stages based on the task order and the input-output dependency. Based on the analysis of task parallelism in different pipeline stages, the data parallelism characteristics in each task are summarized by studying the involved algorithms. Finally, this paper proposes a parallel co-processing mode and a collaborative strategy for real-time visualization of urban 3DGIS. It also provides a fundamental basis for developing parallel algorithms and strategies in 3DGIS.

1st Workshop on Eye Tracking and Visualization

CERN Document Server

Chuang, Lewis; Fisher, Brian; Schmidt, Albrecht; Weiskopf, Daniel

2017-01-01

This book discusses research, methods, and recent developments in the interdisciplinary field that spans research in visualization, eye tracking, human-computer interaction, and psychology. It presents extended versions of papers from the First Workshop on Eye Tracking and Visualization (ETVIS), which was organized as a workshop of the IEEE VIS Conference 2015. Topics include visualization and visual analytics of eye-tracking data, metrics and cognitive models, eye-tracking experiments in the context of visualization interfaces, and eye tracking in 3D and immersive environments. The extended ETVIS papers are complemented by a chapter offering an overview of visualization approaches for analyzing eye-tracking data and a chapter that discusses electrooculography (EOG) as an alternative of acquiring information about eye movements. Covering scientific visualization, information visualization, and visual analytics, this book is a valuable resource for eye-tracking researchers within the visualization community.

Exploring the design space of immersive urban analytics

Directory of Open Access Journals (Sweden)

Zhutian Chen

2017-06-01

Full Text Available Recent years have witnessed the rapid development and wide adoption of immersive head-mounted devices, such as HTC VIVE, Oculus Rift, and Microsoft HoloLens. These immersive devices have the potential to significantly extend the methodology of urban visual analytics by providing critical 3D context information and creating a sense of presence. In this paper, we propose a theoretical model to characterize the visualizations in immersive urban analytics. Furthermore, based on our comprehensive and concise model, we contribute a typology of combination methods of 2D and 3D visualizations that distinguishes between linked views, embedded views, and mixed views. We also propose a supporting guideline to assist users in selecting a proper view under certain circumstances by considering visual geometry and spatial distribution of the 2D and 3D visualizations. Finally, based on existing work, possible future research opportunities are explored and discussed.

Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

Directory of Open Access Journals (Sweden)

Wenhui Ma

2017-06-01

Full Text Available Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change

Directory of Open Access Journals (Sweden)

Karen M. Thorne

2015-03-01

Full Text Available Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1 Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2 What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a

Collaborative decision-analytic framework to maximize resilience of tidal marshes to climate change

Science.gov (United States)

Thorne, Karen M.; Mattsson, Brady J.; Takekawa, John Y.; Cummings, Jonathan; Crouse, Debby; Block, Giselle; Bloom, Valary; Gerhart, Matt; Goldbeck, Steve; Huning, Beth; Sloop, Christina; Stewart, Mendel; Taylor, Karen; Valoppi, Laura

2015-01-01

Decision makers that are responsible for stewardship of natural resources face many challenges, which are complicated by uncertainty about impacts from climate change, expanding human development, and intensifying land uses. A systematic process for evaluating the social and ecological risks, trade-offs, and cobenefits associated with future changes is critical to maximize resilience and conserve ecosystem services. This is particularly true in coastal areas where human populations and landscape conversion are increasing, and where intensifying storms and sea-level rise pose unprecedented threats to coastal ecosystems. We applied collaborative decision analysis with a diverse team of stakeholders who preserve, manage, or restore tidal marshes across the San Francisco Bay estuary, California, USA, as a case study. Specifically, we followed a structured decision-making approach, and we using expert judgment developed alternative management strategies to increase the capacity and adaptability to manage tidal marsh resilience while considering uncertainties through 2050. Because sea-level rise projections are relatively confident to 2050, we focused on uncertainties regarding intensity and frequency of storms and funding. Elicitation methods allowed us to make predictions in the absence of fully compatible models and to assess short- and long-term trade-offs. Specifically we addressed two questions. (1) Can collaborative decision analysis lead to consensus among a diverse set of decision makers responsible for environmental stewardship and faced with uncertainties about climate change, funding, and stakeholder values? (2) What is an optimal strategy for the conservation of tidal marshes, and what strategy is robust to the aforementioned uncertainties? We found that when taking this approach, consensus was reached among the stakeholders about the best management strategies to maintain tidal marsh integrity. A Bayesian decision network revealed that a strategy

Visual analytics of geo-social interaction patterns for epidemic control.

Science.gov (United States)

Luo, Wei

2016-08-10

Human interaction and population mobility determine the spatio-temporal course of the spread of an airborne disease. This research views such spreads as geo-social interaction problems, because population mobility connects different groups of people over geographical locations via which the viruses transmit. Previous research argued that geo-social interaction patterns identified from population movement data can provide great potential in designing effective pandemic mitigation. However, little work has been done to examine the effectiveness of designing control strategies taking into account geo-social interaction patterns. To address this gap, this research proposes a new framework for effective disease control; specifically this framework proposes that disease control strategies should start from identifying geo-social interaction patterns, designing effective control measures accordingly, and evaluating the efficacy of different control measures. This framework is used to structure design of a new visual analytic tool that consists of three components: a reorderable matrix for geo-social mixing patterns, agent-based epidemic models, and combined visualization methods. With real world human interaction data in a French primary school as a proof of concept, this research compares the efficacy of vaccination strategies between the spatial-social interaction patterns and the whole areas. The simulation results show that locally targeted vaccination has the potential to keep infection to a small number and prevent spread to other regions. At some small probability, the local control strategies will fail; in these cases other control strategies will be needed. This research further explores the impact of varying spatial-social scales on the success of local vaccination strategies. The results show that a proper spatial-social scale can help achieve the best control efficacy with a limited number of vaccines. The case study shows how GS-EpiViz does support the design

Analytic information processing style in epilepsy patients.

Science.gov (United States)

Buonfiglio, Marzia; Di Sabato, Francesco; Mandillo, Silvia; Albini, Mariarita; Di Bonaventura, Carlo; Giallonardo, Annateresa; Avanzini, Giuliano

2017-08-01

Relevant to the study of epileptogenesis is learning processing, given the pivotal role that neuroplasticity assumes in both mechanisms. Recently, evoked potential analyses showed a link between analytic cognitive style and altered neural excitability in both migraine and healthy subjects, regardless of cognitive impairment or psychological disorders. In this study we evaluated analytic/global and visual/auditory perceptual dimensions of cognitive style in patients with epilepsy. Twenty-five cryptogenic temporal lobe epilepsy (TLE) patients matched with 25 idiopathic generalized epilepsy (IGE) sufferers and 25 healthy volunteers were recruited and participated in three cognitive style tests: "Sternberg-Wagner Self-Assessment Inventory", the C. Cornoldi test series called AMOS, and the Mariani Learning style Questionnaire. Our results demonstrate a significant association between analytic cognitive style and both IGE and TLE and respectively a predominant auditory and visual analytic style (ANOVA: p values <0,0001). These findings should encourage further research to investigate information processing style and its neurophysiological correlates in epilepsy. Copyright © 2017 Elsevier Inc. All rights reserved.

Assisting Instructional Assessment of Undergraduate Collaborative Wiki and SVN Activities

Science.gov (United States)

Kim, Jihie; Shaw, Erin; Xu, Hao; Adarsh, G. V.

2012-01-01

In this paper we examine the collaborative performance of undergraduate engineering students who used shared project documents (Wikis, Google documents) and a software version control system (SVN) to support project collaboration. We present an initial implementation of TeamAnalytics, an instructional tool that facilitates the analyses of the…

GeoChronos: An On-line Collaborative Platform for Earth Observation Scientists

Science.gov (United States)

Gamon, J. A.; Kiddle, C.; Curry, R.; Markatchev, N.; Zonta-Pastorello, G., Jr.; Rivard, B.; Sanchez-Azofeifa, G. A.; Simmonds, R.; Tan, T.

2009-12-01

included the IAI International Wireless Sensor Networking Summer School at the University of Alberta, and the IAI Tropi-Dry community. Current GeoChronos activities include the development of a web-based spectral library and related analytical and visualization tools, in collaboration with members of the SpecNet community. The GeoChronos portal will be open to all members of the earth observation science community when the project nears completion at the end of 2010.

Semantic Interaction for Sensemaking: Inferring Analytical Reasoning for Model Steering.

Science.gov (United States)

Endert, A; Fiaux, P; North, C

2012-12-01

Visual analytic tools aim to support the cognitively demanding task of sensemaking. Their success often depends on the ability to leverage capabilities of mathematical models, visualization, and human intuition through flexible, usable, and expressive interactions. Spatially clustering data is one effective metaphor for users to explore similarity and relationships between information, adjusting the weighting of dimensions or characteristics of the dataset to observe the change in the spatial layout. Semantic interaction is an approach to user interaction in such spatializations that couples these parametric modifications of the clustering model with users' analytic operations on the data (e.g., direct document movement in the spatialization, highlighting text, search, etc.). In this paper, we present results of a user study exploring the ability of semantic interaction in a visual analytic prototype, ForceSPIRE, to support sensemaking. We found that semantic interaction captures the analytical reasoning of the user through keyword weighting, and aids the user in co-creating a spatialization based on the user's reasoning and intuition.

VAP/VAT: video analytics platform and test bed for testing and deploying video analytics

Science.gov (United States)

Gorodnichy, Dmitry O.; Dubrofsky, Elan

2010-04-01

Deploying Video Analytics in operational environments is extremely challenging. This paper presents a methodological approach developed by the Video Surveillance and Biometrics Section (VSB) of the Science and Engineering Directorate (S&E) of the Canada Border Services Agency (CBSA) to resolve these problems. A three-phase approach to enable VA deployment within an operational agency is presented and the Video Analytics Platform and Testbed (VAP/VAT) developed by the VSB section is introduced. In addition to allowing the integration of third party and in-house built VA codes into an existing video surveillance infrastructure, VAP/VAT also allows the agency to conduct an unbiased performance evaluation of the cameras and VA software available on the market. VAP/VAT consists of two components: EventCapture, which serves to Automatically detect a "Visual Event", and EventBrowser, which serves to Display & Peruse of "Visual Details" captured at the "Visual Event". To deal with Open architecture as well as with Closed architecture cameras, two video-feed capture mechanisms have been developed within the EventCapture component: IPCamCapture and ScreenCapture.

Towards different communication in collaborative design

NARCIS (Netherlands)

Smulders, F.E.H.M.; Lousberg, L.; Dorst, C.H.

2008-01-01

Purpose – This paper aims to create a social constructivist perspective on collaborative architecture that is complementary to the rational-analytic perspective as embodied in the "hard" project management tools. Design/methodology/approach – Two theoretical perspectives from the field of design

Social Set Visualizer (SoSeVi) II

DEFF Research Database (Denmark)

Flesch, Benjamin; Vatrapu, Ravi; Mukkamala, Raghava Rao

2016-01-01

SeVi). The development of the dashboard involved cutting-edge open source visual analytics libraries (D3.js) and creation of new visualizations such as visualizations of actor mobility across time and space, conversational comets, and more. Evaluation of the dashboard consisted of technical testing, usability testing......Current state-of-the-art in big social data analytics is largely limited to graph theoretical approaches such as social network analysis (SNA) informed by the social philosophical approach of relational sociology. This paper proposes and illustrates an alternate holistic approach to big social data...

Visual Analytics for the Food-Water-Energy Nexus in the Phoenix Active Management Area

Science.gov (United States)

Maciejewski, R.; Mascaro, G.; White, D. D.; Ruddell, B. L.; Aggarwal, R.; Sarjoughian, H.

2016-12-01

The Phoenix Active Management Area (AMA) is an administrative region of 14,500 km2 identified by the Arizona Department of Water Resources with the aim of reaching and maintaining the safe yield (i.e. balance between annual amount of groundwater withdrawn and recharged) by 2025. The AMA includes the Phoenix metropolitan area, which has experienced a dramatic population growth over the last decades with a progressive conversion of agricultural land into residential land. As a result of these changes, the water and energy demand as well as the food production in the region have significantly evolved over the last 30 years. Given the arid climate, a crucial role to support this growth has been the creation of a complex water supply system based on renewable and non-renewable resources, including the energy-intensive Central Arizona Project. In this talk, we present a preliminary characterization of the evolution in time of the feedbacks between food, water, and energy in the Phoenix AMA by analyzing secondary data (available from water and energy providers, irrigation districts, and municipalities), as well as satellite imagery and primary data collected by the authors. A preliminary visual analytics framework is also discussed describing current design practices and ideas for exploring networked components and cascading impacts within the FEW Nexus. This analysis and framework represent the first steps towards the development of an integrated modeling, visualization, and decision support infrastructure for comprehensive FEW systems decision making at decision-relevant temporal and spatial scales.

Visual Analytics for the Exploration of Tumor Tissue Characterization

DEFF Research Database (Denmark)

Raidou, R. G.; Van Der Heide, U. A.; Dinh, C. V.

2015-01-01

imaging data, to derive per voxel a number of features, indicative of tissue properties. However, the high dimensionality and complexity of this imaging-derived feature space is prohibiting for easy exploration and analysis - especially when clinical researchers require to associate observations from...... the feature space to other reference data, e.g., features derived from histopathological data. Currently, the exploratory approach used in clinical research consists of juxtaposing these data, visually comparing them and mentally reconstructing their relationships. This is a time consuming and tedious process......, from which it is difficult to obtain the required insight. We propose a visual tool for: (1) easy exploration and visual analysis of the feature space of imaging-derived tissue characteristics and (2) knowledge discovery and hypothesis generation and confirmation, with respect to reference data used...

Insight solutions are correct more often than analytic solutions

Science.gov (United States)

Salvi, Carola; Bricolo, Emanuela; Kounios, John; Bowden, Edward; Beeman, Mark

2016-01-01

How accurate are insights compared to analytical solutions? In four experiments, we investigated how participants’ solving strategies influenced their solution accuracies across different types of problems, including one that was linguistic, one that was visual and two that were mixed visual-linguistic. In each experiment, participants’ self-judged insight solutions were, on average, more accurate than their analytic ones. We hypothesised that insight solutions have superior accuracy because they emerge into consciousness in an all-or-nothing fashion when the unconscious solving process is complete, whereas analytic solutions can be guesses based on conscious, prematurely terminated, processing. This hypothesis is supported by the finding that participants’ analytic solutions included relatively more incorrect responses (i.e., errors of commission) than timeouts (i.e., errors of omission) compared to their insight responses. PMID:27667960

The World Spatiotemporal Analytics and Mapping Project (WSTAMP): Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World's Largest Open Source Data Sets

Science.gov (United States)

Piburn, J.; Stewart, R.; Myers, A.; Sorokine, A.; Axley, E.; Anderson, D.; Burdette, J.; Biddle, C.; Hohl, A.; Eberle, R.; Kaufman, J.; Morton, A.

2017-10-01

Spatiotemporal (ST) analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

Croatian Analytical Terminology

Directory of Open Access Journals (Sweden)

Kastelan-Macan; M.

2008-04-01

Full Text Available Results of analytical research are necessary in all human activities. They are inevitable in making decisions in the environmental chemistry, agriculture, forestry, veterinary medicine, pharmaceutical industry, and biochemistry. Without analytical measurements the quality of materials and products cannot be assessed, so that analytical chemistry is an essential part of technical sciences and disciplines.The language of Croatian science, and analytical chemistry within it, was one of the goals of our predecessors. Due to the political situation, they did not succeed entirely, but for the scientists in independent Croatia this is a duty, because language is one of the most important features of the Croatian identity. The awareness of the need to introduce Croatian terminology was systematically developed in the second half of the 19th century, along with the founding of scientific societies and the wish of scientists to write their scientific works in Croatian, so that the results of their research may be applied in economy. Many authors of textbooks from the 19th and the first half of the 20th century contributed to Croatian analytical terminology (F. Rački, B. Šulek, P. Žulić, G. Pexidr, J. Domac, G. Janeček , F. Bubanović, V. Njegovan and others. M. DeŢelić published the first systematic chemical terminology in 1940, adjusted to the IUPAC recommendations. In the second half of 20th century textbooks in classic analytical chemistry were written by V. Marjanović-Krajovan, M. Gyiketta-Ogrizek, S. Žilić and others. I. Filipović wrote the General and Inorganic Chemistry textbook and the Laboratory Handbook (in collaboration with P. Sabioncello and contributed greatly to establishing the terminology in instrumental analytical methods.The source of Croatian nomenclature in modern analytical chemistry today are translated textbooks by Skoog, West and Holler, as well as by Günnzler i Gremlich, and original textbooks by S. Turina, Z. �

Not Just a Game … When We Play Together, We Learn Together: Interactive Virtual Environments and Gaming Engines for Geospatial Visualization

Science.gov (United States)

Shipman, J. S.; Anderson, J. W.

2017-12-01

An ideal tool for ecologists and land managers to investigate the impacts of both projected environmental changes and policy alternatives is the creation of immersive, interactive, virtual landscapes. As a new frontier in visualizing and understanding geospatial data, virtual landscapes require a new toolbox for data visualization that includes traditional GIS tools and uncommon tools such as the Unity3d game engine. Game engines provide capabilities to not only explore data but to build and interact with dynamic models collaboratively. These virtual worlds can be used to display and illustrate data that is often more understandable and plausible to both stakeholders and policy makers than is achieved using traditional maps.Within this context we will present funded research that has been developed utilizing virtual landscapes for geographic visualization and decision support among varied stakeholders. We will highlight the challenges and lessons learned when developing interactive virtual environments that require large multidisciplinary team efforts with varied competences. The results will emphasize the importance of visualization and interactive virtual environments and the link with emerging research disciplines within Visual Analytics.

VISUAL3D - An EIT network on visualization of geomodels

Science.gov (United States)

Bauer, Tobias

2017-04-01

When it comes to interpretation of data and understanding of deep geological structures and bodies at different scales then modelling tools and modelling experience is vital for deep exploration. Geomodelling provides a platform for integration of different types of data, including new kinds of information (e.g., new improved measuring methods). EIT Raw Materials, initiated by the EIT (European Institute of Innovation and Technology) and funded by the European Commission, is the largest and strongest consortium in the raw materials sector worldwide. The VISUAL3D network of infrastructure is an initiative by EIT Raw Materials and aims at bringing together partners with 3D-4D-visualisation infrastructure and 3D-4D-modelling experience. The recently formed network collaboration interlinks hardware, software and expert knowledge in modelling visualization and output. A special focus will be the linking of research, education and industry and integrating multi-disciplinary data and to visualize the data in three and four dimensions. By aiding network collaborations we aim at improving the combination of geomodels with differing file formats and data characteristics. This will create an increased competency in modelling visualization and the ability to interchange and communicate models more easily. By combining knowledge and experience in geomodelling with expertise in Virtual Reality visualization partners of EIT Raw Materials but also external parties will have the possibility to visualize, analyze and validate their geomodels in immersive VR-environments. The current network combines partners from universities, research institutes, geological surveys and industry with a strong background in geological 3D-modelling and 3D visualization and comprises: Luleå University of Technology, Geological Survey of Finland, Geological Survey of Denmark and Greenland, TUBA Freiberg, Uppsala University, Geological Survey of France, RWTH Aachen, DMT, KGHM Cuprum, Boliden, Montan

Analytical Review of Data Visualization Methods in Application to Big Data

OpenAIRE

Gorodov, Evgeniy Yur’evich; Gubarev, Vasiliy Vasil’evich

2013-01-01

This paper describes the term Big Data in aspects of data representation and visualization. There are some specific problems in Big Data visualization, so there are definitions for these problems and a set of approaches to avoid them. Also, we make a review of existing methods for data visualization in application to Big Data and taking into account the described problems. Summarizing the result, we have provided a classification of visualization methods in application to Big Data.

Information-Pooling Bias in Collaborative Security Incident Correlation Analysis.

Science.gov (United States)

Rajivan, Prashanth; Cooke, Nancy J

2018-03-01

Incident correlation is a vital step in the cybersecurity threat detection process. This article presents research on the effect of group-level information-pooling bias on collaborative incident correlation analysis in a synthetic task environment. Past research has shown that uneven information distribution biases people to share information that is known to most team members and prevents them from sharing any unique information available with them. The effect of such biases on security team collaborations are largely unknown. Thirty 3-person teams performed two threat detection missions involving information sharing and correlating security incidents. Incidents were predistributed to each person in the team based on the hidden profile paradigm. Participant teams, randomly assigned to three experimental groups, used different collaboration aids during Mission 2. Communication analysis revealed that participant teams were 3 times more likely to discuss security incidents commonly known to the majority. Unaided team collaboration was inefficient in finding associations between security incidents uniquely available to each member of the team. Visualizations that augment perceptual processing and recognition memory were found to mitigate the bias. The data suggest that (a) security analyst teams, when conducting collaborative correlation analysis, could be inefficient in pooling unique information from their peers; (b) employing off-the-shelf collaboration tools in cybersecurity defense environments is inadequate; and (c) collaborative security visualization tools developed considering the human cognitive limitations of security analysts is necessary. Potential applications of this research include development of team training procedures and collaboration tool development for security analysts.

Cognitive computing and big data analytics

CERN Document Server

Hurwitz, Judith; Bowles, Adrian

2015-01-01

MASTER THE ABILITY TO APPLY BIG DATA ANALYTICS TO MASSIVE AMOUNTS OF STRUCTURED AND UNSTRUCTURED DATA Cognitive computing is a technique that allows humans and computers to collaborate in order to gain insights and knowledge from data by uncovering patterns and anomalies. This comprehensive guide explains the underlying technologies, such as artificial intelligence, machine learning, natural language processing, and big data analytics. It then demonstrates how you can use these technologies to transform your organization. You will explore how different vendors and different industries are a

The HydroShare Collaborative Repository for the Hydrology Community

Science.gov (United States)

Tarboton, D. G.; Idaszak, R.; Horsburgh, J. S.; Ames, D. P.; Goodall, J. L.; Couch, A.; Hooper, R. P.; Dash, P. K.; Stealey, M.; Yi, H.; Bandaragoda, C.; Castronova, A. M.

2017-12-01

HydroShare is an online, collaboration system for sharing of hydrologic data, analytical tools, and models. It supports the sharing of, and collaboration around, "resources" which are defined by standardized content types for data formats and models commonly used in hydrology. With HydroShare you can: Share your data and models with colleagues; Manage who has access to the content that you share; Share, access, visualize and manipulate a broad set of hydrologic data types and models; Use the web services application programming interface (API) to program automated and client access; Publish data and models and obtain a citable digital object identifier (DOI); Aggregate your resources into collections; Discover and access data and models published by others; Use web apps to visualize, analyze and run models on data in HydroShare. This presentation will describe the functionality and architecture of HydroShare highlighting our approach to making this system easy to use and serving the needs of the hydrology community represented by the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc. (CUAHSI). Metadata for uploaded files is harvested automatically or captured using easy to use web user interfaces. Users are encouraged to add or create resources in HydroShare early in the data life cycle. To encourage this we allow users to share and collaborate on HydroShare resources privately among individual users or groups, entering metadata while doing the work. HydroShare also provides enhanced functionality for users through web apps that provide tools and computational capability for actions on resources. HydroShare's architecture broadly is comprised of: (1) resource storage, (2) resource exploration website, and (3) web apps for actions on resources. System components are loosely coupled and interact through APIs, which enhances robustness, as components can be upgraded and advanced relatively independently. The full power of this paradigm is the

The World Spatiotemporal Analytics and Mapping Project (WSTAMP: Further Progress in Discovering, Exploring, and Mapping Spatiotemporal Patterns Across the World’s Largest Open Source Data Sets

Directory of Open Access Journals (Sweden)

J. Piburn

2017-10-01

Full Text Available Spatiotemporal (ST analytics applied to major data sources such as the World Bank and World Health Organization has shown tremendous value in shedding light on the evolution of cultural, health, economic, and geopolitical landscapes on a global level. WSTAMP engages this opportunity by situating analysts, data, and analytics together within a visually rich and computationally rigorous online analysis environment. Since introducing WSTAMP at the First International Workshop on Spatiotemporal Computing, several transformative advances have occurred. Collaboration with human computer interaction experts led to a complete interface redesign that deeply immerses the analyst within a ST context, significantly increases visual and textual content, provides navigational crosswalks for attribute discovery, substantially reduce mouse and keyboard actions, and supports user data uploads. Secondly, the database has been expanded to include over 16,000 attributes, 50 years of time, and 200+ nation states and redesigned to support non-annual, non-national, city, and interaction data. Finally, two new analytics are implemented for analyzing large portfolios of multi-attribute data and measuring the behavioral stability of regions along different dimensions. These advances required substantial new approaches in design, algorithmic innovations, and increased computational efficiency. We report on these advances and inform how others may freely access the tool.

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

Science.gov (United States)

Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

2016-01-01

The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well. PMID:26861345

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges.

Science.gov (United States)

Chen, Yuanfang; Lee, Gyu Myoung; Shu, Lei; Crespi, Noel

2016-02-06

The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases) is an important research issue in the industrial applications of the Internet of Things (IoT). An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices) dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI) framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

Industrial Internet of Things-Based Collaborative Sensing Intelligence: Framework and Research Challenges

Directory of Open Access Journals (Sweden)

Yuanfang Chen

2016-02-01

Full Text Available The development of an efficient and cost-effective solution to solve a complex problem (e.g., dynamic detection of toxic gases is an important research issue in the industrial applications of the Internet of Things (IoT. An industrial intelligent ecosystem enables the collection of massive data from the various devices (e.g., sensor-embedded wireless devices dynamically collaborating with humans. Effectively collaborative analytics based on the collected massive data from humans and devices is quite essential to improve the efficiency of industrial production/service. In this study, we propose a collaborative sensing intelligence (CSI framework, combining collaborative intelligence and industrial sensing intelligence. The proposed CSI facilitates the cooperativity of analytics with integrating massive spatio-temporal data from different sources and time points. To deploy the CSI for achieving intelligent and efficient industrial production/service, the key challenges and open issues are discussed, as well.

Using Interactive Data Visualizations for Exploratory Analysis in Undergraduate Genomics Coursework: Field Study Findings and Guidelines

Science.gov (United States)

Kumar, Anuj; Nong, Paige; Su, Gang; Meng, Fan

2016-01-01

Life scientists increasingly use visual analytics to explore large data sets and generate hypotheses. Undergraduate biology majors should be learning these same methods. Yet visual analytics is one of the most underdeveloped areas of undergraduate biology education. This study sought to determine the feasibility of undergraduate biology majors conducting exploratory analysis using the same interactive data visualizations as practicing scientists. We examined 22 upper level undergraduates in a genomics course as they engaged in a case-based inquiry with an interactive heat map. We qualitatively and quantitatively analyzed students’ visual analytic behaviors, reasoning and outcomes to identify student performance patterns, commonly shared efficiencies and task completion. We analyzed students’ successes and difficulties in applying knowledge and skills relevant to the visual analytics case and related gaps in knowledge and skill to associated tool designs. Findings show that undergraduate engagement in visual analytics is feasible and could be further strengthened through tool usability improvements. We identify these improvements. We speculate, as well, on instructional considerations that our findings suggested may also enhance visual analytics in case-based modules. PMID:26877625

Constraint-Referenced Analytics of Algebra Learning

Science.gov (United States)

Sutherland, Scot M.; White, Tobin F.

2016-01-01

The development of the constraint-referenced analytics tool for monitoring algebra learning activities presented here came from the desire to firstly, take a more quantitative look at student responses in collaborative algebra activities, and secondly, to situate those activities in a more traditional introductory algebra setting focusing on…

"Let's work together": what do infants understand about collaborative goals?

Science.gov (United States)

Henderson, Annette M E; Woodward, Amanda L

2011-10-01

Collaboration is fundamental to our daily lives, yet little is known about how humans come to understand these activities. The present research was conducted to fill this void by using a novel visual habituation paradigm to investigate infants' understanding of the collaborative-goal structure of collaborative action. The findings of the three experiments reported here suggest that 14-month-old infants understand that the actions of collaborative partners are complementary and critical to the attainment of a common collaborative goal. Importantly, 14-month-olds do not interpret the actions of two individuals in terms of a collaborative goal when their actions are not causally related. The implications of our findings for theories of collaboration and folk psychology are discussed. Published by Elsevier B.V.

Frameworks for visualization at the extreme scale

International Nuclear Information System (INIS)

Joy, Kenneth I; Miller, Mark; Childs, Hank; Bethel, E Wes; Clyne, John; Ostrouchov, George; Ahern, Sean

2007-01-01

The challenges of visualization at the extreme scale involve issues of scale, complexity, temporal exploration and uncertainty. The Visualization and Analytics Center for Enabling Technologies (VACET) focuses on leveraging scientific visualization and analytics software technology as an enabling technology to increased scientific discovery and insight. In this paper, we introduce new uses of visualization frameworks through the introduction of Equivalence Class Functions (ECFs). These functions give a new class of derived quantities designed to greatly expand the ability of the end user to explore and visualize data. ECFs are defined over equivalence classes (i.e., groupings) of elements from an original mesh, and produce summary values for the classes as output. ECFs can be used in the visualization process to directly analyze data, or can be used to synthesize new derived quantities on the original mesh. The design of ECFs enable a parallel implementation that allows the use of these techniques on massive data sets that require parallel processing

Master VISUALLY Excel 2010

CERN Document Server

Marmel, Elaine

2010-01-01

The complete visual reference on Excel basics. Aimed at visual learners who are seeking an all-in-one reference that provides in-depth coveage of Excel from a visual viewpoint, this resource delves into all the newest features of Excel 2010. You'll explore Excel with helpful step-by-step instructions that show you, rather than tell you, how to navigate Excel, work with PivotTables and PivotCharts, use macros to streamline work, and collaborate with other users in one document.: This two-color guide features screen shots with specific, numbered instructions so you can learn the actions you need

Visualizing Decision Trees in Games to Support Children's Analytic Reasoning: Any Negative Effects on Gameplay?

Directory of Open Access Journals (Sweden)

Robert Haworth

2010-01-01

Full Text Available The popularity and usage of digital games has increased in recent years, bringing further attention to their design. Some digital games require a significant use of higher order thought processes, such as problem solving and reflective and analytical thinking. Through the use of appropriate and interactive representations, these thought processes could be supported. A visualization of the game's internal structure is an example of this. However, it is unknown whether including these extra representations will have a negative effect on gameplay. To investigate this issue, a digital maze-like game was designed with its underlying structure represented as a decision tree. A qualitative, exploratory study with children was performed to examine whether the tree supported their thought processes and what effects, if any, the tree had on gameplay. This paper reports the findings of this research and discusses the implications for the design of games in general.

Penetrating the Fog: Analytics in Learning and Education

Science.gov (United States)

Siemens, George; Long, Phil

2011-01-01

Attempts to imagine the future of education often emphasize new technologies--ubiquitous computing devices, flexible classroom designs, and innovative visual displays. But the most dramatic factor shaping the future of higher education is something that people cannot actually touch or see: "big data and analytics." Learning analytics is still in…

Visual Information Communications International Conference

CERN Document Server

Nguyen, Quang Vinh; Zhang, Kang; VINCI'09

2010-01-01

Visual Information Communication is based on VINCI'09, The Visual Information Communications International Conference, September 2009 in Sydney, Australia. Topics covered include The Arts of Visual Layout, Presentation & Exploration, The Design of Visual Attributes, Symbols & Languages, Methods for Visual Analytics and Knowledge Discovery, Systems, Interfaces and Applications of Visualization, Methods for Multimedia Data Recognition & Processing. This cutting-edge book addresses the issues of knowledge discovery, end-user programming, modeling, rapid systems prototyping, education, and design activities. Visual Information Communications is an edited volume whose contributors include well-established researchers worldwide, from diverse disciplines including architects, artists, engineers, and scientists. Visual Information Communication is designed for a professional audience composed of practitioners and researchers working in the field of digital design and visual communications. This volume i...

Design and evaluation of virtual environments mechanisms to support remote collaboration on complex process diagrams

NARCIS (Netherlands)

Poppe, E.; Brown, R.; Recker, J.; Johnson, D.; Vanderfeesten, I.T.P.

2017-01-01

Many organizational analysis tasks are solved by collaborating teams. In technology-mediated collaborations, enabling relevant visual cues is a core issue with existing technology. We explore whether avatars can provide relevant cues in collaborative virtual environments. To do so, we develop a

Developing Visual Thinking in the Electronic Health Record.

Science.gov (United States)

Boyd, Andrew D; Young, Christine D; Amatayakul, Margret; Dieter, Michael G; Pawola, Lawrence M

2017-01-01

The purpose of this vision paper is to identify how data visualization could transform healthcare. Electronic Health Records (EHRs) are maturing with new technology and tools being applied. Researchers are reaping the benefits of data visualization to better access compilations of EHR data for enhanced clinical research. Data visualization, while still primarily the domain of clinical researchers, is beginning to show promise for other stakeholders. A non-exhaustive review of the literature indicates that respective to the growth and development of the EHR, the maturity of data visualization in healthcare is in its infancy. Visual analytics has been only cursorily applied to healthcare. A fundamental issue contributing to fragmentation and poor coordination of healthcare delivery is that each member of the healthcare team, including patients, has a different view. Summarizing all of this care comprehensively for any member of the healthcare team is a "wickedly hard" visual analytics and data visualization problem to solve.

Mapping longitudinal scientific progress, collaboration and impact of the Alzheimer's disease neuroimaging initiative.

Directory of Open Access Journals (Sweden)

Xiaohui Yao

Full Text Available Alzheimer's disease neuroimaging initiative (ADNI is a landmark imaging and omics study in AD. ADNI research literature has increased substantially over the past decade, which poses challenges for effectively communicating information about the results and impact of ADNI-related studies. In this work, we employed advanced information visualization techniques to perform a comprehensive and systematic mapping of the ADNI scientific growth and impact over a period of 12 years.Citation information of ADNI-related publications from 01/01/2003 to 05/12/2015 were downloaded from the Scopus database. Five fields, including authors, years, affiliations, sources (journals, and keywords, were extracted and preprocessed. Statistical analyses were performed on basic publication data as well as journal and citations information. Science mapping workflows were conducted using the Science of Science (Sci2 Tool to generate geospatial, topical, and collaboration visualizations at the micro (individual to macro (global levels such as geospatial layouts of institutional collaboration networks, keyword co-occurrence networks, and author collaboration networks evolving over time.During the studied period, 996 ADNI manuscripts were published across 233 journals and conference proceedings. The number of publications grew linearly from 2008 to 2015, so did the number of involved institutions. ADNI publications received much more citations than typical papers from the same set of journals. Collaborations were visualized at multiple levels, including authors, institutions, and research areas. The evolution of key ADNI research topics was also plotted over the studied period.Both statistical and visualization results demonstrate the increasing attention of ADNI research, strong citation impact of ADNI publications, the expanding collaboration networks among researchers, institutions and ADNI core areas, and the dynamic evolution of ADNI research topics. The visualizations

BIM-based collaborative design and socio-technical analytics of green buildings

NARCIS (Netherlands)

El-Diraby, T.; Krijnen, T.; Papagelis, M.

2017-01-01

As Building Information Modeling evolves into becoming the central mean for coordinating project design and planning activities, we notice a few limitations/opportunities in the way current BIM tools address the needs for integrated design, collaboration and analysis (the initial objective of BIM).

Metrology and analytical chemistry: Bridging the cultural gap

International Nuclear Information System (INIS)

King, Bernard

2002-01-01

Metrology in general and issues such as traceability and measurement uncertainty in particular are new to most analytical chemists and many remain to be convinced of their value. There is a danger of the cultural gap between metrologists and analytical chemists widening with unhelpful consequences and it is important that greater collaboration and cross-fertilisation is encouraged. This paper discusses some of the similarities and differences in the approaches adopted by metrologists and analytical chemists and indicates how these approaches can be combined to establish a unique metrology of chemical measurement which could be accepted by both cultures. (author)

Teach yourself visually complete Excel

CERN Document Server

McFedries, Paul

2013-01-01

Get the basics of Excel and then go beyond with this new instructional visual guide While many users need Excel just to create simple worksheets, many businesses and professionals rely on the advanced features of Excel to handle things like database creation and data analysis. Whatever project you have in mind, this visual guide takes you step by step through what each step should look like. Veteran author Paul McFedries first presents the basics and then gradually takes it further with his coverage of designing worksheets, collaborating between worksheets, working with visual data

The association between stereotyping and interprofessional collaborative practice.

Science.gov (United States)

Rachma Sari, Vika; Hariyati, Rr Tutik Sri; Syuhaimie Hamid, Achir Yani

2018-02-01

This study aimed to identify the association between stereotyping and professional intercollaborative practice. This study used a cross-sectional analytical study involving physicians, nurses, pharmacists, and dietitians in a hospital in Jakarta, Indonesia, who were selected using the stratified random sampling method. Data was collected using the Student Stereotypes Rating Questionnaire (SSRQ) and the Assessment of Interprofessional Team Collaboration Scale (AITCS). The stereotyping level was analyzed based on a nine-point SSRQ, while interprofessional collaborative practice was scored based on partnership/shared decision-making, cooperation, and coordination. Stereotyping was shown to significantly correlate with interprofessional collaborative practice as measured by the SSRQ and AITCS. Poor interprofessional collaborative practice in subscale partnership/decision-making was dominant. Also, low-rating stereotyping was shown to be dominant with poor interprofessional collaborative practice. The research recommends that health care providers improve partnership/ decision-making skills for better interprofessional collaboration. For further research, it's recommended to explore another barrier of interprofessional collaborative practice. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.

Advanced Dynamics Analytical and Numerical Calculations with MATLAB

CERN Document Server

Marghitu, Dan B

2012-01-01

Advanced Dynamics: Analytical and Numerical Calculations with MATLAB provides a thorough, rigorous presentation of kinematics and dynamics while using MATLAB as an integrated tool to solve problems. Topics presented are explained thoroughly and directly, allowing fundamental principles to emerge through applications from areas such as multibody systems, robotics, spacecraft and design of complex mechanical devices. This book differs from others in that it uses symbolic MATLAB for both theory and applications. Special attention is given to solutions that are solved analytically and numerically using MATLAB. The illustrations and figures generated with MATLAB reinforce visual learning while an abundance of examples offer additional support. This book also: Provides solutions analytically and numerically using MATLAB Illustrations and graphs generated with MATLAB reinforce visual learning for students as they study Covers modern technical advancements in areas like multibody systems, robotics, spacecraft and des...

End-User Development of Information Visualization

DEFF Research Database (Denmark)

Pantazos, Kostas; Lauesen, Søren; Vatrapu, Ravi

2013-01-01

such as data manipulation, but no formal training in programming. 18 visualization tools were surveyed from an enduser developer perspective. The results of this survey study show that end-user developers need better tools to create and modify custom visualizations. A closer collaboration between End......This paper investigates End-User Development of Information Visualization. More specifically, we investigated how existing visualization tools allow end-user developers to construct visualizations. End-user developers have some developing or scripting skills to perform relatively advanced tasks......-User Development and Information Visualization researchers could contribute towards the development of better tools to support custom visualizations. In addition, as empirical evaluations of these tools are lacking both research communities should focus more on this aspect. The study serves as a starting point...

Molecular simulations and visualization: introduction and overview.

Science.gov (United States)

Hirst, Jonathan D; Glowacki, David R; Baaden, Marc

2014-01-01

Here we provide an introduction and overview of current progress in the field of molecular simulation and visualization, touching on the following topics: (1) virtual and augmented reality for immersive molecular simulations; (2) advanced visualization and visual analytic techniques; (3) new developments in high performance computing; and (4) applications and model building.

A Strategy for Uncertainty Visualization Design

Science.gov (United States)

2009-10-01

143–156, Magdeburg , Germany . [11] Thomson, J., Hetzler, E., MacEachren, A., Gahegan, M. and Pavel, M. (2005), A Typology for Visualizing Uncertainty...and Stasko [20] to bridge analytic gaps in visualization design, when tasks in the strategy overlap (and therefore complement) design frameworks

Toward a Shared Vocabulary for Visual Analysis: An Analytic Toolkit for Deconstructing the Visual Design of Graphic Novels

Science.gov (United States)

Connors, Sean P.

2012-01-01

Literacy educators might advocate using graphic novels to develop students' visual literacy skills, but teachers who lack a vocabulary for engaging in close analysis of visual texts may be reluctant to teach them. Recognizing this, teacher educators should equip preservice teachers with a vocabulary for analyzing visual texts. This article…

Unpacking complexities of managerial subjectivity: An analytic fixation on constitutive dynamics

DEFF Research Database (Denmark)

Plotnikof, Mie

2012-01-01

, and the analytic challenges of discourse/Discourse-distinctions and avoiding agency-structure-dualism. This paper proposes an integral conceptualization of subjectification that directs analytic attention to the complex constitutive dynamics of organizational discourses and agency normative to organizational...... is discussed with a case-study of public managers in collaborative governance processes in the Danish day-care sector. With complex-sensitive analytics the paper contributes to the ‘plurivocal’ debate on advancing organizational discourse approaches....

Exploring the Potential of 3D Visualization Techniques for Usage in Collaborative Design

NARCIS (Netherlands)

Wits, Wessel Willems; Noël, F.; Masclet, C.

2011-01-01

Best practice for collaborative design demands good interaction between its collaborators. The capacity to share common knowledge about design models at hand is a basic requirement. With current advancing technologies gathering collective knowledge is more straightforward, as the dialog between

A Graphics Design Framework to Visualize Multi-Dimensional Economic Datasets

Science.gov (United States)

Chandramouli, Magesh; Narayanan, Badri; Bertoline, Gary R.

2013-01-01

This study implements a prototype graphics visualization framework to visualize multidimensional data. This graphics design framework serves as a "visual analytical database" for visualization and simulation of economic models. One of the primary goals of any kind of visualization is to extract useful information from colossal volumes of…

Visualization analysis and design

CERN Document Server

Munzner, Tamara

2015-01-01

Visualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques for spatial data, and visual analytics techniques for interweaving data transformation and analysis with interactive visual exploration. It emphasizes the careful validation of effectiveness and the consideration of function before form. The book breaks down visualization design according to three questions: what data users need to see, why users need to carry out their tasks, and how the visual representations proposed can be constructed and manipulated. It walks readers through the use of space and color to visually encode data in a view, the trade-offs between changing a single view and using multiple linked views, and the ways to reduce the amount of data shown in each view. The book concludes with six case stu...

Forecasting Hotspots-A Predictive Analytics Approach.

Science.gov (United States)

Maciejewski, R; Hafen, R; Rudolph, S; Larew, S G; Mitchell, M A; Cleveland, W S; Ebert, D S

2011-04-01

Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among people, events, and places in space and time. Analysts search for events of interest through statistical tools linked to visual displays, drill down into the data, and form hypotheses based upon the available information. However, current systems stop short of predicting events. In spatiotemporal data, analysts are searching for regions of space and time with unusually high incidences of events (hotspots). In the cases where hotspots are found, analysts would like to predict how these regions may grow in order to plan resource allocation and preventative measures. Furthermore, analysts would also like to predict where future hotspots may occur. To facilitate such forecasting, we have created a predictive visual analytics toolkit that provides analysts with linked spatiotemporal and statistical analytic views. Our system models spatiotemporal events through the combination of kernel density estimation for event distribution and seasonal trend decomposition by loess smoothing for temporal predictions. We provide analysts with estimates of error in our modeling, along with spatial and temporal alerts to indicate the occurrence of statistically significant hotspots. Spatial data are distributed based on a modeling of previous event locations, thereby maintaining a temporal coherence with past events. Such tools allow analysts to perform real-time hypothesis testing, plan intervention strategies, and allocate resources to correspond to perceived threats.

Understanding Digital Note-Taking Practice for Visualization.

Science.gov (United States)

Willett, Wesley; Goffin, Pascal; Isenberg, Petra

2015-05-13

We present results and design implications from a study of digital note-taking practice to examine how visualization can support revisitation, reflection, and collaboration around notes. As digital notebooks become common forms of external memory, keeping track of volumes of content is increasingly difficult. Information visualization tools can help give note-takers an overview of their content and allow them to explore diverse sets of notes, find and organize related content, and compare their notes with their collaborators. To ground the design of such tools, we conducted a detailed mixed-methods study of digital note-taking practice. We identify a variety of different editing, organization, and sharing methods used by digital note-takers, many of which result in notes becoming "lost in the pile''. These findings form the basis for our design considerations that examine how visualization can support the revisitation, organization, and sharing of digital notes.

From flipchart to glossy visualisation through collaboration and d3.js

CERN Multimedia

CERN. Geneva

2015-01-01

Representing complex data visually is an important tool for communication, and the CERN Knowledge Transfer Annual Report is no exception to this. I want to share with the audience our experience with data visualization through the strength of collaboration, and the power and simplicity of the d3.js javascript framework.

Shopping For Danger: E-commerce techniques applied to collaboration in cyber security

Energy Technology Data Exchange (ETDEWEB)

Bruce, Joseph R.; Fink, Glenn A.

2012-05-24

Collaboration among cyber security analysts is essential to a successful protection strategy on the Internet today, but it is uncommonly practiced or encouraged in operating environments. Barriers to productive collaboration often include data sensitivity, time and effort to communicate, institutional policy, and protection of domain knowledge. We propose an ambient collaboration framework, Vulcan, designed to remove the barriers of time and effort and mitigate the others. Vulcan automated data collection, collaborative filtering, and asynchronous dissemination, eliminating the effort implied by explicit collaboration among peers. We instrumented two analytic applications and performed a mock analysis session to build a dataset and test the output of the system.

Collaborative form(s)

DEFF Research Database (Denmark)

Gunn, Wendy

anthropology engages groups of people within collaborative, interdisciplinary, inter-organizational design processes and co-analytic activities vs. the individual anthropologist conducting studies of people. In doing anthropology by means of design as Gatt and Ingold (2013) have shown, design is considered...... the process of research rather than its object. In its temporal orientation, anthropology by means of design moves, ‘…forward with people in tandem with their desires and aspirations rather than going back over times passed’ (ibid 2013: 141). Doing design by means of anthropology takes as its most fundamental...

The importance of visualization in cartographic communication

Directory of Open Access Journals (Sweden)

Ikonović Vesna

2011-01-01

Full Text Available Visualization is a field of computer graphics which explores the analytical and communication possibilities of visual presentation. Visualization explores the possibilities of using images, similar to three-dimensional world, as models so that analysis and communication can be improved. Visualization depends on new computer techniques of data analysis and presentation, as well as on the accuracy, exactness and form of said data. Visualization is a scientific tool, but its application demands art, imagination and intuition. Visualization demands the use of the latest and the best computer technology.

Collaboration system for simulation using commercial Web3D

International Nuclear Information System (INIS)

Okamoto, Koji; Ohkubo, Kohei

2004-01-01

The Web-3D system has been widely used in the internet. It can show the 3D environment easily and friendly. In order to develop the network collaboration system, the Web-3D system is used as the front end of the visualization tool. The 3D geometries have been transferred from the server using HTTP with the viewpoint, one of the commercialized Web-3D. The simulation results are directly transferred to the client using the TCP/IP socket with JAVA. The viewpoint can be controlled by the JAVA, so the transferred simulation data are displayed on the web, in real-time. The multi-client system enables the visualization of the real-time simulation results with remote site. The same results are shown on the remote web site, simultaneously. This means the remote collaboration can be achievable for the real-time simulation. Also, the system has the feedback system, which control the simulation parameter remotely. In this prototype system, the key feature of the collaboration system are discussed using the viewpoint as the frontend. (author)

Visual histories of decision processes for collaborative decision making

OpenAIRE

Kozlova, Karine

2016-01-01

Remembering, understanding and reconstructing past activities is a necessary part of any learning, sense-making or decision making process. It is also essential for any collaborative activity. This dissertation investigates the design and evaluation of systems to support decision remembering, understanding and reconstruction by groups and individuals. By conducting three qualitative case studies of small professional groups, we identify the critical activities where history functionality is n...

Big data analytics as a service infrastructure: challenges, desired properties and solutions

International Nuclear Information System (INIS)

Martín-Márquez, Manuel

2015-01-01

CERN's accelerator complex generates a very large amount of data. A large volumen of heterogeneous data is constantly generated from control equipment and monitoring agents. These data must be stored and analysed. Over the decades, CERN's researching and engineering teams have applied different approaches, techniques and technologies for this purpose. This situation has minimised the necessary collaboration and, more relevantly, the cross data analytics over different domains. These two factors are essential to unlock hidden insights and correlations between the underlying processes, which enable better and more efficient daily-based accelerator operations and more informed decisions. The proposed Big Data Analytics as a Service Infrastructure aims to: (1) integrate the existing developments; (2) centralise and standardise the complex data analytics needs for CERN's research and engineering community; (3) deliver real-time, batch data analytics and information discovery capabilities; and (4) provide transparent access and Extract, Transform and Load (ETL), mechanisms to the various and mission-critical existing data repositories. This paper presents the desired objectives and properties resulting from the analysis of CERN's data analytics requirements; the main challenges: technological, collaborative and educational and; potential solutions. (paper)

The Qualities Needed for a Successful Collaboration: A Contribution to the Conceptual Understanding of Collaboration for Efficient Public Transport

Directory of Open Access Journals (Sweden)

Robert Hrelja

2016-06-01

Full Text Available The creation of an efficient public transport system requires collaborations between formal independent organizations. This paper examines collaborations between public and private organizations and passengers, with the aim of contributing to the conceptual understanding of collaborations on public transport. The study begins by describing previous research on collaboration in the public transport area and in other research fields analytically relevant for public transport. Accordingly, collaboration is defined as an attempt to overcome problems with collective action and to transform a situation in which the various organizations operate independently into a situation where they act in concert to achieve shared objectives. The collaboration process involves the establishment of joint rules and structures that govern the relationship and behavior of the organizations. According to this definition, collaboration is a more sophisticated form of collective action than is indicated by terms such as “co-operation” or “coordination”. Fully-functioning collaboration can be described as a form of “co-action”, as opposed to “individual action”. In co-action, formal independent organizations together reap the benefits of working together and achieve more than if they had acted alone. Co-action can be regarded as a gradual trust-building process that requires qualities such as mutual confidence, an understanding of other organizations’ motivations, and joint problem formulation.

Prototyping Visual Learning Analytics Guided by an Educational Theory Informed Goal

Science.gov (United States)

Hillaire, Garron; Rappolt-Schlichtmann, Gabrielle; Ducharme, Kim

2016-01-01

Prototype work can support the creation of data visualizations throughout the research and development process through paper prototypes with sketching, designed prototypes with graphic design tools, and functional prototypes to explore how the implementation will work. One challenging aspect of data visualization work is coordinating the expertise…

Big Data Analytics in Chemical Engineering.

Science.gov (United States)

Chiang, Leo; Lu, Bo; Castillo, Ivan

2017-06-07

Big data analytics is the journey to turn data into insights for more informed business and operational decisions. As the chemical engineering community is collecting more data (volume) from different sources (variety), this journey becomes more challenging in terms of using the right data and the right tools (analytics) to make the right decisions in real time (velocity). This article highlights recent big data advancements in five industries, including chemicals, energy, semiconductors, pharmaceuticals, and food, and then discusses technical, platform, and culture challenges. To reach the next milestone in multiplying successes to the enterprise level, government, academia, and industry need to collaboratively focus on workforce development and innovation.

EmailTime: visual analytics and statistics for temporal email

Science.gov (United States)

Erfani Joorabchi, Minoo; Yim, Ji-Dong; Shaw, Christopher D.

2011-01-01

Although the discovery and analysis of communication patterns in large and complex email datasets are difficult tasks, they can be a valuable source of information. We present EmailTime, a visual analysis tool of email correspondence patterns over the course of time that interactively portrays personal and interpersonal networks using the correspondence in the email dataset. Our approach is to put time as a primary variable of interest, and plot emails along a time line. EmailTime helps email dataset explorers interpret archived messages by providing zooming, panning, filtering and highlighting etc. To support analysis, it also measures and visualizes histograms, graph centrality and frequency on the communication graph that can be induced from the email collection. This paper describes EmailTime's capabilities, along with a large case study with Enron email dataset to explore the behaviors of email users within different organizational positions from January 2000 to December 2001. We defined email behavior as the email activity level of people regarding a series of measured metrics e.g. sent and received emails, numbers of email addresses, etc. These metrics were calculated through EmailTime. Results showed specific patterns in the use email within different organizational positions. We suggest that integrating both statistics and visualizations in order to display information about the email datasets may simplify its evaluation.

The Earth Data Analytic Services (EDAS) Framework

Science.gov (United States)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

Data science and big data analytics discovering, analyzing, visualizing and presenting data

CERN Document Server

2014-01-01

Data Science and Big Data Analytics is about harnessing the power of data for new insights. The book covers the breadth of activities and methods and tools that Data Scientists use. The content focuses on concepts, principles and practical applications that are applicable to any industry and technology environment, and the learning is supported and explained with examples that you can replicate using open-source software. This book will help you: Become a contributor on a data science teamDeploy a structured lifecycle approach to data analytics problemsApply appropriate analytic techniques and

NASA's Scientific Visualization Studio

Science.gov (United States)

Mitchell, Horace G.

2003-01-01

Since 1988, the Scientific Visualization Studio(SVS) at NASA Goddard Space Flight Center has produced scientific visualizations of NASA s scientific research and remote sensing data for public outreach. These visualizations take the form of images, animations, and end-to-end systems and have been used in many venues: from the network news to science programs such as NOVA, from museum exhibits at the Smithsonian to White House briefings. This presentation will give an overview of the major activities and accomplishments of the SVS, and some of the most interesting projects and systems developed at the SVS will be described. Particular emphasis will be given to the practices and procedures by which the SVS creates visualizations, from the hardware and software used to the structures and collaborations by which products are designed, developed, and delivered to customers. The web-based archival and delivery system for SVS visualizations at svs.gsfc.nasa.gov will also be described.

Ciência & Saúde Coletiva: scientific production analysis and collaborative research networks.

Science.gov (United States)

Conner, Norma; Provedel, Attilio; Maciel, Ethel Leonor Noia

2017-03-01

The purpose of this metric and descriptive study was to identify the most productive authors and their collaborative research networks from articles published in Ciência & Saúde Coletiva between, 2005, and 2014. Authors meeting the cutoff criteria of at least 10 articles were considered the most productive authors. VOSviewer and Network Workbench technologies were applied for visual representations of collaborative research networks involving the most productive authors in the period. Initial analysis recovered 2511 distinct articles, with 8920 total authors with an average of 3.55 authors per article. Author analysis revealed 6288 distinct authors, 24 of these authors were identified as the most productive. These 24 authors generated 287 articles with an average of 4.31 authors per article, and represented 8 separate collaborative partnerships, the largest of which had 14 authors, indicating a significant degree of collaboration among these authors. This analysis provides a visual representation of networks of knowledge development in public health and demonstrates the usefulness of VOSviewer and Network Workbench technologies in future research.

A Day in the Professional Life of a Collaborative Biostatistician Deconstructed: Implications for Curriculum Design

Science.gov (United States)

Samsa, Gregory P.

2018-01-01

Collaborative biostatistics is the creative application of statistical tools to biomedical problems. The relatively modest literature about the traits of effective collaborative biostatisticians focuses on four core competencies: (a) technical and analytical; (b) substance-matter knowledge; (c) communication; and (d) problem solving and problem…

The Importance of Earth Observations and Data Collaboration within Environmental Intelligence Supporting Arctic Research

Science.gov (United States)

Casas, Joseph

2017-01-01

Within the IARPC Collaboration Team activities of 2016, Arctic in-situ and remote earth observations advanced topics such as :1) exploring the role for new and innovative autonomous observing technologies in the Arctic; 2) advancing catalytic national and international community based observing efforts in support of the National Strategy for the Arctic Region; and 3) enhancing the use of discovery tools for observing system collaboration such as the U.S. National Oceanic and Atmospheric Administration (NOAA) Arctic Environmental Response Management Application (ERMA) and the U.S. National Aeronautics and Space Administration (NASA) Arctic Collaborative Environment (ACE) project geo reference visualization decision support and exploitation internet based tools. Critical to the success of these earth observations for both in-situ and remote systems is the emerging of new and innovative data collection technologies and comprehensive modeling as well as enhanced communications and cyber infrastructure capabilities which effectively assimilate and dissemination many environmental intelligence products in a timely manner. The Arctic Collaborative Environment (ACE) project is well positioned to greatly enhance user capabilities for accessing, organizing, visualizing, sharing and producing collaborative knowledge for the Arctic.

Adaptive semantics visualization

CERN Document Server

Nazemi, Kawa

2016-01-01

This book introduces a novel approach for intelligent visualizations that adapts the different visual variables and data processing to human’s behavior and given tasks. Thereby a number of new algorithms and methods are introduced to satisfy the human need of information and knowledge and enable a usable and attractive way of information acquisition. Each method and algorithm is illustrated in a replicable way to enable the reproduction of the entire “SemaVis” system or parts of it. The introduced evaluation is scientifically well-designed and performed with more than enough participants to validate the benefits of the methods. Beside the introduced new approaches and algorithms, readers may find a sophisticated literature review in Information Visualization and Visual Analytics, Semantics and information extraction, and intelligent and adaptive systems. This book is based on an awarded and distinguished doctoral thesis in computer science.

Writing virtual environments for software visualization

CERN Document Server

Jeffery, Clinton

2015-01-01

This book describes the software for creating networked, 3D multi-user virtual environments that allow users to create and remotely share visualizations of program behavior. The authors cover the major features of collaborative virtual environments and how to program them in a very high level language, and show how visualization can enable important advances in our ability to understand and reduce the costs of maintaining software. The book also examines the application of popular game-like software technologies.   • Discusses the acquisition of program behavior data to be visualized • Demonstrates the integration of multiple 2D and 3D dynamic views within a 3Dscene • Presents the network messaging capabilities to share those visualizations

Application of Andrew's Plots to Visualization of Multidimensional Data

Science.gov (United States)

Grinshpun, Vadim

2016-01-01

Importance: The article raises a point of visual representation of big data, recently considered to be demanded for many scientific and real-life applications, and analyzes particulars for visualization of multi-dimensional data, giving examples of the visual analytics-related problems. Objectives: The purpose of this paper is to study application…

Amending the Characterization of Guidance in Visual Analytics

OpenAIRE

Ceneda, Davide; Gschwandtner, Theresia; May, Thorsten; Miksch, Silvia; Schulz, Hans-Jörg; Streit, Marc; Tominski, Christian

2017-01-01

At VAST 2016, a characterization of guidance has been presented. It includes a definition of guidance and a model of guidance based on van Wijk's model of visualization. This note amends the original characterization of guidance in two aspects. First, we provide a clarification of what guidance actually is (and is not). Second, we insert into the model a conceptually relevant link that was missing in the original version.

High performance visual display for HENP detectors

International Nuclear Information System (INIS)

McGuigan, Michael; Smith, Gordon; Spiletic, John; Fine, Valeri; Nevski, Pavel

2001-01-01

A high end visual display for High Energy Nuclear Physics (HENP) detectors is necessary because of the sheer size and complexity of the detector. For BNL this display will be of special interest because of STAR and ATLAS. To load, rotate, query, and debug simulation code with a modern detector simply takes too long even on a powerful work station. To visualize the HENP detectors with maximal performance we have developed software with the following characteristics. We develop a visual display of HENP detectors on BNL multiprocessor visualization server at multiple level of detail. We work with general and generic detector framework consistent with ROOT, GAUDI etc, to avoid conflicting with the many graphic development groups associated with specific detectors like STAR and ATLAS. We develop advanced OpenGL features such as transparency and polarized stereoscopy. We enable collaborative viewing of detector and events by directly running the analysis in BNL stereoscopic theatre. We construct enhanced interactive control, including the ability to slice, search and mark areas of the detector. We incorporate the ability to make a high quality still image of a view of the detector and the ability to generate animations and a fly through of the detector and output these to MPEG or VRML models. We develop data compression hardware and software so that remote interactive visualization will be possible among dispersed collaborators. We obtain real time visual display for events accumulated during simulations

Live Storybook Outcomes of Pilot Multidisciplinary Elementary Earth Science Collaborative Project

Science.gov (United States)

Soeffing, C.; Pierson, R.

2017-12-01

Live Storybook Outcomes of pilot multidisciplinary elementary earth science collaborative project Anchoring phenomena leading to student led investigations are key to applying the NGSS standards in the classroom. This project employs the GLOBE elementary storybook, Discoveries at Willow Creek, as an inspiration and operational framework for a collaborative pilot project engaging 4th grade students in asking questions, collecting relevant data, and using analytical tools to document and understand natural phenomena. The Institute of Global Environmental Strategies (IGES), a GLOBE Partner, the Outdoor Campus, an informal educational outdoor learning facility managed by South Dakota Game, Fish and Parks, University of Sioux Falls, and All City Elementary, Sioux Falls are collaborating partners in this project. The Discoveries at Willow Creek storyline introduces young students to the scientific process, and models how they can apply science and engineering practices (SEPs) to discover and understand the Earth system in which they live. One innovation associated with this project is the formal engagement of elementary students in a global citizen science program (for all ages), GLOBE Observer, and engaging them in data collection using GLOBE Observer's Cloud and Mosquito Habitat Mapper apps. As modeled by the fictional students from Willow Creek, the 4th grade students will identify their 3 study sites at the Outdoor Campus, keep a journal, and record observations. The students will repeat their investigations at the Outdoor Campus to document and track change over time. Students will be introduced to "big data" in a manageable way, as they see their observations populate GLOBE's map-based data visualization and . Our research design recognizes the comfort and familiarity factor of literacy activities in the elementary classroom for students and teachers alike, and postulates that connecting a science education project to an engaging storybook text will contribute to a

Student Visual Communication of Evolution

Science.gov (United States)

Oliveira, Alandeom W.; Cook, Kristin

2017-06-01

Despite growing recognition of the importance of visual representations to science education, previous research has given attention mostly to verbal modalities of evolution instruction. Visual aspects of classroom learning of evolution are yet to be systematically examined by science educators. The present study attends to this issue by exploring the types of evolutionary imagery deployed by secondary students. Our visual design analysis revealed that students resorted to two larger categories of images when visually communicating evolution: spatial metaphors (images that provided a spatio-temporal account of human evolution as a metaphorical "walk" across time and space) and symbolic representations ("icons of evolution" such as personal portraits of Charles Darwin that simply evoked evolutionary theory rather than metaphorically conveying its conceptual contents). It is argued that students need opportunities to collaboratively critique evolutionary imagery and to extend their visual perception of evolution beyond dominant images.

Advanced tools for enhancing control room collaborations

International Nuclear Information System (INIS)

Abla, G.; Flanagan, S.M.; Peng, Q.; Burruss, J.R.; Schissel, D.P.

2006-01-01

The US National Fusion Collaboratory (NFC) project has been exploring a variety of computer and network technologies to develop a persistent, efficient, reliable and convenient collaborative environment for magnetic fusion research. One goal is to enhance remote and collocated team collaboration by integrating collaboration software tools into control room operations as well as with data analysis tools. To achieve this goal, the NFC recently introduced two new collaboration technologies into the DIII-D tokamak control room. The first technology is a high-resolution, large format Shared Display Wall (SDW). By creating a shared public display space and providing real time visual information about the multiple aspects of complex experiment activity, the large SDW plays an important role in increasing the rate of information dissemination and promoting interaction among team members. The second technology being implemented is the 'tokamak control room aware' Instant Messaging (IM) service. In addition to providing text-chat capabilities for research scientists, it enables them to automatically receive information about experiment operations and data analysis processes to remotely monitor the status of ongoing tokamak experiment. As a result, the IM service has become a unified portal interface for team collaboration and remote participation

Advanced tools for enhancing control room collaborations

Energy Technology Data Exchange (ETDEWEB)

Abla, G. [General Atomics, P.O. Box 85608, San Diego, CA 92186 5608 (United States)]. E-mail: abla@fusion.gat.com; Flanagan, S.M. [General Atomics, P.O. Box 85608, San Diego, CA 92186 5608 (United States); Peng, Q. [General Atomics, P.O. Box 85608, San Diego, CA 92186 5608 (United States); Burruss, J.R. [General Atomics, P.O. Box 85608, San Diego, CA 92186 5608 (United States); Schissel, D.P. [General Atomics, P.O. Box 85608, San Diego, CA 92186 5608 (United States)

2006-07-15

The US National Fusion Collaboratory (NFC) project has been exploring a variety of computer and network technologies to develop a persistent, efficient, reliable and convenient collaborative environment for magnetic fusion research. One goal is to enhance remote and collocated team collaboration by integrating collaboration software tools into control room operations as well as with data analysis tools. To achieve this goal, the NFC recently introduced two new collaboration technologies into the DIII-D tokamak control room. The first technology is a high-resolution, large format Shared Display Wall (SDW). By creating a shared public display space and providing real time visual information about the multiple aspects of complex experiment activity, the large SDW plays an important role in increasing the rate of information dissemination and promoting interaction among team members. The second technology being implemented is the 'tokamak control room aware' Instant Messaging (IM) service. In addition to providing text-chat capabilities for research scientists, it enables them to automatically receive information about experiment operations and data analysis processes to remotely monitor the status of ongoing tokamak experiment. As a result, the IM service has become a unified portal interface for team collaboration and remote participation.

Emergence of auditory-visual relations from a visual-visual baseline with auditory-specific consequences in individuals with autism.

Science.gov (United States)

Varella, André A B; de Souza, Deisy G

2014-07-01

Empirical studies have demonstrated that class-specific contingencies may engender stimulus-reinforcer relations. In these studies, crossmodal relations emerged when crossmodal relations comprised the baseline, and intramodal relations emerged when intramodal relations were taught during baseline. This study investigated whether auditory-visual relations (crossmodal) would emerge after participants learned a visual-visual baseline (intramodal) with auditory stimuli presented as specific consequences. Four individuals with autism learned AB and CD relations with class-specific reinforcers. When A1 and C1 were presented as samples, the selections of B1 and D1, respectively, were followed by an edible (R1) and a sound (S1). Selections of B2 and D2 under the control of A2 and C2, respectively, were followed by R2 and S2. Probe trials tested for visual-visual AC, CA, AD, DA, BC, CB, BD, and DB emergent relations and auditory-visual SA, SB, SC, and SD emergent relations. All of the participants demonstrated the emergence of all auditory-visual relations, and three of four participants showed emergence of all visual-visual relations. Thus, the emergence of auditory-visual relations from specific auditory consequences suggests that these relations do not depend on crossmodal baseline training. The procedure has great potential for applied technology to generate auditory-visual discriminations and stimulus classes in the context of behavior-analytic interventions for autism. © Society for the Experimental Analysis of Behavior.

The Diesel Combustion Collaboratory: Combustion Researchers Collaborating over the Internet

Energy Technology Data Exchange (ETDEWEB)

C. M. Pancerella; L. A. Rahn; C. Yang

2000-02-01

The Diesel Combustion Collaborator (DCC) is a pilot project to develop and deploy collaborative technologies to combustion researchers distributed throughout the DOE national laboratories, academia, and industry. The result is a problem-solving environment for combustion research. Researchers collaborate over the Internet using DCC tools, which include: a distributed execution management system for running combustion models on widely distributed computers, including supercomputers; web-accessible data archiving capabilities for sharing graphical experimental or modeling data; electronic notebooks and shared workspaces for facilitating collaboration; visualization of combustion data; and video-conferencing and data-conferencing among researchers at remote sites. Security is a key aspect of the collaborative tools. In many cases, the authors have integrated these tools to allow data, including large combustion data sets, to flow seamlessly, for example, from modeling tools to data archives. In this paper the authors describe the work of a larger collaborative effort to design, implement and deploy the DCC.

Visually observing comets

CERN Document Server

Seargent, David A J

2017-01-01

In these days of computers and CCD cameras, visual comet observers can still contribute scientifically useful data with the help of this handy reference for use in the field. Comets are one of the principal areas for productive pro-amateur collaboration in astronomy, but finding comets requires a different approach than the observing of more predictable targets. Principally directed toward amateur astronomers who prefer visual observing or who are interested in discovering a new comet or visually monitoring the behavior of known comets, it includes all the advice needed to thrive as a comet observer. After presenting a brief overview of the nature of comets and how we came to the modern understanding of comets, this book details the various types of observations that can usefully be carried out at the eyepiece of a telescope. Subjects range from how to search for new comets to visually estimating the brightness of comets and the length and orientation of tails, in addition to what to look for in comet heads a...

A Survey on Sensor Coverage and Visual Data Capturing/Processing/Transmission in Wireless Visual Sensor Networks

Directory of Open Access Journals (Sweden)

Florence G. H. Yap

2014-02-01

Full Text Available Wireless Visual Sensor Networks (WVSNs where camera-equipped sensor nodes can capture, process and transmit image/video information have become an important new research area. As compared to the traditional wireless sensor networks (WSNs that can only transmit scalar information (e.g., temperature, the visual data in WVSNs enable much wider applications, such as visual security surveillance and visual wildlife monitoring. However, as compared to the scalar data in WSNs, visual data is much bigger and more complicated so intelligent schemes are required to capture/process/ transmit visual data in limited resources (hardware capability and bandwidth WVSNs. WVSNs introduce new multi-disciplinary research opportunities of topics that include visual sensor hardware, image and multimedia capture and processing, wireless communication and networking. In this paper, we survey existing research efforts on the visual sensor hardware, visual sensor coverage/deployment, and visual data capture/ processing/transmission issues in WVSNs. We conclude that WVSN research is still in an early age and there are still many open issues that have not been fully addressed. More new novel multi-disciplinary, cross-layered, distributed and collaborative solutions should be devised to tackle these challenging issues in WVSNs.

An Agent Based Collaborative Simplification of 3D Mesh Model

Science.gov (United States)

Wang, Li-Rong; Yu, Bo; Hagiwara, Ichiro

Large-volume mesh model faces the challenge in fast rendering and transmission by Internet. The current mesh models obtained by using three-dimensional (3D) scanning technology are usually very large in data volume. This paper develops a mobile agent based collaborative environment on the development platform of mobile-C. Communication among distributed agents includes grasping image of visualized mesh model, annotation to grasped image and instant message. Remote and collaborative simplification can be efficiently conducted by Internet.

Visualizing Repertory Grid Data for Formative Assessment

DEFF Research Database (Denmark)

Pantazos, Kostas; Vatrapu, Ravi; Hussain, Abid

2013-01-01

at facilitating data analysis through a visual and interactive approach, which allows users to understand their data, reflect, and make better decisions. This paper presents an interactive visualization tool for teachers and students. The tool visualizes repertory grid data using two dashboards, where teachers...... and students can investigate constructs and rating elements of students at the individual or group level. Visualizing the repertory grid data is an initial attempt towards teaching analytics. Future work will focus on evaluating the tool in a real setting with teachers and students, and collecting suggestions...

GWAS in a box: statistical and visual analytics of structured associations via GenAMap.

Directory of Open Access Journals (Sweden)

Eric P Xing

Full Text Available With the continuous improvement in genotyping and molecular phenotyping technology and the decreasing typing cost, it is expected that in a few years, more and more clinical studies of complex diseases will recruit thousands of individuals for pan-omic genetic association analyses. Hence, there is a great need for algorithms and software tools that could scale up to the whole omic level, integrate different omic data, leverage rich structure information, and be easily accessible to non-technical users. We present GenAMap, an interactive analytics software platform that 1 automates the execution of principled machine learning methods that detect genome- and phenome-wide associations among genotypes, gene expression data, and clinical or other macroscopic traits, and 2 provides new visualization tools specifically designed to aid in the exploration of association mapping results. Algorithmically, GenAMap is based on a new paradigm for GWAS and PheWAS analysis, termed structured association mapping, which leverages various structures in the omic data. We demonstrate the function of GenAMap via a case study of the Brem and Kruglyak yeast dataset, and then apply it on a comprehensive eQTL analysis of the NIH heterogeneous stock mice dataset and report some interesting findings. GenAMap is available from http://sailing.cs.cmu.edu/genamap.

Achieving Cost Reduction Through Data Analytics.

Science.gov (United States)

Rocchio, Betty Jo

2016-10-01

The reimbursement structure of the US health care system is shifting from a volume-based system to a value-based system. Adopting a comprehensive data analytics platform has become important to health care facilities, in part to navigate this shift. Hospitals generate plenty of data, but actionable analytics are necessary to help personnel interpret and apply data to improve practice. Perioperative services is an important revenue-generating department for hospitals, and each perioperative service line requires a tailored approach to be successful in managing outcomes and controlling costs. Perioperative leaders need to prepare to use data analytics to reduce variation in supplies, labor, and overhead. Mercy, based in Chesterfield, Missouri, adopted a perioperative dashboard that helped perioperative leaders collaborate with surgeons and perioperative staff members to organize and analyze health care data, which ultimately resulted in significant cost savings. Copyright © 2016 AORN, Inc. Published by Elsevier Inc. All rights reserved.

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

International Nuclear Information System (INIS)

Schwantes, J.M.; Pellegrini, K.L.; Marsden, Oliva

2017-01-01

The Nuclear Forensics International Technical Working Group (ITWG) recently completed its fourth Collaborative Materials Exercise (CMX-4) in the 21 year history of the Group. This was also the largest materials exercise to date, with participating laboratories from 16 countries or international organizations. Exercise samples (including three separate samples of low enriched uranium oxide) were shipped as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. In all, over 30 analytical techniques were applied to characterize exercise materials, for which ten of those techniques were applied to ITWG exercises for the first time. An objective review of the state of practice and emerging application of analytical techniques of nuclear forensic analysis based upon the outcome of this most recent exercise is provided. (author)

State of practice and emerging application of analytical techniques of nuclear forensic analysis: highlights from the 4th Collaborative Materials Exercise of the Nuclear Forensics International Technical Working Group (ITWG)

International Nuclear Information System (INIS)

Schwantes, Jon M.; Marsden, Oliva; Pellegrini, Kristi L.

2016-01-01

The Nuclear Forensics International Technical Working Group (ITWG) recently completed its fourth Collaborative Materials Exercise (CMX-4) in the 21 year history of the Group. This was also the largest materials exercise to date, with participating laboratories from 16 countries or international organizations. Moreover, exercise samples (including three separate samples of low enriched uranium oxide) were shipped as part of an illicit trafficking scenario, for which each laboratory was asked to conduct nuclear forensic analyses in support of a fictitious criminal investigation. In all, over 30 analytical techniques were applied to characterize exercise materials, for which ten of those techniques were applied to ITWG exercises for the first time. We performed an objective review of the state of practice and emerging application of analytical techniques of nuclear forensic analysis based upon the outcome of this most recent exercise is provided.

Collaborative, Nondestructive Analysis of Contaminated Soil

Energy Technology Data Exchange (ETDEWEB)

Knight, K. B. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Dai, Z. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Davidson, L. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Eppich, G. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Lindvall, R. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Parsons-Davis, T. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Ramon, C. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Roberts, S. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Sharp, M. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Turin, H. J. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); LaMont, S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States); Zidi, T. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Belamri, M. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Bounatiro, S. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Benbouzid, S. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Fellouh, A. S. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Idir, T. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Larbah, Y. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Moulay, M. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Noureddine, A. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France); Rahal, B. [Commissariat a l' Energie Atomique (COMENA), Gif-sur-Yvette (France)

2017-12-14

This report summarizes a joint nondestructive analysis exercise that LLNL, LANL, and COMENA discussed through a collaborative meeting in July 2017. This work was performed as one part of a collaboration with Algeria under Action Sheet 7: “Technical Cooperation and Assistance in Nuclear Forensics”. The primary intent of this exercise was for US and Algerian participants to jointly share results of nondestructive analyses (NDA) of a contaminated soil sample provided by the Algerians and to discuss key observations and analytical approaches. While the two samples were analyzed blind at LLNL and LANL, the soil samples were revealed after the exercise to have a common origin, and to have originated as an IAEA soil sample (IAEA-326, Bojanowski et al., 2001) provided to COMENA as part of a previous exercise. Comparative analysis revealed common findings between the laboratories, and also emphasized the need for standardized operating procedures to improve inter-comparability and confidence in conclusions. Recommended handling practices in the presence of sample heterogeneities were also discussed. This exercise provided an opportunity to demonstrate nuclear forensics analytical capabilities at COMENA, LANL, and LLNL, and identified areas that could benefit from future technical exchanges. Plans were made for a follow-on joint exercise in 2018, involving destructive analyses of the CUP-2 uranium ore concentrate standard.

Getting from A to B to C-ollaborative Innovative Design Utopia at the Museum?

DEFF Research Database (Denmark)

Rørbæk, Anne

The paper focuses on boundary crossing collaboration for developing digital communication technology as a means to innovate the museum experience. A qualitative longitudinal case study of the collaboration between an art museum and a digital design company in Denmark is presented. Diversity...... is conceptualized as key in the process under study, as the promoter of creative and innovative outcomes. It is argued that the acceptance of and dialogue between contrasting positions has an essential role in extending the scope of group creativity. To show this, a cartographic micro-analytical approach called...... a ‘temporal positional map’ is developed. In this analytical framework, the focus is not on persons and outcomes as such, but on the lives of positions. It thereby serves as a tool to get a deeper understanding of some of the magical complexity of the role of diversity in collaborative processes. The paper...

Giving raw data a chance to talk: a demonstration of exploratory visual analytics with a pediatric research database using Microsoft Live Labs Pivot to promote cohort discovery, research, and quality assessment.

Science.gov (United States)

Viangteeravat, Teeradache; Nagisetty, Naga Satya V Rao

2014-01-01

Secondary use of large and open data sets provides researchers with an opportunity to address high-impact questions that would otherwise be prohibitively expensive and time consuming to study. Despite the availability of data, generating hypotheses from huge data sets is often challenging, and the lack of complex analysis of data might lead to weak hypotheses. To overcome these issues and to assist researchers in building hypotheses from raw data, we are working on a visual and analytical platform called PRD Pivot. PRD Pivot is a de-identified pediatric research database designed to make secondary use of rich data sources, such as the electronic health record (EHR). The development of visual analytics using Microsoft Live Labs Pivot makes the process of data elaboration, information gathering, knowledge generation, and complex information exploration transparent to tool users and provides researchers with the ability to sort and filter by various criteria, which can lead to strong, novel hypotheses.

Interinstitutional collaboration for end-user bioinformatics training: Cytoscape as a case study

Directory of Open Access Journals (Sweden)

Marci D. Brandenburg, MS, MSI

2017-04-01

Conclusions: This collaboration furthered the U-M bioinformationist’s role in the field as an expert in Cytoscape instruction, while also establishing the CWML as a leader in providing support for analyzing and visualizing molecular data at Yale University. The authors found this collaboration to be a successful way for librarians to fill end-user training gaps in rapidly changing fields such as bioinformatics.

Situational Awareness Support to Enhance Teamwork in Collaborative Environments

NARCIS (Netherlands)

Kulyk, Olga Anatoliyivna; van der Veer, Gerrit C.; van Dijk, Elisabeth M.A.G.; Jorge, J

2008-01-01

Modern collaborative environments often provide an overwhelming amount of visual information on multiple displays. The multitude of personal and shared interaction devices leads to lack of awareness of team members on ongoing activities, and awareness of who is in control of shared artefacts. This

SOMFlow: Guided Exploratory Cluster Analysis with Self-Organizing Maps and Analytic Provenance.

Science.gov (United States)

Sacha, Dominik; Kraus, Matthias; Bernard, Jurgen; Behrisch, Michael; Schreck, Tobias; Asano, Yuki; Keim, Daniel A

2018-01-01

Clustering is a core building block for data analysis, aiming to extract otherwise hidden structures and relations from raw datasets, such as particular groups that can be effectively related, compared, and interpreted. A plethora of visual-interactive cluster analysis techniques has been proposed to date, however, arriving at useful clusterings often requires several rounds of user interactions to fine-tune the data preprocessing and algorithms. We present a multi-stage Visual Analytics (VA) approach for iterative cluster refinement together with an implementation (SOMFlow) that uses Self-Organizing Maps (SOM) to analyze time series data. It supports exploration by offering the analyst a visual platform to analyze intermediate results, adapt the underlying computations, iteratively partition the data, and to reflect previous analytical activities. The history of previous decisions is explicitly visualized within a flow graph, allowing to compare earlier cluster refinements and to explore relations. We further leverage quality and interestingness measures to guide the analyst in the discovery of useful patterns, relations, and data partitions. We conducted two pair analytics experiments together with a subject matter expert in speech intonation research to demonstrate that the approach is effective for interactive data analysis, supporting enhanced understanding of clustering results as well as the interactive process itself.

Remote Online Visualization Environment for Researchers, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Many scientists have the common need of visualizing data in a collaborative and interactive manner. In a modern environment, these data are often stored across a...

Final Report "CoDeveloper: A Secure Web-Invocable Collaborative Software Development Tool"

Energy Technology Data Exchange (ETDEWEB)

Svetlana Shasharina

2005-11-27

Modern scientific simulations generate large datasets at remote sites with appropriate resources (supercomputers and clusters). Bringing these large datasets to the computers of all members of a distributed team of collaborators is often impractical or even impossible: there might not be enough bandwidth, storage capacity or appropriate data analysis and visualization tools locally available. To address the need to access remote data, avoid heavy Internet traffic and unnecessary data replication, Tech-X Corporation developed a tool, which allows running remote data visualization collaboratively and sharing the visualization objects as they get generated. The size of these objects is typically much smaller than the size of the original data. For marketing reasons, we renamed the product CoReViz. The detailed information on this product can be found at http://www.txcorp.com/products/CoReViz/. We installed and tested this tool at multiple machines at Tech-X and on seaborg at NERSC. In what follows, we give a detailed description of this tool.

Delving into Teacher Collaboration: Untangling Problems and Solutions for Leadership

Science.gov (United States)

Gates, Gordon; Robinson, Sharon

2009-01-01

This article offers description and interpretation for understanding the exercise of leadership in teacher collaboration. Data gathered in two urban high schools through observations and interviews were coded and categorized following Miles and Huberman's modified analytic induction technique. The analysis contributes to emerging theory on…

Model-based Engineering for the Integration of Manufacturing Systems with Advanced Analytics

OpenAIRE

Lechevalier , David; Narayanan , Anantha; Rachuri , Sudarsan; Foufou , Sebti; Lee , Y Tina

2016-01-01

Part 3: Interoperability and Systems Integration; International audience; To employ data analytics effectively and efficiently on manufacturing systems, engineers and data scientists need to collaborate closely to bring their domain knowledge together. In this paper, we introduce a domain-specific modeling approach to integrate a manufacturing system model with advanced analytics, in particular neural networks, to model predictions. Our approach combines a set of meta-models and transformatio...

VIGOR: Interactive Visual Exploration of Graph Query Results.

Science.gov (United States)

Pienta, Robert; Hohman, Fred; Endert, Alex; Tamersoy, Acar; Roundy, Kevin; Gates, Chris; Navathe, Shamkant; Chau, Duen Horng

2018-01-01

Finding patterns in graphs has become a vital challenge in many domains from biological systems, network security, to finance (e.g., finding money laundering rings of bankers and business owners). While there is significant interest in graph databases and querying techniques, less research has focused on helping analysts make sense of underlying patterns within a group of subgraph results. Visualizing graph query results is challenging, requiring effective summarization of a large number of subgraphs, each having potentially shared node-values, rich node features, and flexible structure across queries. We present VIGOR, a novel interactive visual analytics system, for exploring and making sense of query results. VIGOR uses multiple coordinated views, leveraging different data representations and organizations to streamline analysts sensemaking process. VIGOR contributes: (1) an exemplar-based interaction technique, where an analyst starts with a specific result and relaxes constraints to find other similar results or starts with only the structure (i.e., without node value constraints), and adds constraints to narrow in on specific results; and (2) a novel feature-aware subgraph result summarization. Through a collaboration with Symantec, we demonstrate how VIGOR helps tackle real-world problems through the discovery of security blindspots in a cybersecurity dataset with over 11,000 incidents. We also evaluate VIGOR with a within-subjects study, demonstrating VIGOR's ease of use over a leading graph database management system, and its ability to help analysts understand their results at higher speed and make fewer errors.

Which energy mix for the UK (United Kingdom)? An evolutive descriptive mapping with the integrated GAIA (graphical analysis for interactive aid)–AHP (analytic hierarchy process) visualization tool

International Nuclear Information System (INIS)

Ishizaka, Alessio; Siraj, Sajid; Nemery, Philippe

2016-01-01

Although Multi-Criteria Decision Making methods have been extensively used in energy planning, their descriptive use has been rarely considered. In this paper, we add an evolutionary description phase as an extension to the AHP (analytic hierarchy process) method that helps policy makers to gain insights into their decision problems. The proposed extension has been implemented in an open-source software that allows the users to visualize the difference of opinions within a decision process, and also the evolution of preferences over time. The method was tested in a two-phase experiment to understand the evolution of opinions on energy sources. Participants were asked to provide their preferences for different energy sources for the next twenty years for the United Kingdom. They were first asked to compare the options intuitively without using any structured approach, and then were given three months to compare the same set of options after collecting detailed information on the technical, economic, environmental and social impacts created by each of the selected energy sources. The proposed visualization method allow us to quickly discover the preference directions, and also the changes in their preferences from first to second phase. The proposed tool can help policy makers in better understanding of the energy planning problems that will lead us towards better planning and decisions in the energy sector. - Highlights: • We introduce a descriptive visual analysis tool for the analytic hierarchy process. • The method has been implemented as an open-source preference elicitation tool. • We analyse user preferences in the energy sector using this method. • The tool also provides a way to visualize temporal preferences changes. • The main negative temporal shift in the ranking was found for the nuclear energy.

Visualizing water

Science.gov (United States)

Baart, F.; van Gils, A.; Hagenaars, G.; Donchyts, G.; Eisemann, E.; van Velzen, J. W.

2016-12-01

A compelling visualization is captivating, beautiful and narrative. Here we show how melding the skills of computer graphics, art, statistics, and environmental modeling can be used to generate innovative, attractive and very informative visualizations. We focus on the topic of visualizing forecasts and measurements of water (water level, waves, currents, density, and salinity). For the field of computer graphics and arts, water is an important topic because it occurs in many natural scenes. For environmental modeling and statistics, water is an important topic because the water is essential for transport, a healthy environment, fruitful agriculture, and a safe environment.The different disciplines take different approaches to visualizing water. In computer graphics, one focusses on creating water as realistic looking as possible. The focus on realistic perception (versus the focus on the physical balance pursued by environmental scientists) resulted in fascinating renderings, as seen in recent games and movies. Visualization techniques for statistical results have benefited from the advancement in design and journalism, resulting in enthralling infographics. The field of environmental modeling has absorbed advances in contemporary cartography as seen in the latest interactive data-driven maps. We systematically review the design emerging types of water visualizations. The examples that we analyze range from dynamically animated forecasts, interactive paintings, infographics, modern cartography to web-based photorealistic rendering. By characterizing the intended audience, the design choices, the scales (e.g. time, space), and the explorability we provide a set of guidelines and genres. The unique contributions of the different fields show how the innovations in the current state of the art of water visualization have benefited from inter-disciplinary collaborations.

Data visualization of temporal ozone pollution between urban and ...

African Journals Online (AJOL)

... this study was conducted with the aim to assess and visualize the occurrence of potential Ozone pollution severity of two chosen locations in Selangor, Malaysia: Shah Alam (urban) and Banting (sub-urban). Data visualization analytics were employed using Ozone exceedances and Principal Component Analysis (PCA).

Collaboration and E-collaboration

DEFF Research Database (Denmark)

Razmerita, Liana; Kirchner, Kathrin

2015-01-01

Understanding student’s perception of collaboration and how collaboration is supported by ICT is important for its efficient use in the classroom. This article aims to investigate how students perceive collaboration and how they use new technologies in collaborative group work. Furthermore......, it tries to measure the impact of technology on students’ satisfaction with collaboration outcomes. In particular, the study aims to address the following research questions: Which demographic information (e.g. gender and place of origin) is significant for collaboration and ecollaboration? and Which...... are the perceived factors that influence the students’ group performance? The findings of this study emphasize that there are gender and cultural differences with respect to the perception of e-collaboration. Furthermore, the article summarizes in a model the most significant factors influencing group performance....

Realistic terrain visualization based on 3D virtual world technology

Science.gov (United States)

Huang, Fengru; Lin, Hui; Chen, Bin; Xiao, Cai

2010-11-01

The rapid advances in information technologies, e.g., network, graphics processing, and virtual world, have provided challenges and opportunities for new capabilities in information systems, Internet applications, and virtual geographic environments, especially geographic visualization and collaboration. In order to achieve meaningful geographic capabilities, we need to explore and understand how these technologies can be used to construct virtual geographic environments to help to engage geographic research. The generation of three-dimensional (3D) terrain plays an important part in geographical visualization, computer simulation, and virtual geographic environment applications. The paper introduces concepts and technologies of virtual worlds and virtual geographic environments, explores integration of realistic terrain and other geographic objects and phenomena of natural geographic environment based on SL/OpenSim virtual world technologies. Realistic 3D terrain visualization is a foundation of construction of a mirror world or a sand box model of the earth landscape and geographic environment. The capabilities of interaction and collaboration on geographic information are discussed as well. Further virtual geographic applications can be developed based on the foundation work of realistic terrain visualization in virtual environments.

Improving collaboration between primary care research networks using Access Grid technology

Directory of Open Access Journals (Sweden)

Zsolt Nagykaldi

2008-05-01

Full Text Available Access Grid (AG is an Internet2-driven, high performance audio_visual conferencing technology used worldwide by academic and government organisations to enhance communication, human interaction and group collaboration. AG technology is particularly promising for improving academic multi-centre research collaborations. This manuscript describes how the AG technology was utilised by the electronic Primary Care Research Network (ePCRN that is part of the National Institutes of Health (NIH Roadmap initiative to improve primary care research and collaboration among practice- based research networks (PBRNs in the USA. It discusses the design, installation and use of AG implementations, potential future applications, barriers to adoption, and suggested solutions.

Semantic Enrichment of Movement Behavior with Foursquare--A Visual Analytics Approach.

Science.gov (United States)

Krueger, Robert; Thom, Dennis; Ertl, Thomas

2015-08-01

In recent years, many approaches have been developed that efficiently and effectively visualize movement data, e.g., by providing suitable aggregation strategies to reduce visual clutter. Analysts can use them to identify distinct movement patterns, such as trajectories with similar direction, form, length, and speed. However, less effort has been spent on finding the semantics behind movements, i.e. why somebody or something is moving. This can be of great value for different applications, such as product usage and consumer analysis, to better understand urban dynamics, and to improve situational awareness. Unfortunately, semantic information often gets lost when data is recorded. Thus, we suggest to enrich trajectory data with POI information using social media services and show how semantic insights can be gained. Furthermore, we show how to handle semantic uncertainties in time and space, which result from noisy, unprecise, and missing data, by introducing a POI decision model in combination with highly interactive visualizations. Finally, we evaluate our approach with two case studies on a large electric scooter data set and test our model on data with known ground truth.

Towards Sensorial Approaches to Visual Research with Racially Diverse Young Men

Directory of Open Access Journals (Sweden)

Emmanuel Tabi

2018-03-01

Full Text Available This is a collaborative ethnographic research project that highlights the artistic, literary contributions of racially diverse young men. It uses Critical Race Theory to question conventional, Eurocentric educational approaches that historically and currently continue to suppress various socially and culturally learned modes of communication. This article presents two research projects in urban and suburban formal and informal educational institutions to highlight multimodal literary approaches. The first project is an amalgamation of two critical, ethnographic case studies that explores how racially diverse young men express their literacy through rap and spoken word poetry. The second project uses ethnographic methods to observe racially diverse young men’s production of films and photographs in high school, community centers, and art gallery spaces. This study uses visual methods coupled with affect and sensory-laden approaches to collect data and conduct an analysis. The article reflects on conversations surrounding young men, particularly racialized young men, their relationship with literacy, and how these conversations are founded on their failure and deficit language about their literacy repertoires. We believe that such research is closely tied with other social justice themes and modes of inquiry. This article steers away from the ways racialized young men do not use literacy, and focuses instead on the ways that they do use literacy. Their literacy practices are predominantly visual in nature, frequently accompanied by other modes such as words and moving images. Fitting within the scope of the special issue on social justice and visual methods, we argue for a greater acknowledgement and analytical gaze on sensory and affective nuances within visual research. This approach adds texture and volume to interpreting racialized young men’s narratives. Interrogating their visuals and talking through their narratives that have agentive

Interactive visual exploration and analysis of origin-destination data

Science.gov (United States)

Ding, Linfang; Meng, Liqiu; Yang, Jian; Krisp, Jukka M.

2018-05-01

In this paper, we propose a visual analytics approach for the exploration of spatiotemporal interaction patterns of massive origin-destination data. Firstly, we visually query the movement database for data at certain time windows. Secondly, we conduct interactive clustering to allow the users to select input variables/features (e.g., origins, destinations, distance, and duration) and to adjust clustering parameters (e.g. distance threshold). The agglomerative hierarchical clustering method is applied for the multivariate clustering of the origin-destination data. Thirdly, we design a parallel coordinates plot for visualizing the precomputed clusters and for further exploration of interesting clusters. Finally, we propose a gradient line rendering technique to show the spatial and directional distribution of origin-destination clusters on a map view. We implement the visual analytics approach in a web-based interactive environment and apply it to real-world floating car data from Shanghai. The experiment results show the origin/destination hotspots and their spatial interaction patterns. They also demonstrate the effectiveness of our proposed approach.

Shaded computer graphic techniques for visualizing and interpreting analytic fluid flow models

Science.gov (United States)

Parke, F. I.

1981-01-01

Mathematical models which predict the behavior of fluid flow in different experiments are simulated using digital computers. The simulations predict values of parameters of the fluid flow (pressure, temperature and velocity vector) at many points in the fluid. Visualization of the spatial variation in the value of these parameters is important to comprehend and check the data generated, to identify the regions of interest in the flow, and for effectively communicating information about the flow to others. The state of the art imaging techniques developed in the field of three dimensional shaded computer graphics is applied to visualization of fluid flow. Use of an imaging technique known as 'SCAN' for visualizing fluid flow, is studied and the results are presented.

Visual communication in the psychoanalytic situation.

Science.gov (United States)

Kanzer, M

1980-01-01

The relationship between verbal and visual aspects of the analytic proceedings shows them blended integrally in the experiences of both patient and analyst and in contributing to the insights derived during the treatment. Areas in which the admixture of the verbal and visual occur are delineated. Awareness of the visual aspects gives substance to the operations of empathy, intuition, acting out, working through, etc. Some typical features of visual 'language" are noted and related to the analytic situation. As such they can be translated with the use of logic and consciousness on the analyst's part, not mere random eruptions of intuition. The original significance of dreams as a royal road to the unconscious is confirmed-but we also find in them insights to be derived with higher mental processes. Finally, dyadic aspects of the formation and aims of dreams during analysis are pointed out, with important implications for the analyst's own self-supervision of his techniques and 'real personality" and their effects upon the patient. how remarkable that Dora's dreams, all too belatedly teaching Freud about their transference implications, still have so much more to communicate that derives from his capacity to record faithfully observations he was not yet ready to explain.

Many-objective optimization and visual analytics reveal key trade-offs for London's water supply

Science.gov (United States)

Matrosov, Evgenii S.; Huskova, Ivana; Kasprzyk, Joseph R.; Harou, Julien J.; Lambert, Chris; Reed, Patrick M.

2015-12-01

In this study, we link a water resource management simulator to multi-objective search to reveal the key trade-offs inherent in planning a real-world water resource system. We consider new supplies and demand management (conservation) options while seeking to elucidate the trade-offs between the best portfolios of schemes to satisfy projected water demands. Alternative system designs are evaluated using performance measures that minimize capital and operating costs and energy use while maximizing resilience, engineering and environmental metrics, subject to supply reliability constraints. Our analysis shows many-objective evolutionary optimization coupled with state-of-the art visual analytics can help planners discover more diverse water supply system designs and better understand their inherent trade-offs. The approach is used to explore future water supply options for the Thames water resource system (including London's water supply). New supply options include a new reservoir, water transfers, artificial recharge, wastewater reuse and brackish groundwater desalination. Demand management options include leakage reduction, compulsory metering and seasonal tariffs. The Thames system's Pareto approximate portfolios cluster into distinct groups of water supply options; for example implementing a pipe refurbishment program leads to higher capital costs but greater reliability. This study highlights that traditional least-cost reliability constrained design of water supply systems masks asset combinations whose benefits only become apparent when more planning objectives are considered.

GeoCAM: A geovisual analytics workspace to contextualize and interpret statements about movement

Directory of Open Access Journals (Sweden)

Anuj Jaiswal

2011-12-01

Full Text Available This article focuses on integrating computational and visual methods in a system that supports analysts to identify, extract, map, and relate linguistic accounts of movement. We address two objectives: (1 build the conceptual, theoretical, and empirical framework needed to represent and interpret human-generated directions; and (2 design and implement a geovisual analytics workspace for direction document analysis. We have built a set of geo-enabled, computational methods to identify documents containing movement statements, and a visual analytics environment that uses natural language processing methods iteratively with geographic database support to extract, interpret, and map geographic movement references in context. Additionally, analysts can provide feedback to improve computational results. To demonstrate the value of this integrative approach, we have realized a proof-of-concept implementation focusing on identifying and processing documents that contain human-generated route directions. Using our visual analytic interface, an analyst can explore the results, provide feedback to improve those results, pose queries against a database of route directions, and interactively represent the route on a map.

BrainBrowser: distributed, web-based neurological data visualization

Directory of Open Access Journals (Sweden)

Tarek eSherif

2015-01-01

Full Text Available Recent years have seen massive, distributed datasets become the norm in neuroimaging research, and the methodologies used analyze them have, in response, become more collaborative and exploratory. Tools and infrastructure are continuously being developed and deployed to facilitate research in this context: grid computation platforms to process the data, distributed data stores to house and share them, high-speed networks to move them around and collaborative, often web-based, platforms to provide access to and sometimes manage the entire system. BrainBrowser is a lightweight, high-performance JavaScript visualization library built to provide easy-to-use, powerful, on-demand visualization of remote datasets in this new research environment. BrainBrowser leverages modern Web technologies, such as WebGL, HTML5 and Web Workers, to visualize 3D surface and volumetric neuroimaging data in any modern web browser without requiring any browser plugins. It is thus trivial to integrate BrainBrowser into any web-based platform. BrainBrowser is simple enough to produce a basic web-based visualization in a few lines of code, while at the same time being robust enough to create full-featured visualization applications. BrainBrowser can dynamically load the data required for a given visualization, so no network bandwidth needs to be waisted on data that will not be used. BrainBrowser's integration into the standardized web platform also allows users to consider using 3D data visualization in novel ways, such as for data distribution, data sharing and dynamic online publications. BrainBrowser is already being used in two major online platforms, CBRAIN and LORIS, and has been used to make the 1TB MACACC dataset openly accessible.

Language and Visual Perception Associations: Meta-Analytic Connectivity Modeling of Brodmann Area 37

Directory of Open Access Journals (Sweden)

Alfredo Ardila

2015-01-01

Full Text Available Background. Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. Objectives. The purpose of this paper was to analyze the connectivity of Brodmann area (BA 37 (posterior, inferior, and temporal/fusiform gyrus in relation to (1 language and (2 visual processing. Methods. Two meta-analyses were initially conducted (first level analysis. The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception. The DataBase of Brainmap was used. Results. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. Conclusion. It was concluded that left BA37 is a common node of two distinct networks—visual recognition (perception and semantic language functions.

Language and visual perception associations: meta-analytic connectivity modeling of Brodmann area 37.

Science.gov (United States)

Ardila, Alfredo; Bernal, Byron; Rosselli, Monica

2015-01-01

Understanding the functions of different brain areas has represented a major endeavor of neurosciences. Historically, brain functions have been associated with specific cortical brain areas; however, modern neuroimaging developments suggest cognitive functions are associated to networks rather than to areas. The purpose of this paper was to analyze the connectivity of Brodmann area (BA) 37 (posterior, inferior, and temporal/fusiform gyrus) in relation to (1) language and (2) visual processing. Two meta-analyses were initially conducted (first level analysis). The first one was intended to assess the language network in which BA37 is involved. The second one was intended to assess the visual perception network. A third meta-analysis (second level analysis) was then performed to assess contrasts and convergence between the two cognitive domains (language and visual perception). The DataBase of Brainmap was used. Our results support the role of BA37 in language but by means of a distinct network from the network that supports its second most important function: visual perception. It was concluded that left BA37 is a common node of two distinct networks-visual recognition (perception) and semantic language functions.

Clinical laboratory analytics: Challenges and promise for an emerging discipline

Directory of Open Access Journals (Sweden)

Brian H Shirts

2015-01-01

Full Text Available The clinical laboratory is a major source of health care data. Increasingly these data are being integrated with other data to inform health system-wide actions meant to improve diagnostic test utilization, service efficiency, and "meaningful use." The Academy of Clinical Laboratory Physicians and Scientists hosted a satellite meeting on clinical laboratory analytics in conjunction with their annual meeting on May 29, 2014 in San Francisco. There were 80 registrants for the clinical laboratory analytics meeting. The meeting featured short presentations on current trends in clinical laboratory analytics and several panel discussions on data science in laboratory medicine, laboratory data and its role in the larger healthcare system, integrating laboratory analytics, and data sharing for collaborative analytics. One main goal of meeting was to have an open forum of leaders that work with the "big data" clinical laboratories produce. This article summarizes the proceedings of the meeting and content discussed.

Visual business ecosystem intelligence: lessons from the field.

Science.gov (United States)

Basole, Rahul C

2014-01-01

Macroscopic insight into business ecosystems is becoming increasingly important. With the emergence of new digital business data, opportunities exist to develop rich, interactive visual-analytics tools. Georgia Institute of Technology researchers have been developing and implementing visual business ecosystem intelligence tools in corporate settings. This article discusses the challenges they faced, the lessons learned, and opportunities for future research.

Visualizing Dynamic Bitcoin Transaction Patterns.

Science.gov (United States)

McGinn, Dan; Birch, David; Akroyd, David; Molina-Solana, Miguel; Guo, Yike; Knottenbelt, William J

2016-06-01

This work presents a systemic top-down visualization of Bitcoin transaction activity to explore dynamically generated patterns of algorithmic behavior. Bitcoin dominates the cryptocurrency markets and presents researchers with a rich source of real-time transactional data. The pseudonymous yet public nature of the data presents opportunities for the discovery of human and algorithmic behavioral patterns of interest to many parties such as financial regulators, protocol designers, and security analysts. However, retaining visual fidelity to the underlying data to retain a fuller understanding of activity within the network remains challenging, particularly in real time. We expose an effective force-directed graph visualization employed in our large-scale data observation facility to accelerate this data exploration and derive useful insight among domain experts and the general public alike. The high-fidelity visualizations demonstrated in this article allowed for collaborative discovery of unexpected high frequency transaction patterns, including automated laundering operations, and the evolution of multiple distinct algorithmic denial of service attacks on the Bitcoin network.

Visualizing Dynamic Bitcoin Transaction Patterns

Science.gov (United States)

McGinn, Dan; Birch, David; Akroyd, David; Molina-Solana, Miguel; Guo, Yike; Knottenbelt, William J.

2016-01-01

Abstract This work presents a systemic top-down visualization of Bitcoin transaction activity to explore dynamically generated patterns of algorithmic behavior. Bitcoin dominates the cryptocurrency markets and presents researchers with a rich source of real-time transactional data. The pseudonymous yet public nature of the data presents opportunities for the discovery of human and algorithmic behavioral patterns of interest to many parties such as financial regulators, protocol designers, and security analysts. However, retaining visual fidelity to the underlying data to retain a fuller understanding of activity within the network remains challenging, particularly in real time. We expose an effective force-directed graph visualization employed in our large-scale data observation facility to accelerate this data exploration and derive useful insight among domain experts and the general public alike. The high-fidelity visualizations demonstrated in this article allowed for collaborative discovery of unexpected high frequency transaction patterns, including automated laundering operations, and the evolution of multiple distinct algorithmic denial of service attacks on the Bitcoin network. PMID:27441715

Interactive data visualization foundations, techniques, and applications

CERN Document Server

Ward, Matthew; Keim, Daniel

2010-01-01

Visualization is the process of representing data, information, and knowledge in a visual form to support the tasks of exploration, confirmation, presentation, and understanding. This book is designed as a textbook for students, researchers, analysts, professionals, and designers of visualization techniques, tools, and systems. It covers the full spectrum of the field, including mathematical and analytical aspects, ranging from its foundations to human visual perception; from coded algorithms for different types of data, information and tasks to the design and evaluation of new visualization techniques. Sample programs are provided as starting points for building one's own visualization tools. Numerous data sets have been made available that highlight different application areas and allow readers to evaluate the strengths and weaknesses of different visualization methods. Exercises, programming projects, and related readings are given for each chapter. The book concludes with an examination of several existin...

Fusion Analytics: A Data Integration System for Public Health and Medical Disaster Response Decision Support

Science.gov (United States)

Passman, Dina B.

2013-01-01

Objective The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decision-making in disasters. Introduction Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing web-based data analysis and visualization tools. Methods Fusion Analytics serves as a one-stop-shop for the web-based data visualizations of multiple real-time data sources within ASPR. The 24-7 web availability makes it an ideal analytic tool for situational awareness and response allowing stakeholders to access the portal from any internet-enabled device without installing any software. The Fusion Analytics data integration system was built using off-the-shelf EBI software. Fusion Analytics leverages the full power of statistical analysis software and delivers reports to users in a secure web-based environment. Fusion Analytics provides an example of how public health staff can develop and deploy a robust public health informatics solution using an off-the shelf product and with limited development funding. It also provides the unique example of a public health information system that combines patient data for traditional disease surveillance with manpower and resource data to provide overall decision support for federal public health and medical disaster response operations. Conclusions We are currently in a unique position within public health. One the one hand, we have been gaining greater and greater access to electronic data of all kinds over the last few years. On the other, we are working in a time of reduced government spending

Collaborative Virtual 3D Environment for Internet-Accessible Physics Experiments

Directory of Open Access Journals (Sweden)

Bettina Scheucher

2009-08-01

Full Text Available Abstract—Immersive 3D worlds have increasingly raised the interest of researchers and practitioners for various learning and training settings over the last decade. These virtual worlds can provide multiple communication channels between users and improve presence and awareness in the learning process. Consequently virtual 3D environments facilitate collaborative learning and training scenarios. In this paper we focus on the integration of internet-accessible physics experiments (iLabs combined with the TEALsim 3D simulation toolkit in Project Wonderland, Sun's toolkit for creating collaborative 3D virtual worlds. Within such a collaborative environment these tools provide the opportunity for teachers and students to work together as avatars as they control actual equipment, visualize physical phenomenon generated by the experiment, and discuss the results. In particular we will outline the steps of integration, future goals, as well as the value of a collaboration space in Wonderland's virtual world.

Developing Visual Literacy: Historical and Manipulated Photography in the Social Studies Classroom

Science.gov (United States)

Cruz, Bárbara C.; Ellerbrock, Cheryl R.

2015-01-01

The importance of visual literacy development is demonstrated using social studies examples from an innovative, collaborative arts program. Discussion of the Visual Thinking Strategies approach, connections to the Common Core State Standards, prompts for higher-order critical thinking, and the application of historical and social science ideas in…

Students and Teachers as Developers of Visual Learning Designs with Augmented Reality for Visual Arts Education

DEFF Research Database (Denmark)

Buhl, Mie

2017-01-01

upon which to discuss the potential for reengineering the traditional role of the teacher/learning designer as the only supplier and the students as the receivers of digital learning designs in higher education. The discussion applies the actor-network theory and socio-material perspectives...... on education in order to enhance the meta-perspective of traditional teacher and student roles.......Abstract This paper reports on a project in which communication and digital media students collaborated with visual arts teacher students and their teacher trainer to develop visual digital designs for learning that involved Augmented Reality (AR) technology. The project exemplified a design...

The Visual Geophysical Exploration Environment: A Multi-dimensional Scientific Visualization

Science.gov (United States)

Pandya, R. E.; Domenico, B.; Murray, D.; Marlino, M. R.

2003-12-01

The Visual Geophysical Exploration Environment (VGEE) is an online learning environment designed to help undergraduate students understand fundamental Earth system science concepts. The guiding principle of the VGEE is the importance of hands-on interaction with scientific visualization and data. The VGEE consists of four elements: 1) an online, inquiry-based curriculum for guiding student exploration; 2) a suite of El Nino-related data sets adapted for student use; 3) a learner-centered interface to a scientific visualization tool; and 4) a set of concept models (interactive tools that help students understand fundamental scientific concepts). There are two key innovations featured in this interactive poster session. One is the integration of concept models and the visualization tool. Concept models are simple, interactive, Java-based illustrations of fundamental physical principles. We developed eight concept models and integrated them into the visualization tool to enable students to probe data. The ability to probe data using a concept model addresses the common problem of transfer: the difficulty students have in applying theoretical knowledge to everyday phenomenon. The other innovation is a visualization environment and data that are discoverable in digital libraries, and installed, configured, and used for investigations over the web. By collaborating with the Integrated Data Viewer developers, we were able to embed a web-launchable visualization tool and access to distributed data sets into the online curricula. The Thematic Real-time Environmental Data Distributed Services (THREDDS) project is working to provide catalogs of datasets that can be used in new VGEE curricula under development. By cataloging this curricula in the Digital Library for Earth System Education (DLESE), learners and educators can discover the data and visualization tool within a framework that guides their use.

Visual teaching and learning in the fields of engineering

Directory of Open Access Journals (Sweden)

Kyvete S. Shatri

2015-11-01

Full Text Available Engineering education today is faced with numerous demands that are closely connected with a globalized economy. One of these requirements is to draw the engineers of the future, who are characterized with: strong analytical skills, creativity, ingenuity, professionalism, intercultural communication and leadership. To achieve this effective teaching methods should be used to facilitate and enhance the learning of students and their performance in general, making them able to cope with market demands of a globalized economy. One of these methods is the visualization as a very important method that increases the learning of students. A visual approach in science and in engineering also increases communication, critical thinking and provides analytical approach to various problems. Therefore, this research is aimed to investigate the effect of the use of visualization in the process of teaching and learning in engineering fields and encourage teachers and students to use visual methods for teaching and learning. The results of this research highlight the positive effect that the use of visualization has in the learning process of students and their overall performance. In addition, innovative teaching methods have a good effect in the improvement of the situation. Visualization motivates students to learn, making them more cooperative and developing their communication skills.

Web-Scale Multidimensional Visualization of Big Spatial Data to Support Earth Sciences—A Case Study with Visualizing Climate Simulation Data

Directory of Open Access Journals (Sweden)

Sizhe Wang

2017-06-01

Full Text Available The world is undergoing rapid changes in its climate, environment, and ecosystems due to increasing population growth, urbanization, and industrialization. Numerical simulation is becoming an important vehicle to enhance the understanding of these changes and their impacts, with regional and global simulation models producing vast amounts of data. Comprehending these multidimensional data and fostering collaborative scientific discovery requires the development of new visualization techniques. In this paper, we present a cyberinfrastructure solution—PolarGlobe—that enables comprehensive analysis and collaboration. PolarGlobe is implemented upon an emerging web graphics library, WebGL, and an open source virtual globe system Cesium, which has the ability to map spatial data onto a virtual Earth. We have also integrated volume rendering techniques, value and spatial filters, and vertical profile visualization to improve rendered images and support a comprehensive exploration of multi-dimensional spatial data. In this study, the climate simulation dataset produced by the extended polar version of the well-known Weather Research and Forecasting Model (WRF is used to test the proposed techniques. PolarGlobe is also easily extendable to enable data visualization for other Earth Science domains, such as oceanography, weather, or geology.

Human Resource Predictive Analytics HRPA For HR Management In Organizations

Directory of Open Access Journals (Sweden)

Sujeet N. Mishra

2015-08-01

Full Text Available Human resource predictive analytics is an evolving application field of analytics for HRM purposes. The purpose of HRM is measuring employee performance and engagement studying workforce collaboration patterns analyzing employee churn and turnover and modelling employee lifetime value. The motive of applying HRPA is to optimize performances and produce better return on investment for organizations through decision making based on data collection HR metrics and predictive models. The paper is divided into three sections to understand the emergence of HR predictive analytics for HRM. Firstly the paper introduces the concept of HRPA. Secondly the paper discusses three aspects of HRPA a Need b Approach amp Application c Impact. Lastly the paper leads to the conclusion on HRPA.

Collaborative efforts in the characterization of stack-collected fly ash

International Nuclear Information System (INIS)

Fisher, G.L.; Prentice, B.A.; Silberman, D.; Ondov, J.M.; Ragaini, R.C.; Bierman, A.H.

1976-01-01

A collaborative study with Lawrence Livermore Laboratory (LLL) has been initiated to characterize the physical and chemical properties of stack-collected fly ash. The expertise of the two laboratories with respect to chemical analysis and particle sizing is complementary and allows for comparison and extension of analytical results not possible with independent analysis

Learning, Learning Analytics, Activity Visualisation and Open learner Model

DEFF Research Database (Denmark)

Bull, Susan; Kickmeier-Rust, Michael; Vatrapu, Ravi

2013-01-01

This paper draws on visualisation approaches in learning analytics, considering how classroom visualisations can come together in practice. We suggest an open learner model in situations where many tools and activity visualisations produce more visual information than can be readily interpreted....

Use of activity logs to improve online collaboration

Directory of Open Access Journals (Sweden)

César Coll Salvador

2018-02-01

Full Text Available This article presents a review of works that center their interest in eLearning platforms and the data mining of participants’ activity. The studies in this research area generate information, through the analysis of such logs and data, that is provided to the students in real time to help them to collaborate and learn through collaboration on the platform. There are studies from different areas of study such as Learning Analytics, Educational Data Mining, Group Awareness Tools or Interaction Analysis Tools. The review takes a double perspective: i to analyze the data extracted from activity logs, their processing, the information generated and the ways to communicate it; and ii to explorer the model and the instruments used to assess how the information provided impact on online collaborative processes and/or the learning. The conclusions emphasize that the models of collaborative learning that justifies the selection of the data extracted from the activity logs, the processing, the information generated and provided to the students and the way of communicating it, are not explicitly stated. In addition, important biases are detected because of not considering the multidimensional nature of the collaborative learning processes. Also, few studies analyze the relations between students' uses of the information provided and the quality of their collaborative processes and learning results. The very few studies that do analyze such relation do not go into depth on the changes in group dynamics caused by information.

Immersive visualization of dynamic CFD model results

International Nuclear Information System (INIS)

Comparato, J.R.; Ringel, K.L.; Heath, D.J.

2004-01-01

With immersive visualization the engineer has the means for vividly understanding problem causes and discovering opportunities to improve design. Software can generate an interactive world in which collaborators experience the results of complex mathematical simulations such as computational fluid dynamic (CFD) modeling. Such software, while providing unique benefits over traditional visualization techniques, presents special development challenges. The visualization of large quantities of data interactively requires both significant computational power and shrewd data management. On the computational front, commodity hardware is outperforming large workstations in graphical quality and frame rates. Also, 64-bit commodity computing shows promise in enabling interactive visualization of large datasets. Initial interactive transient visualization methods and examples are presented, as well as development trends in commodity hardware and clustering. Interactive, immersive visualization relies on relevant data being stored in active memory for fast response to user requests. For large or transient datasets, data management becomes a key issue. Techniques for dynamic data loading and data reduction are presented as means to increase visualization performance. (author)

Towards a Web-Enabled Geovisualization and Analytics Platform for the Energy and Water Nexus

Science.gov (United States)

Sanyal, J.; Chandola, V.; Sorokine, A.; Allen, M.; Berres, A.; Pang, H.; Karthik, R.; Nugent, P.; McManamay, R.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Interactive data analytics are playing an increasingly vital role in the generation of new, critical insights regarding the complex dynamics of the energy/water nexus (EWN) and its interactions with climate variability and change. Integration of impacts, adaptation, and vulnerability (IAV) science with emerging, and increasingly critical, data science capabilities offers a promising potential to meet the needs of the EWN community. To enable the exploration of pertinent research questions, a web-based geospatial visualization platform is being built that integrates a data analysis toolbox with advanced data fusion and data visualization capabilities to create a knowledge discovery framework for the EWN. The system, when fully built out, will offer several geospatial visualization capabilities including statistical visual analytics, clustering, principal-component analysis, dynamic time warping, support uncertainty visualization and the exploration of data provenance, as well as support machine learning discoveries to render diverse types of geospatial data and facilitate interactive analysis. Key components in the system architecture includes NASA's WebWorldWind, the Globus toolkit, postgresql, as well as other custom built software modules.

Visual Input Enhancement and Grammar Learning: A Meta-Analytic Review

Science.gov (United States)

Lee, Sang-Ki; Huang, Hung-Tzu

2008-01-01

Effects of pedagogical interventions with visual input enhancement on grammar learning have been investigated by a number of researchers during the past decade and a half. The present review delineates this research domain via a systematic synthesis of 16 primary studies (comprising 20 unique study samples) retrieved through an exhaustive…

Vroom: designing an augmented environment for remote collaboration in digital cinema production

Science.gov (United States)

Margolis, Todd; Cornish, Tracy

2013-03-01

As media technologies become increasingly affordable, compact and inherently networked, new generations of telecollaborative platforms continue to arise which integrate these new affordances. Virtual reality has been primarily concerned with creating simulations of environments that can transport participants to real or imagined spaces that replace the "real world". Meanwhile Augmented Reality systems have evolved to interleave objects from Virtual Reality environments into the physical landscape. Perhaps now there is a new class of systems that reverse this precept to enhance dynamic media landscapes and immersive physical display environments to enable intuitive data exploration through collaboration. Vroom (Virtual Room) is a next-generation reconfigurable tiled display environment in development at the California Institute for Telecommunications and Information Technology (Calit2) at the University of California, San Diego. Vroom enables freely scalable digital collaboratories, connecting distributed, high-resolution visualization resources for collaborative work in the sciences, engineering and the arts. Vroom transforms a physical space into an immersive media environment with large format interactive display surfaces, video teleconferencing and spatialized audio built on a highspeed optical network backbone. Vroom enables group collaboration for local and remote participants to share knowledge and experiences. Possible applications include: remote learning, command and control, storyboarding, post-production editorial review, high resolution video playback, 3D visualization, screencasting and image, video and multimedia file sharing. To support these various scenarios, Vroom features support for multiple user interfaces (optical tracking, touch UI, gesture interface, etc.), support for directional and spatialized audio, giga-pixel image interactivity, 4K video streaming, 3D visualization and telematic production. This paper explains the design process that

Analytical Solutions for Predicting Underwater Explosion Gas Bubble Behaviour

Science.gov (United States)

2010-11-01

décrit différents modèles analytiques élaborés antérieurement pour prévoir la croissance et l’implosion radiales en champ libre des bulles gazeuses...9.80665 Air pressure (kPa), Pair 101.325 101.325 4.4 Code Development The visualization software IDL was used to develop a code for calculating the...models and assumptions provide better predictions. Using the visualization software IDL the various analytical models and similitude equations, a code

Leadership of Collaborative Innovation in the Public Sector

DEFF Research Database (Denmark)

Hansen, Jesper Rohr; Griggs, Steven

2016-01-01

The organizational phenomenon studied in this chapter is leadership of collaborative innovation. I approach this phenomenon of leadership by exploring the constructionist nature of leadership in a local-government setting. I explain how this perspective on leadership was inspired by a three...... studied and subsequently describe my analytical approach. Next I explain the methodology used and give two empirical examples. Finally I reflect upon how the organizational ethnography deployed has contributed to existing knowledge of collaborative innovation leadership and touch briefly......-year ethnographic study by means of engaged-scholarship ethnography. In particular, I illustrate the implications of using such an ethnography—namely, identifying uncertainty as the main explanation for leadership construction. The chapter is structured as follows. First I present the organizational phenomenon...

Meta-analysis of individual registry results enhances international registry collaboration.

Science.gov (United States)

Paxton, Elizabeth W; Mohaddes, Maziar; Laaksonen, Inari; Lorimer, Michelle; Graves, Stephen E; Malchau, Henrik; Namba, Robert S; Kärrholm, John; Rolfson, Ola; Cafri, Guy

2018-03-28

Background and purpose - Although common in medical research, meta-analysis has not been widely adopted in registry collaborations. A meta-analytic approach in which each registry conducts a standardized analysis on its own data followed by a meta-analysis to calculate a weighted average of the estimates allows collaboration without sharing patient-level data. The value of meta-analysis as an alternative to individual patient data analysis is illustrated in this study by comparing the risk of revision of porous tantalum cups versus other uncemented cups in primary total hip arthroplasties from Sweden, Australia, and a US registry (2003-2015). Patients and methods - For both individual patient data analysis and meta-analysis approaches a Cox proportional hazard model was fit for time to revision, comparing porous tantalum (n = 23,201) with other uncemented cups (n = 128,321). Covariates included age, sex, diagnosis, head size, and stem fixation. In the meta-analysis approach, treatment effect size (i.e., Cox model hazard ratio) was calculated within each registry and a weighted average for the individual registries' estimates was calculated. Results - Patient-level data analysis and meta-analytic approaches yielded the same results with the porous tantalum cups having a higher risk of revision than other uncemented cups (HR (95% CI) 1.6 (1.4-1.7) and HR (95% CI) 1.5 (1.4-1.7), respectively). Adding the US cohort to the meta-analysis led to greater generalizability, increased precision of the treatment effect, and similar findings (HR (95% CI) 1.6 (1.4-1.7)) with increased risk of porous tantalum cups. Interpretation - The meta-analytic technique is a viable option to address privacy, security, and data ownership concerns allowing more expansive registry collaboration, greater generalizability, and increased precision of treatment effects.

Visualization and characterization of users in a citizen science project

Science.gov (United States)

Morais, Alessandra M. M.; Raddick, Jordan; Coelho dos Santos, Rafael D.

2013-05-01

Recent technological advances allowed the creation and use of internet-based systems where many users can collaborate gathering and sharing information for specific or general purposes: social networks, e-commerce review systems, collaborative knowledge systems, etc. Since most of the data collected in these systems is user-generated, understanding of the motivations and general behavior of users is a very important issue. Of particular interest are citizen science projects, where users without scientific training are asked for collaboration labeling and classifying information (either automatically by giving away idle computer time or manually by actually seeing data and providing information about it). Understanding behavior of users of those types of data collection systems may help increase the involvement of the users, categorize users accordingly to different parameters, facilitate their collaboration with the systems, design better user interfaces, and allow better planning and deployment of similar projects and systems. Behavior of those users could be estimated through analysis of their collaboration track: registers of which user did what and when can be easily and unobtrusively collected in several different ways, the simplest being a log of activities. In this paper we present some results on the visualization and characterization of almost 150.000 users with more than 80.000.000 collaborations with a citizen science project - Galaxy Zoo I, which asked users to classify galaxies' images. Basic visualization techniques are not applicable due to the number of users, so techniques to characterize users' behavior based on feature extraction and clustering are used.

Image Recommendation Algorithm Using Feature-Based Collaborative Filtering

Science.gov (United States)

Kim, Deok-Hwan

As the multimedia contents market continues its rapid expansion, the amount of image contents used in mobile phone services, digital libraries, and catalog service is increasing remarkably. In spite of this rapid growth, users experience high levels of frustration when searching for the desired image. Even though new images are profitable to the service providers, traditional collaborative filtering methods cannot recommend them. To solve this problem, in this paper, we propose feature-based collaborative filtering (FBCF) method to reflect the user's most recent preference by representing his purchase sequence in the visual feature space. The proposed approach represents the images that have been purchased in the past as the feature clusters in the multi-dimensional feature space and then selects neighbors by using an inter-cluster distance function between their feature clusters. Various experiments using real image data demonstrate that the proposed approach provides a higher quality recommendation and better performance than do typical collaborative filtering and content-based filtering techniques.

Analytics Platform for ATLAS Computing Services

CERN Document Server

Vukotic, Ilija; The ATLAS collaboration; Bryant, Lincoln

2016-01-01

Big Data technologies have proven to be very useful for storage, processing and visualization of derived metrics associated with ATLAS distributed computing (ADC) services. Log file data and database records, and metadata from a diversity of systems have been aggregated and indexed to create an analytics platform for ATLAS ADC operations analysis. Dashboards, wide area data access cost metrics, user analysis patterns, and resource utilization efficiency charts are produced flexibly through queries against a powerful analytics cluster. Here we explore whether these techniques and analytics ecosystem can be applied to add new modes of open, quick, and pervasive access to ATLAS event data so as to simplify access and broaden the reach of ATLAS public data to new communities of users. An ability to efficiently store, filter, search and deliver ATLAS data at the event and/or sub-event level in a widely supported format would enable or significantly simplify usage of machine learning tools like Spark, Jupyter, R, S...

Product design planning with the analytic hierarchy process in inter-organizational networks

NARCIS (Netherlands)

Hummel, J. Marjan; van Rossum, Wouter; Verkerke, Gijsbertus Jacob; Rakhorst, Gerhard

2002-01-01

In the second half of inter–organizational product development, the new product is likely to face significant design changes. Our study focused on the adequacy of the analytic hierarchy process (AHP) to support the collaborative partners to steer and align the accompanying design activities. It

Product design planning with the analytic hierarchy process in inter-organizational networks

NARCIS (Netherlands)

Hummel, J.M.; van Rossum, Wouter; Verkerke, Bart; Rakhorst, G

2002-01-01

In the second half of inter-organizational product developments the new product is likely to face significant design changes. Our study focused on the adequacy of the analytic hierarchy process (AHP) to support the collaborative partners to steer and align the accompanying design activities. It

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

Science.gov (United States)

Saqr, Mohammed; Fors, Uno; Tedre, Matti

2018-02-06

Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information

Visual Communication in Transition: Designing for New Media Literacies and Visual Culture Art Education across Activities and Settings

Science.gov (United States)

Zuiker, Steven J.

2014-01-01

As an example of design-based research, this case study describes and analyses the enactment of a collaborative drawing and animation studio in a Singapore secondary school art classroom. The design embodies principles of visual culture art education and new media literacies in order to organize transitions in the settings of participation and…

The Preference of Visualization in Teaching and Learning Absolute Value

Science.gov (United States)

Konyalioglu, Alper Cihan; Aksu, Zeki; Senel, Esma Ozge

2012-01-01

Visualization is mostly despised although it complements and--sometimes--guides the analytical process. This study mainly investigates teachers' preferences concerning the use of the visualization method and determines the extent to which they encourage their students to make use of it within the problem-solving process. This study was conducted…

Determination of some individual chlorobiphenyls in eel-fat with capillary gaschromatography: collaborative study

NARCIS (Netherlands)

Tuinstra, L.G.M.T.; Roos, A.H.; Werdmuller, G.A.

1984-01-01

A method for the determination of six individual chlorobiphenyls in eel-fat, based on saponification of the sample and determination with capillary gas chromatography, was studied collaboratively. Eleven laboratories submitted analytical results in duplo of six individual chlorbiphenyls on two

Collaboration spotting for dental science.

Science.gov (United States)

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-10-06

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to Dental Science. In order to create a Sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro--maxillo--facial critical size defects, namely the use of Porous HydroxyApatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex--vivo of Mesenchymal Stem Cells. We produced the Sociograms for these technologies and the resulting maps are now accessible on--line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state--of--the--art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used for Dental Science and produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped

Collaboration Spotting for oral medicine.

Science.gov (United States)

Leonardi, E; Agocs, A; Fragkiskos, S; Kasfikis, N; Le Goff, J M; Cristalli, M P; Luzzi, V; Polimeni, A

2014-09-01

The goal of the Collaboration Spotting project is to create an automatic system to collect information about publications and patents related to a given technology, to identify the key players involved, and to highlight collaborations and related technologies. The collected information can be visualized in a web browser as interactive graphical maps showing in an intuitive way the players and their collaborations (Sociogram) and the relations among the technologies (Technogram). We propose to use the system to study technologies related to oral medicine. In order to create a sociogram, we create a logical filter based on a set of keywords related to the technology under study. This filter is used to extract a list of publications from the Web of Science™ database. The list is validated by an expert in the technology and sent to CERN where it is inserted in the Collaboration Spotting database. Here, an automatic software system uses the data to generate the final maps. We studied a set of recent technologies related to bone regeneration procedures of oro-maxillo-facial critical size defects, namely the use of porous hydroxyapatite (HA) as a bone substitute alone (bone graft) or as a tridimensional support (scaffold) for insemination and differentiation ex vivo of mesenchymal stem cells. We produced the sociograms for these technologies and the resulting maps are now accessible on-line. The Collaboration Spotting system allows the automatic creation of interactive maps to show the current and historical state of research on a specific technology. These maps are an ideal tool both for researchers who want to assess the state-of-the-art in a given technology, and for research organizations who want to evaluate their contribution to the technological development in a given field. We demonstrated that the system can be used in oral medicine as is produced the maps for an initial set of technologies in this field. We now plan to enlarge the set of mapped technologies in

Assessing Adult Learning Preferences Using the Analytic Hierarchy Process.

Science.gov (United States)

Lee, Doris; McCool, John; Napieralski, Laura

2000-01-01

Graduate students (n=134) used the analytic hierarchy process, which weights expressed preferences, to rate four learning activities: lectures, discussion/reflection, individual projects, and group projects. Their preferences for discussion/reflection and individual projects were independent of auditory, visual, and kinesthetic learning styles.…

Forging a link between mentoring and collaboration: a new training model for implementation science.

Science.gov (United States)

Luke, Douglas A; Baumann, Ana A; Carothers, Bobbi J; Landsverk, John; Proctor, Enola K

2016-10-13

Training investigators for the rapidly developing field of implementation science requires both mentoring and scientific collaboration. Using social network descriptive analyses, visualization, and modeling, this paper presents results of an evaluation of the mentoring and collaborations fostered over time through the National Institute of Mental Health (NIMH) supported by Implementation Research Institute (IRI). Data were comprised of IRI participant self-reported collaborations and mentoring relationships, measured in three annual surveys from 2012 to 2014. Network descriptive statistics, visualizations, and network statistical modeling were conducted to examine patterns of mentoring and collaboration among IRI participants and to model the relationship between mentoring and subsequent collaboration. Findings suggest that IRI is successful in forming mentoring relationships among its participants, and that these mentoring relationships are related to future scientific collaborations. Exponential random graph network models demonstrated that mentoring received in 2012 was positively and significantly related to the likelihood of having a scientific collaboration 2 years later in 2014 (p = 0.001). More specifically, mentoring was significantly related to future collaborations focusing on new research (p = 0.009), grant submissions (p = 0.003), and publications (p = 0.017). Predictions based on the network model suggest that for every additional mentoring relationships established in 2012, the likelihood of a scientific collaboration 2 years later is increased by almost 7 %. These results support the importance of mentoring in implementation science specifically and team science more generally. Mentoring relationships were established quickly and early by the IRI core faculty. IRI fellows reported increasing scientific collaboration of all types over time, including starting new research, submitting new grants, presenting research results, and

Large Data Visualization with Open-Source Tools

CERN Multimedia

CERN. Geneva

2015-01-01

Visualization and post-processing of large data have become increasingly challenging and require more and more tools to support the diversity of data to process. In this seminar, we will present a suite of open-source tools supported and developed by Kitware to perform large-scale data visualization and analysis. In particular, we will present ParaView, an open-source tool for parallel visualization of massive datasets, the Visualization Toolkit (VTK), an open-source toolkit for scientific visualization, and Tangelohub, a suite of tools for large data analytics. About the speaker Julien Jomier is directing Kitware's European subsidiary in Lyon, France, where he focuses on European business development. Julien works on a variety of projects in the areas of parallel and distributed computing, mobile computing, image processing, and visualization. He is one of the developers of the Insight Toolkit (ITK), the Visualization Toolkit (VTK), and ParaView. Julien is also leading the CDash project, an open-source co...

DIA2: Web-based Cyberinfrastructure for Visual Analysis of Funding Portfolios.

Science.gov (United States)

Madhavan, Krishna; Elmqvist, Niklas; Vorvoreanu, Mihaela; Chen, Xin; Wong, Yuetling; Xian, Hanjun; Dong, Zhihua; Johri, Aditya

2014-12-01

We present a design study of the Deep Insights Anywhere, Anytime (DIA2) platform, a web-based visual analytics system that allows program managers and academic staff at the U.S. National Science Foundation to search, view, and analyze their research funding portfolio. The goal of this system is to facilitate users' understanding of both past and currently active research awards in order to make more informed decisions of their future funding. This user group is characterized by high domain expertise yet not necessarily high literacy in visualization and visual analytics-they are essentially casual experts-and thus require careful visual and information design, including adhering to user experience standards, providing a self-instructive interface, and progressively refining visualizations to minimize complexity. We discuss the challenges of designing a system for casual experts and highlight how we addressed this issue by modeling the organizational structure and workflows of the NSF within our system. We discuss each stage of the design process, starting with formative interviews, prototypes, and finally live deployments and evaluation with stakeholders.

Network Patterns of Inventor Collaboration and Their Effects on Innovation Outputs

Directory of Open Access Journals (Sweden)

Wonchang Hur

2016-03-01

Full Text Available The purpose of this study is to examine how the collaboration structure among inventors in an R and D organization affects its capability to create impactful innovations. Specifically, this study is focused on examining whether a certain type of network mechanism found in collaboration among inventors contributes more to enhancing the future impacts of collaboration outputs, which is represented by the forward citations of their patents. To this end, co-invention networks for R and D organizations are constructed from an inventor-patent database, and the three structural patterns are measured by using network analytic constructs, namely, structural holes, strength of ties, and centralization. The results show that the presence of structural holes and strong ties are positively associated with the increasing forward citations, and that decentralized collaboration has also a positive impact. The findings offer support for both structural hole and network closure perspectives on social capital, which have been considered contradictive in the literature.

Demonstration of visualization techniques for the control room engineer in 2030

DEFF Research Database (Denmark)

Marinelli, Mattia; Heussen, Kai; Strasser, Thomas

2017-01-01

Deliverable 8.1 reports results on analytics and visualizations of real time flexibility in support of voltage and frequency control in 2030+ power system. The investigation is carried out by means of relevant control room scenarios in order to derive the appropriate analytics needed for each spe...

Big Data Analytics and Machine Intelligence Capability Development at NASA Langley Research Center: Strategy, Roadmap, and Progress

Science.gov (United States)

Ambur, Manjula Y.; Yagle, Jeremy J.; Reith, William; McLarney, Edward

2016-01-01

In 2014, a team of researchers, engineers and information technology specialists at NASA Langley Research Center developed a Big Data Analytics and Machine Intelligence Strategy and Roadmap as part of Langley's Comprehensive Digital Transformation Initiative, with the goal of identifying the goals, objectives, initiatives, and recommendations need to develop near-, mid- and long-term capabilities for data analytics and machine intelligence in aerospace domains. Since that time, significant progress has been made in developing pilots and projects in several research, engineering, and scientific domains by following the original strategy of collaboration between mission support organizations, mission organizations, and external partners from universities and industry. This report summarizes the work to date in Data Intensive Scientific Discovery, Deep Content Analytics, and Deep Q&A projects, as well as the progress made in collaboration, outreach, and education. Recommendations for continuing this success into future phases of the initiative are also made.

Ultrascale Visualization of Climate Data

Science.gov (United States)

Williams, Dean N.; Bremer, Timo; Doutriaux, Charles; Patchett, John; Williams, Sean; Shipman, Galen; Miller, Ross; Pugmire, David R.; Smith, Brian; Steed, Chad;

Interlaboratory analytical performance studies; a way to estimate measurement uncertainty

Directory of Open Access Journals (Sweden)

El¿bieta £ysiak-Pastuszak

2004-09-01

Full Text Available Comparability of data collected within collaborative programmes became the key challenge of analytical chemistry in the 1990s, including monitoring of the marine environment. To obtain relevant and reliable data, the analytical process has to proceed under a well-established Quality Assurance (QA system with external analytical proficiency tests as an inherent component. A programme called Quality Assurance in Marine Monitoring in Europe (QUASIMEME was established in 1993 and evolved over the years as the major provider of QA proficiency tests for nutrients, trace metals and chlorinated organic compounds in marine environment studies. The article presents an evaluation of results obtained in QUASIMEME Laboratory Performance Studies by the monitoring laboratory of the Institute of Meteorology and Water Management (Gdynia, Poland in exercises on nutrient determination in seawater. The measurement uncertainty estimated from routine internal quality control measurements and from results of analytical performance exercises is also presented in the paper.

BioIMAX: A Web 2.0 approach for easy exploratory and collaborative access to multivariate bioimage data

Directory of Open Access Journals (Sweden)

Khan Michael

2011-07-01

Full Text Available Abstract Background Innovations in biological and biomedical imaging produce complex high-content and multivariate image data. For decision-making and generation of hypotheses, scientists need novel information technology tools that enable them to visually explore and analyze the data and to discuss and communicate results or findings with collaborating experts from various places. Results In this paper, we present a novel Web2.0 approach, BioIMAX, for the collaborative exploration and analysis of multivariate image data by combining the webs collaboration and distribution architecture with the interface interactivity and computation power of desktop applications, recently called rich internet application. Conclusions BioIMAX allows scientists to discuss and share data or results with collaborating experts and to visualize, annotate, and explore multivariate image data within one web-based platform from any location via a standard web browser requiring only a username and a password. BioIMAX can be accessed at http://ani.cebitec.uni-bielefeld.de/BioIMAX with the username "test" and the password "test1" for testing purposes.

Work-Centered Design and Evaluation of a C2 Visualization Aid

National Research Council Canada - National Science Library

Roth, Emilie; Scott, Ronald; Kazmierczak, Tom; Whitaker, Randall; Stilson, Mona; Thomas-Meyers, Gina; Wampler, Jeffrey

2006-01-01

.... We have been developing and applying work-centered design and evaluation methodologies to design advanced visualization and support tools intended to more effectively support C2 cognitive and collaborative work...

High End Visualization of Geophysical Datasets Using Immersive Technology: The SIO Visualization Center.

Science.gov (United States)

Newman, R. L.

2002-12-01

How many images can you display at one time with Power Point without getting "postage stamps"? Do you have fantastic datasets that you cannot view because your computer is too slow/small? Do you assume a few 2-D images of a 3-D picture are sufficient? High-end visualization centers can minimize and often eliminate these problems. The new visualization center [http://siovizcenter.ucsd.edu] at Scripps Institution of Oceanography [SIO] immerses users into a virtual world by projecting 3-D images onto a Panoram GVR-120E wall-sized floor-to-ceiling curved screen [7' x 23'] that has 3.2 mega-pixels of resolution. The Infinite Reality graphics subsystem is driven by a single-pipe SGI Onyx 3400 with a system bandwidth of 44 Gbps. The Onyx is powered by 16 MIPS R12K processors and 16 GB of addressable memory. The system is also equipped with transmitters and LCD shutter glasses which permit stereographic 3-D viewing of high-resolution images. This center is ideal for groups of up to 60 people who can simultaneously view these large-format images. A wide range of hardware and software is available, giving the users a totally immersive working environment in which to display, analyze, and discuss large datasets. The system enables simultaneous display of video and audio streams from sources such as SGI megadesktop and stereo megadesktop, S-VHS video, DVD video, and video from a Macintosh or PC. For instance, one-third of the screen might be displaying S-VHS video from a remotely-operated-vehicle [ROV], while the remaining portion of the screen might be used for an interactive 3-D flight over the same parcel of seafloor. The video and audio combinations using this system are numerous, allowing users to combine and explore data and images in innovative ways, greatly enhancing scientists' ability to visualize, understand and collaborate on complex datasets. In the not-distant future, with the rapid growth in networking speeds in the US, it will be possible for Earth Sciences

Open Access to Multi-Domain Collaborative Analysis of Geospatial Data Through the Internet

Science.gov (United States)

Turner, A.

2009-12-01

The internet has provided us with a high bandwidth, low latency, globally connected network in which to rapidly share realtime data from sensors, reports, and imagery. In addition, the availability of this data is even easier to obtain, consume and analyze. Another aspect of the internet has been the increased approachability of complex systems through lightweight interfaces - with additional complex services able to provide more advanced connections into data services. These analyses and discussions have primarily been siloed within single domains, or kept out of the reach of amateur scientists and interested citizens. However, through more open access to analytical tools and data, experts can collaborate with citizens to gather information, provide interfaces for experimenting and querying results, and help make improved insights and feedback for further investigation. For example, farmers in Uganda are able to use their mobile phones to query, analyze, and be alerted to banana crop disease based on agriculture and climatological data. In the U.S., local groups use online social media sharing sites to gather data on storm-water runoff and stream siltation in order to alert wardens and environmental agencies. This talk will present various web-based geospatial visualization and analysis techniques and tools such as Google Earth and GeoCommons that have emerged that provide for a collaboration between experts of various domains as well as between experts, government, and citizen scientists. Through increased communication and the sharing of data and tools, it is possible to gain broad insight and development of joint, working solutions to a variety of difficult scientific and policy related questions.

Collaborative Visualization and Analysis of Multi-dimensional, Time-dependent and Distributed Data in the Geosciences Using the Unidata Integrated Data Viewer

Science.gov (United States)

Meertens, C. M.; Murray, D.; McWhirter, J.

2004-12-01

Over the last five years, UNIDATA has developed an extensible and flexible software framework for analyzing and visualizing geoscience data and models. The Integrated Data Viewer (IDV), initially developed for visualization and analysis of atmospheric data, has broad interdisciplinary application across the geosciences including atmospheric, ocean, and most recently, earth sciences. As part of the NSF-funded GEON Information Technology Research project, UNAVCO has enhanced the IDV to display earthquakes, GPS velocity vectors, and plate boundary strain rates. These and other geophysical parameters can be viewed simultaneously with three-dimensional seismic tomography and mantle geodynamic model results. Disparate data sets of different formats, variables, geographical projections and scales can automatically be displayed in a common projection. The IDV is efficient and fully interactive allowing the user to create and vary 2D and 3D displays with contour plots, vertical and horizontal cross-sections, plan views, 3D isosurfaces, vector plots and streamlines, as well as point data symbols or numeric values. Data probes (values and graphs) can be used to explore the details of the data and models. The IDV is a freely available Java application using Java3D and VisAD and runs on most computers. UNIDATA provides easy-to-follow instructions for download, installation and operation of the IDV. The IDV primarily uses netCDF, a self-describing binary file format, to store multi-dimensional data, related metadata, and source information. The IDV is designed to work with OPeNDAP-equipped data servers that provide real-time observations and numerical models from distributed locations. Users can capture and share screens and animations, or exchange XML "bundles" that contain the state of the visualization and embedded links to remote data files. A real-time collaborative feature allows groups of users to remotely link IDV sessions via the Internet and simultaneously view and

Collaborative Environments. Considerations Concerning Some Collaborative Systems

Directory of Open Access Journals (Sweden)

Mihaela I. MUNTEAN

2009-01-01

Full Text Available It is obvious, that all collaborative environments (workgroups, communities of practice, collaborative enterprises are based on knowledge and between collaboration and knowledge management there is a strong interdependence. The evolution of information systems in these collaborative environments led to the sudden necessity to adopt, for maintaining the virtual activities and processes, the latest technologies/systems, which are capable to support integrated collaboration in business services. In these environments, portal-based IT platforms will integrate multi-agent collaborative systems, collaborative tools, different enterprise applications and other useful information systems.

Dissociable meta-analytic brain networks contribute to coordinated emotional processing.

Science.gov (United States)

Riedel, Michael C; Yanes, Julio A; Ray, Kimberly L; Eickhoff, Simon B; Fox, Peter T; Sutherland, Matthew T; Laird, Angela R

2018-06-01

Meta-analytic techniques for mining the neuroimaging literature continue to exert an impact on our conceptualization of functional brain networks contributing to human emotion and cognition. Traditional theories regarding the neurobiological substrates contributing to affective processing are shifting from regional- towards more network-based heuristic frameworks. To elucidate differential brain network involvement linked to distinct aspects of emotion processing, we applied an emergent meta-analytic clustering approach to the extensive body of affective neuroimaging results archived in the BrainMap database. Specifically, we performed hierarchical clustering on the modeled activation maps from 1,747 experiments in the affective processing domain, resulting in five meta-analytic groupings of experiments demonstrating whole-brain recruitment. Behavioral inference analyses conducted for each of these groupings suggested dissociable networks supporting: (1) visual perception within primary and associative visual cortices, (2) auditory perception within primary auditory cortices, (3) attention to emotionally salient information within insular, anterior cingulate, and subcortical regions, (4) appraisal and prediction of emotional events within medial prefrontal and posterior cingulate cortices, and (5) induction of emotional responses within amygdala and fusiform gyri. These meta-analytic outcomes are consistent with a contemporary psychological model of affective processing in which emotionally salient information from perceived stimuli are integrated with previous experiences to engender a subjective affective response. This study highlights the utility of using emergent meta-analytic methods to inform and extend psychological theories and suggests that emotions are manifest as the eventual consequence of interactions between large-scale brain networks. © 2018 Wiley Periodicals, Inc.

Guiding Students from Consuming Information to Creating Knowledge: A Freshman English Library Instruction Collaboration

Directory of Open Access Journals (Sweden)

Carolyn B. Gamtso

2012-04-01

Full Text Available In this paper we examine how faculty and librarians’ own approaches to and attitudes toward library tools, as well as their assumptions about student research practices, impede students’ ability to view learning as a recursive, creative, and ongoing inquiry. We propose first that librarians and faculty examine the assumptions of knowledge that characterize their respective university constituencies; second that they dismantle some of the disciplinary boundaries that separate these constituencies; third that they collaborate to craft analytical assignments that stress knowledge as process; and fourth that they transform library instruction from tool-based demonstrations to analytical, problem-based learning exercises. Finally, we describe how we have collaborated to craft a Freshman Composition library instruction session that moves beyond developing students’ information-gathering expertise by focusing on the development of transferable knowledge and critical thinking skills.

A review of analytics and clinical informatics in health care.

Science.gov (United States)

Simpao, Allan F; Ahumada, Luis M; Gálvez, Jorge A; Rehman, Mohamed A

2014-04-01

Federal investment in health information technology has incentivized the adoption of electronic health record systems by physicians and health care organizations; the result has been a massive rise in the collection of patient data in electronic form (i.e. "Big Data"). Health care systems have leveraged Big Data for quality and performance improvements using analytics-the systematic use of data combined with quantitative as well as qualitative analysis to make decisions. Analytics have been utilized in various aspects of health care including predictive risk assessment, clinical decision support, home health monitoring, finance, and resource allocation. Visual analytics is one example of an analytics technique with an array of health care and research applications that are well described in the literature. The proliferation of Big Data and analytics in health care has spawned a growing demand for clinical informatics professionals who can bridge the gap between the medical and information sciences.

Collaborative analysis for certification of zirconium and zirconium base alloy reference materials JAERI-Z11 to Z16

International Nuclear Information System (INIS)

1985-03-01

The second Sub-Committee on Zircaloy Analysis was organized in April 1978, under the Committee on Analytical Chemistry on Nuclear Fuels and Reactor Materials, JAERI, for the renewal of zirconium and zirconium base alloy certified reference materials (CRMs). The Sub-Committee carried out collaborative analysis among 13 participating laboratories for the certification of the CRMs, JAERI-Z11 to Z18, after development, improvement and evaluation of analytical methods during the period of May 1978 to June 1982. As the result of the collaborative analysis, the certified value was given for 18 elements (Sn, Fe, Ni, Cr, B, Cd, U, Cu, Co, Mn, Pb, Al, Ti, Si, Mo, W, Hf, C) in the CRMs. The first part of this report includes general discussion, the second part principles of certification, the third part development and verification of analytical methods, and the fourth part evaluation of analytical results on 17 elements. Preparation of Z11 to Z18, and certification for carbon in JAERI-Z17 and Z18 were reported separately in JAERI-M 83-241 and M 83-035, respectively. (author)

Comparative federal health care policy: evidence of collaborative federalism in Pakistan and Venezuela.

Science.gov (United States)

Baracskay, Daniel

2013-01-01

Collaborative federalism has provided an effective analytical foundation for understanding how complex public policies are implemented in federal systems through intergovernmental and intersectoral alignments. This has particularly been the case in issue areas like public health policy where diseases are detected and treated at the local level. While past studies on collaborative federalism and health care policy have focused on federal systems that are largely democratic, little research has been conducted to examine the extent of collaboration in authoritarian structures. This article applies the collaborative federalism approach to the Islamic Republic of Pakistan and the Bolivarian Republic of Venezuela. Evidence suggests that while both nations have exhibited authoritarian governing structures, there have been discernible policy areas where collaborative federalism is embraced to facilitate the implementation process. Further, while not an innate aspect of their federal structures, Pakistan and Venezuela can potentially expand their use of the collaborative approach to successfully implement health care policy and the epidemiological surveillance and intervention functions. Yet, as argued, this would necessitate further development of their structures on a sustained basis to create an environment conducive for collaborative federalism to flourish, and possibly expand to other policy areas as well.

CM-DataONE: A Framework for collaborative analysis of climate model output

Science.gov (United States)

Xu, Hao; Bai, Yuqi; Li, Sha; Dong, Wenhao; Huang, Wenyu; Xu, Shiming; Lin, Yanluan; Wang, Bin

2015-04-01

CM-DataONE is a distributed collaborative analysis framework for climate model data which aims to break through the data access barriers of increasing file size and to accelerate research process. As data size involved in project such as the fifth Coupled Model Intercomparison Project (CMIP5) has reached petabytes, conventional methods for analysis and diagnosis of model outputs have been rather time-consuming and redundant. CM-DataONE is developed for data publishers and researchers from relevant areas. It can enable easy access to distributed data and provide extensible analysis functions based on tools such as NCAR Command Language, NetCDF Operators (NCO) and Climate Data Operators (CDO). CM-DataONE can be easily installed, configured, and maintained. The main web application has two separate parts which communicate with each other through APIs based on HTTP protocol. The analytic server is designed to be installed in each data node while a data portal can be configured anywhere and connect to a nearest node. Functions such as data query, analytic task submission, status monitoring, visualization and product downloading are provided to end users by data portal. Data conform to CMIP5 Model Output Format in each peer node can be scanned by the server and mapped to a global information database. A scheduler included in the server is responsible for task decomposition, distribution and consolidation. Analysis functions are always executed where data locate. Analysis function package included in the server has provided commonly used functions such as EOF analysis, trend analysis and time series. Functions are coupled with data by XML descriptions and can be easily extended. Various types of results can be obtained by users for further studies. This framework has significantly decreased the amount of data to be transmitted and improved efficiency in model intercomparison jobs by supporting online analysis and multi-node collaboration. To end users, data query is

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.

Collaborative decision-making on wind power projects based on AHP method

Science.gov (United States)

Badea, A.; Proştean, G.; Tămăşilă, M.; Vârtosu, A.

2017-01-01

The complexity of projects implementation in Renewable Energy Sources (RES) requires finding collaborative alliances between suppliers and project developers in RES. Links activities in supply chain in RES, respectively, transportation of heavy components, processing orders to purchase quality raw materials, storage and materials handling, packaging, and other complex activities requiring a logistics system collaboratively to be permanently dimensioned properly selected and monitored. Requirements imposed by stringency of wind power energy projects implementation inevitably involves constraints in infrastructure, implementation and logistics. Thus, following an extensive research in RES project, to eliminate these constraints were identified alternative collaboration to provide feasible solutions on different levels of performance. The paper presents a critical analysis of different collaboration alternatives in supply chain for RES projects, selecting the ones most suitable for particular situations by using decision-making method Analytic Hierarchy Process (AHP). The role of AHP method was to formulate a decision model by which can be establish the collaboration alternative choice through mathematical calculation to reduce the impact created by constraints encountered. The solution provided through AHP provides a framework for detecting optimal alternative collaboration between suppliers and project developers in RES and avoids some breaks in the chain by resizing safety buffers for leveling orders in RES projects.

Big data analytics as a service infrastructure: challenges, desired properties and solutions

CERN Document Server

Martín-Márquez, Manuel

2015-01-01

CERN's accelerator complex generates a very large amount of data. A large volumen of heterogeneous data is constantly generated from control equipment and monitoring agents. These data must be stored and analysed. Over the decades, CERN's researching and engineering teams have applied different approaches, techniques and technologies for this purpose. This situation has minimised the necessary collaboration and, more relevantly, the cross data analytics over different domains. These two factors are essential to unlock hidden insights and correlations between the underlying processes, which enable better and more efficient daily-based accelerator operations and more informed decisions. The proposed Big Data Analytics as a Service Infrastructure aims to: (1) integrate the existing developments, (2) centralise and standardise the complex data analytics needs for CERN's research and engineering community, (3) deliver real-time, batch data analytics and information discovery capabilities, and (4) provide transpare...

Collaborative Image Coding and Transmission over Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Min Wu

2007-01-01

Full Text Available The imaging sensors are able to provide intuitive visual information for quick recognition and decision. However, imaging sensors usually generate vast amount of data. Therefore, processing and coding of image data collected in a sensor network for the purpose of energy efficient transmission poses a significant technical challenge. In particular, multiple sensors may be collecting similar visual information simultaneously. We propose in this paper a novel collaborative image coding and transmission scheme to minimize the energy for data transmission. First, we apply a shape matching method to coarsely register images to find out maximal overlap to exploit the spatial correlation between images acquired from neighboring sensors. For a given image sequence, we transmit background image only once. A lightweight and efficient background subtraction method is employed to detect targets. Only the regions of target and their spatial locations are transmitted to the monitoring center. The whole image can then be reconstructed by fusing the background and the target images as well as their spatial locations. Experimental results show that the energy for image transmission can indeed be greatly reduced with collaborative image coding and transmission.

Collaborative Video Search Combining Video Retrieval with Human-Based Visual Inspection

NARCIS (Netherlands)

Hudelist, M.A.; Cobârzan, C.; Beecks, C.; van de Werken, Rob; Kletz, S.; Hürst, W.O.; Schoeffmann, K.

2016-01-01

We propose a novel video browsing approach that aims at optimally integrating traditional, machine-based retrieval methods with an interface design optimized for human browsing performance. Advanced video retrieval and filtering (e.g., via color and motion signatures, and visual concepts) on a

Connecting art and the brain: an artist’s perspective on visual indeterminacy

Directory of Open Access Journals (Sweden)

Robert ePepperell

2011-08-01

Full Text Available In this article I will discuss the intersection between art and neuroscience from the perspective of a practicing artist. I have collaborated on several scientific studies into the effects of art on the brain and behaviour, looking in particular at the phenomenon of ‘visual indeterminacy’. This is a perceptual state in which subjects fail to recognise objects from visual cues. I will look at the background to this phenomenon, and show how various artists have exploited its effect through the history of art. My own attempts to create indeterminate images will be discussed, including some of the technical problems I faced in trying to manipulate the viewer’s perceptual state through paintings. Visual indeterminacy is not widely studied in neuroscience, although references to it can be found in the literature on visual agnosia and object recognition. I will briefly review some of this work and show how my attempts to understand the science behind visual indeterminacy led me to collaborate with psychophysicists and neuroscientists. After reviewing this work, I will discuss the conclusions I have drawn from its findings and consider the problem of how best to integrate neuroscientific methods with artistic knowledge to create truly interdisciplinary approach.

Showing/Sharing: Analysing Visual Communication from a Praxeological Perspective

Directory of Open Access Journals (Sweden)

Maria Schreiber

2017-12-01

Full Text Available This contribution proposes a methodological framework for empirical research into visual practices on social media. The framework identifies practices, pictures and platforms as relevant dimensions of analysis. It is mainly developed within, and is compatible with qualitative, interpretive approaches which focus on visual communication as part of everyday personal communicative practices. Two screenshots from Instagram and Facebook are introduced as empirical examples to investigate collaborative practices of meaning-making relating to pictures on social media. While social media seems to augment reflexive, processual practices of negotiating identities, visual media, in particular, amps up aesthetic, ambivalent and embodied dimensions within these practices.

Developments in Remote Collaboration and Computation

International Nuclear Information System (INIS)

Burruss, J.R.; Abla, G.; Flanagan, S.; Keahey, K.; Leggett, T.; Ludesche, C.; McCune, D.; Papka, M.E.; Peng, Q.; Randerson, L.; Schissel, D.P.

2005-01-01

The National Fusion Collaboratory (NFC) is creating and deploying collaborative software tools to unite magnetic fusion research in the United States. In particular, the NFC is developing and deploying a national FES 'Grid' (FusionGrid) for secure sharing of computation, visualization, and data resources over the Internet. The goal of FusionGrid is to allow scientists at remote sites to participate as fully in experiments, machine design, and computational activities as if they were working on site thereby creating a unified virtual organization of the geographically dispersed U.S. fusion community

Spread Spectrum Based Energy Efficient Collaborative Communication in Wireless Sensor Networks.

Science.gov (United States)

Ghani, Anwar; Naqvi, Husnain; Sher, Muhammad; Khan, Muazzam Ali; Khan, Imran; Irshad, Azeem

2016-01-01

Wireless sensor networks consist of resource limited devices. Most crucial of these resources is battery life, as in most applications like battle field or volcanic area monitoring, it is often impossible to replace or recharge the power source. This article presents an energy efficient collaborative communication system based on spread spectrum to achieve energy efficiency as well as immunity against jamming, natural interference, noise suppression and universal frequency reuse. Performance of the proposed system is evaluated using the received signal power, bit error rate (BER) and energy consumption. The results show a direct proportionality between the power gain and the number of collaborative nodes as well as BER and signal-to-noise ratio (Eb/N0). The analytical and simulation results of the proposed system are compared with SISO system. The comparison reveals that SISO perform better than collaborative communication in case of small distances whereas collaborative communication performs better than SISO in case of long distances. On the basis of these results it is safe to conclude that collaborative communication in wireless sensor networks using wideband systems improves the life time of nodes in the networks thereby prolonging the network's life time.

Designing for competence: spaces that enhance collaboration readiness in healthcare.

Science.gov (United States)

Lamb, Gerri; Shraiky, James

2013-09-01

Many universities in the United States are investing in classrooms and campuses designed to increase collaboration and teamwork among the health professions. To date, we know little about whether these learning spaces are having the intended impact on student performance. Recent advances in the identification of interprofessional teamwork competencies provide a much-needed step toward a defined outcome metric. Rigorous study of the relationship between design and student competence in collaboration also requires clear specification of design concepts and development of testable frameworks. Such theory-based evaluation is crucial for design to become an integral part of interprofessional education strategies and initiatives. Current classroom and campus designs were analyzed for common themes and features in collaborative spaces as a starting place for specification of design concepts and model development. Four major themes were identified: flexibility, visual transparency/proximity, technology and environmental infrastructure. Potential models linking this preliminary set of design concepts to student competencies are proposed and used to generate hypotheses for future study of the impact of collaborative design spaces on student outcomes.

The Importance of Data Visualization: Incorporating Storytelling into the Scientific Presentation

Science.gov (United States)

Babiak-Vazquez, A.; Cornett, A. N.; Wear, M. L.; Sams, C.

2014-01-01

From its inception in 2000, one of the primary tasks of the Biomedical Data Reduction Analysis (BDRA) group has been translation of large amounts of data into information that is relevant to the audience receiving it. BDRA helps translate data into an integrated model that supports both operational and research activities. This data integrated model and subsequent visual data presentations have contributed to BDRA's success in delivering the message (i.e., the story) that its customers have needed to communicate. This success has led to additional collaborations among groups that had previously not felt they had much in common until they worked together to develop solutions in an integrated fashion. As more emphasis is placed on working with "big data" and on showing how NASA's efforts contribute to the greater good of the American people and of the world, it becomes imperative to visualize the story of our data to communicate the greater message we need to share. METHODS To create and expand its data integrated model, BDRA has incorporated data from many different collaborating partner labs and other sources. Data are compiled from the repositories of the Lifetime Surveillance of Astronaut Health and the Life Sciences Data Archive, and from the individual laboratories at Johnson Space Center that support collection of data from medical testing, environmental monitoring, and countermeasures, as designated in the Medical Requirements Integration Documents. Ongoing communication with the participating collaborators is maintained to ensure that the message and story of the data are retained as data are translated into information and visual data presentations are delivered in different venues and to different audiences. RESULTS We will describe the importance of storytelling through an integrated model and of subsequent data visualizations in today's scientific presentations and discuss the collaborative methods used. We will illustrate the discussion with examples of

Slushy weightings for the optimal pilot model. [considering visual tracking task

Science.gov (United States)

Dillow, J. D.; Picha, D. G.; Anderson, R. O.

1975-01-01

A pilot model is described which accounts for the effect of motion cues in a well defined visual tracking task. The effect of visual and motion cues are accounted for in the model in two ways. First, the observation matrix in the pilot model is structured to account for the visual and motion inputs presented to the pilot. Secondly, the weightings in the quadratic cost function associated with the pilot model are modified to account for the pilot's perception of the variables he considers important in the task. Analytic results obtained using the pilot model are compared to experimental results and in general good agreement is demonstrated. The analytic model yields small improvements in tracking performance with the addition of motion cues for easily controlled task dynamics and large improvements in tracking performance with the addition of motion cues for difficult task dynamics.

Using a Collaborative Critiquing Technique to Develop Chemistry Students' Technical Writing Skills

Science.gov (United States)

Carr, Jeremy M.

2013-01-01

The technique, termed "collaborative critiquing", was developed to teach fundamental technical writing skills to analytical chemistry students for the preparation of laboratory reports. This exercise, which can be completed prior to peer-review activities, is novel, highly interactive, and allows students to take responsibility for their…

How I Learned to Swim: The Visual Journal as a Companion to Creative Inquiry

Science.gov (United States)

Scott Shields, Sara

2016-01-01

In this paper, I discuss my engagement with a visual journal as a companion to creative research practice during my dissertation research. Grounded in arts based research methodologies; I explore visual journals in relationship to research, reflection and analytic processes. I begin with a discussion of the visual journal as an artifact of…

Visualizing data mining results with the Brede tools

Directory of Open Access Journals (Sweden)

Finn A Nielsen

2009-07-01

Full Text Available A few neuroinformatics databases now exist that record results from neuroimaging studies in the form of brain coordinates in stereotaxic space. The Brede Toolbox was originally developed to extract, analyze and visualize data from one of them --- the BrainMap database. Since then the Brede Toolbox has expanded and now includes its own database with coordinates along with ontologies for brain regions and functions: The Brede Database. With Brede Toolbox and Database combined we setup automated workflows for extraction of data, mass meta-analytic data mining and visualizations. Most of the Web presence of the Brede Database is established by a single script executing a workflow involving these steps together with a final generation of Web pages with embedded visualizations and links to interactive three-dimensional models in the Virtual Reality Modeling Language. Apart from the Brede tools I briefly review alternate visualization tools and methods for Internet-based visualization and information visualization as well as portals for visualization tools.

Use of artificial intelligence techniques for visual inspection systems prototyping. Application to magnetoscopy

International Nuclear Information System (INIS)

Pallas, Christophe

1987-01-01

The automation of visual inspection is a complex task that requires collaboration between experts, for example inspection specialist, vision specialist. on-line operators. Solving such problems through prototyping promotes this collaboration: the use of a non specific programming environment allows rapid, concrete checking of method validity, thus leading incrementally to the final system. In this context, artificial intelligence techniques permit easy, extensible, and modular design of the prototype, together with heuristic solution building. We define and achieve the SPOR prototyping environment, based on object-oriented programming and rules-basis managing. The feasibility and the validity of an heuristic method for automated visual inspection in fluoroscopy have been proved through prototyping in SPOR. (author) [fr

mHealth Visual Discovery Dashboard.

Science.gov (United States)

Fang, Dezhi; Hohman, Fred; Polack, Peter; Sarker, Hillol; Kahng, Minsuk; Sharmin, Moushumi; al'Absi, Mustafa; Chau, Duen Horng

2017-09-01

We present Discovery Dashboard, a visual analytics system for exploring large volumes of time series data from mobile medical field studies. Discovery Dashboard offers interactive exploration tools and a data mining motif discovery algorithm to help researchers formulate hypotheses, discover trends and patterns, and ultimately gain a deeper understanding of their data. Discovery Dashboard emphasizes user freedom and flexibility during the data exploration process and enables researchers to do things previously challenging or impossible to do - in the web-browser and in real time. We demonstrate our system visualizing data from a mobile sensor study conducted at the University of Minnesota that included 52 participants who were trying to quit smoking.

Modeling human comprehension of data visualizations

Energy Technology Data Exchange (ETDEWEB)

Matzen, Laura E. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Haass, Michael Joseph [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Divis, Kristin Marie [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Wilson, Andrew T. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)

2017-09-01

This project was inspired by two needs. The first is a need for tools to help scientists and engineers to design effective data visualizations for communicating information, whether to the user of a system, an analyst who must make decisions based on complex data, or in the context of a technical report or publication. Most scientists and engineers are not trained in visualization design, and they could benefit from simple metrics to assess how well their visualization's design conveys the intended message. In other words, will the most important information draw the viewer's attention? The second is the need for cognition-based metrics for evaluating new types of visualizations created by researchers in the information visualization and visual analytics communities. Evaluating visualizations is difficult even for experts. However, all visualization methods and techniques are intended to exploit the properties of the human visual system to convey information efficiently to a viewer. Thus, developing evaluation methods that are rooted in the scientific knowledge of the human visual system could be a useful approach. In this project, we conducted fundamental research on how humans make sense of abstract data visualizations, and how this process is influenced by their goals and prior experience. We then used that research to develop a new model, the Data Visualization Saliency Model, that can make accurate predictions about which features in an abstract visualization will draw a viewer's attention. The model is an evaluation tool that can address both of the needs described above, supporting both visualization research and Sandia mission needs.

Capacity of Wireless Ad Hoc Networks with Opportunistic Collaborative Communications

Directory of Open Access Journals (Sweden)

Simeone O

2007-01-01

Full Text Available Optimal multihop routing in ad hoc networks requires the exchange of control messages at the MAC and network layer in order to set up the (centralized optimization problem. Distributed opportunistic space-time collaboration (OST is a valid alternative that avoids this drawback by enabling opportunistic cooperation with the source at the physical layer. In this paper, the performance of OST is investigated. It is shown analytically that opportunistic collaboration outperforms (centralized optimal multihop in case spatial reuse (i.e., the simultaneous transmission of more than one data stream is not allowed by the transmission protocol. Conversely, in case spatial reuse is possible, the relative performance between the two protocols has to be studied case by case in terms of the corresponding capacity regions, given the topology and the physical parameters of network at hand. Simulation results confirm that opportunistic collaborative communication is a promising paradigm for wireless ad hoc networks that deserves further investigation.

Capacity of Wireless Ad Hoc Networks with Opportunistic Collaborative Communications

Directory of Open Access Journals (Sweden)

O. Simeone

2007-03-01

Full Text Available Optimal multihop routing in ad hoc networks requires the exchange of control messages at the MAC and network layer in order to set up the (centralized optimization problem. Distributed opportunistic space-time collaboration (OST is a valid alternative that avoids this drawback by enabling opportunistic cooperation with the source at the physical layer. In this paper, the performance of OST is investigated. It is shown analytically that opportunistic collaboration outperforms (centralized optimal multihop in case spatial reuse (i.e., the simultaneous transmission of more than one data stream is not allowed by the transmission protocol. Conversely, in case spatial reuse is possible, the relative performance between the two protocols has to be studied case by case in terms of the corresponding capacity regions, given the topology and the physical parameters of network at hand. Simulation results confirm that opportunistic collaborative communication is a promising paradigm for wireless ad hoc networks that deserves further investigation.

Does Visualization Matter? The Role of Interactive Data Visualization to Make Sense of Information

Directory of Open Access Journals (Sweden)

Arif Perdana

2018-05-01

Full Text Available As part of business analytics (BA technologies, reporting and visualization play essential roles in mitigating users’ limitations (i.e., being inexperienced, having limited knowledge, and relying on simplified information. Reporting and visualization can potentially enhance users’ sense-making, thus permitting them to focus more on the information’s message rather than numerical analysis. To better understand the role of reporting and visualization in a contextualized environment, we investigate using interactive data visualization (IDV within accounting. We aim to understand whether IDV can help enhance non-professional investors’ ability to make sense of foundational financial statement analyses. This study conducted an experiment using a sample of 324 nonprofessional investors. Our findings indicate that nonprofessional investors who use IDV are more heuristically adept than non-professional investors who use non-IDV. These findings enrich the theoretical understanding of business analytics’ use in accounting decision making. The results of this study also suggest several practical courses of action, such as promoting wider use of IDV and making affordable IDV more broadly available, particularly for non-professional investors.

Combining computational analyses and interactive visualization for document exploration and sensemaking in jigsaw.

Science.gov (United States)

Görg, Carsten; Liu, Zhicheng; Kihm, Jaeyeon; Choo, Jaegul; Park, Haesun; Stasko, John

2013-10-01

Investigators across many disciplines and organizations must sift through large collections of text documents to understand and piece together information. Whether they are fighting crime, curing diseases, deciding what car to buy, or researching a new field, inevitably investigators will encounter text documents. Taking a visual analytics approach, we integrate multiple text analysis algorithms with a suite of interactive visualizations to provide a flexible and powerful environment that allows analysts to explore collections of documents while sensemaking. Our particular focus is on the process of integrating automated analyses with interactive visualizations in a smooth and fluid manner. We illustrate this integration through two example scenarios: an academic researcher examining InfoVis and VAST conference papers and a consumer exploring car reviews while pondering a purchase decision. Finally, we provide lessons learned toward the design and implementation of visual analytics systems for document exploration and understanding.

High performance visual display for HENP detectors

CERN Document Server

McGuigan, M; Spiletic, J; Fine, V; Nevski, P

2001-01-01

A high end visual display for High Energy Nuclear Physics (HENP) detectors is necessary because of the sheer size and complexity of the detector. For BNL this display will be of special interest because of STAR and ATLAS. To load, rotate, query, and debug simulation code with a modern detector simply takes too long even on a powerful work station. To visualize the HENP detectors with maximal performance we have developed software with the following characteristics. We develop a visual display of HENP detectors on BNL multiprocessor visualization server at multiple level of detail. We work with general and generic detector framework consistent with ROOT, GAUDI etc, to avoid conflicting with the many graphic development groups associated with specific detectors like STAR and ATLAS. We develop advanced OpenGL features such as transparency and polarized stereoscopy. We enable collaborative viewing of detector and events by directly running the analysis in BNL stereoscopic theatre. We construct enhanced interactiv...

Efficient OCT Image Enhancement Based on Collaborative Shock Filtering.

Science.gov (United States)

Liu, Guohua; Wang, Ziyu; Mu, Guoying; Li, Peijin

2018-01-01

Efficient enhancement of noisy optical coherence tomography (OCT) images is a key task for interpreting them correctly. In this paper, to better enhance details and layered structures of a human retina image, we propose a collaborative shock filtering for OCT image denoising and enhancement. Noisy OCT image is first denoised by a collaborative filtering method with new similarity measure, and then the denoised image is sharpened by a shock-type filtering for edge and detail enhancement. For dim OCT images, in order to improve image contrast for the detection of tiny lesions, a gamma transformation is first used to enhance the images within proper gray levels. The proposed method integrating image smoothing and sharpening simultaneously obtains better visual results in experiments.

Large-Scale Astrophysical Visualization on Smartphones

Science.gov (United States)

Becciani, U.; Massimino, P.; Costa, A.; Gheller, C.; Grillo, A.; Krokos, M.; Petta, C.

2011-07-01

Nowadays digital sky surveys and long-duration, high-resolution numerical simulations using high performance computing and grid systems produce multidimensional astrophysical datasets in the order of several Petabytes. Sharing visualizations of such datasets within communities and collaborating research groups is of paramount importance for disseminating results and advancing astrophysical research. Moreover educational and public outreach programs can benefit greatly from novel ways of presenting these datasets by promoting understanding of complex astrophysical processes, e.g., formation of stars and galaxies. We have previously developed VisIVO Server, a grid-enabled platform for high-performance large-scale astrophysical visualization. This article reviews the latest developments on VisIVO Web, a custom designed web portal wrapped around VisIVO Server, then introduces VisIVO Smartphone, a gateway connecting VisIVO Web and data repositories for mobile astrophysical visualization. We discuss current work and summarize future developments.

Interprofessional collaboration - a matter of differentiation and integration? Theoretical reflections based in the context of Norwegian childcare.

Science.gov (United States)

Willumsen, Elisabeth

2008-08-01

This paper presents a selection of theoretical approaches illuminating some aspects of interprofessional collaboration, which will be related to theory of contingency as well as to the concepts of differentiation and integration. Theories that describe collaboration on an interpersonal as well as inter-organizational level are outlined and related to dynamic and contextual factors. Implications for the organization of welfare services are elucidated and a categorization of internal and external collaborative forms is proposed. A reflection model is presented in order to analyse the degree of integration in collaborative work and may serve as an analytical tool for addressing the linkage between different levels of collaboration and identifying opportunities and limitations. Some implications related to the legal mandate(s) given to childcare agencies are discussed in relation to the context of childcare in Norway.

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

Science.gov (United States)

Jedlovec, Gary; Srikishen, Jayanthi; Edwards, Rita; Cross, David; Welch, Jon; Smith, Matt

2013-01-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of "big data" available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Shortterm Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

Scalable Adaptive Graphics Environment (SAGE) Software for the Visualization of Large Data Sets on a Video Wall

Science.gov (United States)

Jedlovec, G.; Srikishen, J.; Edwards, R.; Cross, D.; Welch, J. D.; Smith, M. R.

2013-12-01

The use of collaborative scientific visualization systems for the analysis, visualization, and sharing of 'big data' available from new high resolution remote sensing satellite sensors or four-dimensional numerical model simulations is propelling the wider adoption of ultra-resolution tiled display walls interconnected by high speed networks. These systems require a globally connected and well-integrated operating environment that provides persistent visualization and collaboration services. This abstract and subsequent presentation describes a new collaborative visualization system installed for NASA's Short-term Prediction Research and Transition (SPoRT) program at Marshall Space Flight Center and its use for Earth science applications. The system consists of a 3 x 4 array of 1920 x 1080 pixel thin bezel video monitors mounted on a wall in a scientific collaboration lab. The monitors are physically and virtually integrated into a 14' x 7' for video display. The display of scientific data on the video wall is controlled by a single Alienware Aurora PC with a 2nd Generation Intel Core 4.1 GHz processor, 32 GB memory, and an AMD Fire Pro W600 video card with 6 mini display port connections. Six mini display-to-dual DVI cables are used to connect the 12 individual video monitors. The open source Scalable Adaptive Graphics Environment (SAGE) windowing and media control framework, running on top of the Ubuntu 12 Linux operating system, allows several users to simultaneously control the display and storage of high resolution still and moving graphics in a variety of formats, on tiled display walls of any size. The Ubuntu operating system supports the open source Scalable Adaptive Graphics Environment (SAGE) software which provides a common environment, or framework, enabling its users to access, display and share a variety of data-intensive information. This information can be digital-cinema animations, high-resolution images, high-definition video

The Role of Visual Learning in Improving Students' High-Order Thinking Skills

Science.gov (United States)

Raiyn, Jamal

2016-01-01

Various concepts have been introduced to improve students' analytical thinking skills based on problem based learning (PBL). This paper introduces a new concept to increase student's analytical thinking skills based on a visual learning strategy. Such a strategy has three fundamental components: a teacher, a student, and a learning process. The…

Multiuser Collaboration with Networked Mobile Devices

Science.gov (United States)

Tso, Kam S.; Tai, Ann T.; Deng, Yong M.; Becks, Paul G.

2006-01-01

In this paper we describe a multiuser collaboration infrastructure that enables multiple mission scientists to remotely and collaboratively interact with visualization and planning software, using wireless networked personal digital assistants(PDAs) and other mobile devices. During ground operations of planetary rover and lander missions, scientists need to meet daily to review downlinked data and plan science activities. For example, scientists use the Science Activity Planner (SAP) in the Mars Exploration Rover (MER) mission to visualize downlinked data and plan rover activities during the science meetings [1]. Computer displays are projected onto large screens in the meeting room to enable the scientists to view and discuss downlinked images and data displayed by SAP and other software applications. However, only one person can interact with the software applications because input to the computer is limited to a single mouse and keyboard. As a result, the scientists have to verbally express their intentions, such as selecting a target at a particular location on the Mars terrain image, to that person in order to interact with the applications. This constrains communication and limits the returns of science planning. Furthermore, ground operations for Mars missions are fundamentally constrained by the short turnaround time for science and engineering teams to process and analyze data, plan the next uplink, generate command sequences, and transmit the uplink to the vehicle [2]. Therefore, improving ground operations is crucial to the success of Mars missions. The multiuser collaboration infrastructure enables users to control software applications remotely and collaboratively using mobile devices. The infrastructure includes (1) human-computer interaction techniques to provide natural, fast, and accurate inputs, (2) a communications protocol to ensure reliable and efficient coordination of the input devices and host computers, (3) an application

Decolonizing Engagement? Creating a Sense of Community through Collaborative Filmmaking

Directory of Open Access Journals (Sweden)

Sarah Marie Wiebe

2016-03-01

Full Text Available The visual medium has the potential to be a creative avenue for enhancing  awareness, critical thought and social justice. Through the prism of collaborative filmmaking, academic-activists can enrich textual analyses while creating what Jacques Rancière calls a “sense of community” among participants. This article reflects on the process of co-producing an Indigenous youth-driven documentary film, Indian Givers, which is publicly available on YouTube. It discusses the applied practice of engaging in a collaborative process with the aim of countering Western models of knowledge. The film and this article each draw into focus the experiences and stories of Indigenous youth who live in a highly polluted place commonly referred to as Canada’s “Chemical Valley.” Informed by Chantal Mouffe’s notion of agonism, I contend that collaborative filmmaking contributes to anti-oppressive and community engaged scholarship by facilitating intercultural dialogue, offering a reflexive and relational approach to research, co-creating knowledge and contributing to social action. This paper reflects on some of the challenges of collaborative filmmaking in order to contribute to academic-activist research. As an anti-oppressive research tool, collaborative filmmaking provides a forum for resistance to dominant colonial discourses while creating space for radical difference in pursuit of decolonization.

Classroom Guitar and Students with Visual Impairments: A Positive Approach to Music Learning and Artistry

Science.gov (United States)

Coleman, Jeremy M.

2016-01-01

In 2011, a collaborative effort began between the Texas School for the Blind and Visually Impaired (TSBVI) and Austin Classical Guitar (ACG), a local 501(c) nonprofit music organization. The idea behind this collaboration was to start a small guitar program that would provide TSBVI students with quality classroom guitar instruction. At that time,…

A Paper-Based Electrochromic Array for Visualized Electrochemical Sensing.

Science.gov (United States)

Zhang, Fengling; Cai, Tianyi; Ma, Liang; Zhan, Liyuan; Liu, Hong

2017-01-31

We report a battery-powered, paper-based electrochromic array for visualized electrochemical sensing. The paper-based sensing system consists of six parallel electrochemical cells, which are powered by an aluminum-air battery. Each single electrochemical cell uses a Prussian Blue spot electrodeposited on an indium-doped tin oxide thin film as the electrochromic indicator. Each electrochemical cell is preloaded with increasing amounts of analyte. The sample activates the battery for the sensing. Both the preloaded analyte and the analyte in the sample initiate the color change of Prussian Blue to Prussian White. With a reaction time of 60 s, the number of electrochemical cells with complete color changes is correlated to the concentration of analyte in the sample. As a proof-of-concept analyte, lactic acid was detected semi-quantitatively using the naked eye.

Teach yourself visually complete WordPress

CERN Document Server

Majure, Janet

2013-01-01

Take your WordPress skills to the next level with these tips, tricks, and tasks Congratulations on getting your blog up and running with WordPress! Now are you ready to take it to the next level? Teach Yourself VISUALLY Complete WordPress takes you beyond the blogging basics with expanded tips, tricks, and techniques with clear, step-by-step instructions accompanied by screen shots. This visual book shows you how to incorporate forums, use RSS, obtain and review analytics, work with tools like Google AdSense, and much more.Shows you how to use mobile tools to edit a

The Power of Social Media Analytics: Text Analytics Based on Sentiment Analysis and Word Clouds on R

Directory of Open Access Journals (Sweden)

Ahmed Imran KABIR

2018-01-01

Full Text Available Apparently, word clouds have grown as a clear and appealing illustration or visualization strategy in terms of text. Word clouds are used as a part of various settings as a way to give a diagram by cleansing text throughout those words that come up with most frequently. Generally, this is performed constantly as an unadulterated text outline. In any case, that there is a bigger capability to this basic yet intense visualization worldview in text analytics. In this work, we investigate the adequacy of word clouds for general text analysis errands and also analyze the tweets to find out the sentiment and also discuss the legal aspects of text mining. We used R software to pull twitter data which depends altogether on word cloud as a visualization technique and also with the help of positive and negative words to determine the user sentiment. We indicate how this approach can be viably used to explain text analysis tasks and assess it in a qualitative user research.

Applications of image processing and visualization in the evaluation of murder and assault

Science.gov (United States)

Oliver, William R.; Rosenman, Julian G.; Boxwala, Aziz; Stotts, David; Smith, John; Soltys, Mitchell; Symon, James; Cullip, Tim; Wagner, Glenn

1994-09-01

Recent advances in image processing and visualization are of increasing use in the investigation of violent crime. The Digital Image Processing Laboratory at the Armed Forces Institute of Pathology in collaboration with groups at the University of North Carolina at Chapel Hill are actively exploring visualization applications including image processing of trauma images, 3D visualization, forensic database management and telemedicine. Examples of recent applications are presented. Future directions of effort include interactive consultation and image manipulation tools for forensic data exploration.

The shadow of black holes an analytic description

CERN Document Server

Grenzebach, Arne

2016-01-01

This book introduces an analytic method to describe the shadow of black holes. As an introduction, it presents a survey of the attempts to observe the shadow of galactic black holes. Based on a detailed discussion of the Plebański–Demiański class of space-times, the book derives analytical formulas for the photon regions and for the boundary curve of the shadow as seen by an observer in the domain of outer communication. It also analyzes how the shadow depends on the motion of the observer. For all cases, the photon regions and shadows are visualized for various values of the parameters. Finally, it considers how the analytical formulas can be used for calculating the horizontal and vertical angular diameters of the shadow, and estimates values for the black holes at the centers of our Galaxy near Sgr A* and of the neighboring galaxy M87.

Fast 3D Net Expeditions: Tools for Effective Scientific Collaboration on the World Wide Web

Science.gov (United States)

Watson, Val; Chancellor, Marisa K. (Technical Monitor)

1996-01-01

Two new technologies, the FASTexpedition and Remote FAST, have been developed that provide remote, 3D (three dimensional), high resolution, dynamic, interactive viewing of scientific data. The FASTexpedition permits one to access scientific data from the World Wide Web, take guided expeditions through the data, and continue with self controlled expeditions through the data. Remote FAST permits collaborators at remote sites to simultaneously view an analysis of scientific data being controlled by one of the collaborators. Control can be transferred between sites. These technologies are now being used for remote collaboration in joint university, industry, and NASA projects. Also, NASA Ames Research Center has initiated a project to make scientific data and guided expeditions through the data available as FASTexpeditions on the World Wide Web for educational purposes. Previously, remote visualization of dynamic data was done using video format (transmitting pixel information) such as video conferencing or MPEG (Motion Picture Expert Group) movies on the Internet. The concept for this new technology is to send the raw data (e.g., grids, vectors, and scalars) along with viewing scripts over the Internet and have the pixels generated by a visualization tool running on the viewers local workstation. The visualization tool that is currently used is FAST (Flow Analysis Software Toolkit). The advantages of this new technology over using video format are: (1) The visual is much higher in resolution (1280x1024 pixels with 24 bits of color) than typical video format transmitted over the network. (2) The form of the visualization can be controlled interactively (because the viewer is interactively controlling the visualization tool running on his workstation). (3) A rich variety of guided expeditions through the data can be included easily. (4) A capability is provided for other sites to see a visual analysis of one site as the analysis is interactively performed. Control of

Clustervision: Visual Supervision of Unsupervised Clustering.

Science.gov (United States)

Kwon, Bum Chul; Eysenbach, Ben; Verma, Janu; Ng, Kenney; De Filippi, Christopher; Stewart, Walter F; Perer, Adam

2018-01-01

Clustering, the process of grouping together similar items into distinct partitions, is a common type of unsupervised machine learning that can be useful for summarizing and aggregating complex multi-dimensional data. However, data can be clustered in many ways, and there exist a large body of algorithms designed to reveal different patterns. While having access to a wide variety of algorithms is helpful, in practice, it is quite difficult for data scientists to choose and parameterize algorithms to get the clustering results relevant for their dataset and analytical tasks. To alleviate this problem, we built Clustervision, a visual analytics tool that helps ensure data scientists find the right clustering among the large amount of techniques and parameters available. Our system clusters data using a variety of clustering techniques and parameters and then ranks clustering results utilizing five quality metrics. In addition, users can guide the system to produce more relevant results by providing task-relevant constraints on the data. Our visual user interface allows users to find high quality clustering results, explore the clusters using several coordinated visualization techniques, and select the cluster result that best suits their task. We demonstrate this novel approach using a case study with a team of researchers in the medical domain and showcase that our system empowers users to choose an effective representation of their complex data.

Advanced visualization technology for terascale particle accelerator simulations

International Nuclear Information System (INIS)

Ma, K-L; Schussman, G.; Wilson, B.; Ko, K.; Qiang, J.; Ryne, R.

2002-01-01

This paper presents two new hardware-assisted rendering techniques developed for interactive visualization of the terascale data generated from numerical modeling of next generation accelerator designs. The first technique, based on a hybrid rendering approach, makes possible interactive exploration of large-scale particle data from particle beam dynamics modeling. The second technique, based on a compact texture-enhanced representation, exploits the advanced features of commodity graphics cards to achieve perceptually effective visualization of the very dense and complex electromagnetic fields produced from the modeling of reflection and transmission properties of open structures in an accelerator design. Because of the collaborative nature of the overall accelerator modeling project, the visualization technology developed is for both desktop and remote visualization settings. We have tested the techniques using both time varying particle data sets containing up to one billion particle s per time step and electromagnetic field data sets with millions of mesh elements

State of the art of parallel scientific visualization applications on PC clusters

International Nuclear Information System (INIS)

Juliachs, M.

2004-01-01

In this state of the art on parallel scientific visualization applications on PC clusters, we deal with both surface and volume rendering approaches. We first analyze available PC cluster configurations and existing parallel rendering software components for parallel graphics rendering. CEA/DIF has been studying cluster visualization since 2001. This report is part of a study to set up a new visualization research platform. This platform consisting of an eight-node PC cluster under Linux and a tiled display was installed in collaboration with Versailles-Saint-Quentin University in August 2003. (author)

Visual Analytics in Public Safety: Example Capabilities for Example Government Agencies

Science.gov (United States)

2011-10-01

appelé « analytique visuel », lequel combine et approfondit les domaines de la visualisation de données et de l’analytique computationnel...Data Sources Data Analysis Analytic Reasoning Information Sharing Data types • Transaction • Image • Video • Text • Audio • Spatial...Broadcast Monitoring System creates a continuous, searchable, one-year archive of international television broadcasts. The real-time audio stream is

From Big Data to Big Displays High-Performance Visualization at Blue Brain

KAUST Repository

Eilemann, Stefan

2017-10-19

Blue Brain has pushed high-performance visualization (HPV) to complement its HPC strategy since its inception in 2007. In 2011, this strategy has been accelerated to develop innovative visualization solutions through increased funding and strategic partnerships with other research institutions. We present the key elements of this HPV ecosystem, which integrates C++ visualization applications with novel collaborative display systems. We motivate how our strategy of transforming visualization engines into services enables a variety of use cases, not only for the integration with high-fidelity displays, but also to build service oriented architectures, to link into web applications and to provide remote services to Python applications.

A critical reflexive Perspective on othering in collaborative knowledge production

DEFF Research Database (Denmark)

Jakobsen, Helle Nordentoft; Olesen, Birgitte Ravn

2018-01-01

Purpose The purpose of the article is to show power mechanisms of in- and exclusion in moments where certain participants appeared to be othered in two collaborative research and development projects in a health care setting. Design/methodology/approach The article contributes to critical......-reflexive analyses of reflexive processes within collaborative knowledge production We use an analytical framework combining Bakhtin and Foucault to investigate processes of inclusion and exclusion in the interplay between dominant and subordinated voices in a moment-by-moment analysis of two incidents from...... interdisciplinary workshops. Findings The analysis illuminates how differences between voices challenge participants’ reflexive awareness and lead to the reproduction of contextual power and knowledge hierarchies and the concomitant silencing of particular participants. Thus, the findings draw attention...

Visual Storytelling – Knowledge and Understanding in Education

Directory of Open Access Journals (Sweden)

Linnéa Stenliden

2012-10-01

Full Text Available This paper presents an ongoing research project of use and learning with geographic information visualization and Visual Storytelling (geovisual analytics in education. The fully developed study will be applied in school settings in order to 1 customize the application for educational purpose, 2 improve the teaching in social science and 3 study teachers and students experiences and learning. - The application "Open Statistics eXplorer" will be used to improve the students knowledge and understanding of sophisticated statistical relations, - Teachers will be able to, individually and together, develop a dynamic teaching material through storytelling, through the web, - Students will be able to, with help of powerful geographical statistics, explore statistical relations on their own. A better understanding of how educators and their students can elicit deeper user understanding and participation by exploiting dynamic web-enabled statistics visualization is of importance. Results from an usability study in this project are promising. Together with the associated science of perception in learning in relation to the use of multidimensional spatio-temporal statistical data this research will contribute to the research fields of geovisual analytics as well as educational science.

Reflexively exploring knowledge and power in collaborative research

DEFF Research Database (Denmark)

Nordentoft, Helle Merete; Phillips, Louise Jane; Pedersen, Christina Hee

will be designed in order to stimulate dialogue across different analytical perspectives and empirical research. The analytical perspectives on which facilitation will be based are rooted in social constructionist approaches to dialogic communication theory and action research. The challenges of collaborative...... knowledge forms, knowledge interests and wishes as to the research outcome. In official policy discourse and research practices, a positive picture is often painted of dialogue as a site for mutual learning on the basis of the different knowledge forms that the different participants bring with them...... of mutual learning. There are also tensions between processes of opening up for a plurality of knowledges and processes of closure in order to achieve strategic ends in the form of some kind of outcome. The basic premise underpinning this workshop is that we as researchers can best deal...

Creativity, Complexity, and Precision: Information Visualization for (Landscape) Architecture

DEFF Research Database (Denmark)

Buscher, Monika; Christensen, Michael; Mogensen, Preben Holst

2000-01-01

Drawing on ethnographic studies of (landscape) architects at work, this paper presents a human-centered approach to information visualization. A 3D collaborative electronic workspace allows people to configure, save and browse arrangements of heterogeneous work materials. Spatial arrangements...... and links are created and maintained as an integral part of ongoing work with `live' documents and objects. The result is an extension of the physical information space of the architects' studio that utilizes the potential of electronic data storage, visualization and network technologies to support work...... with information in context...

LATUX: An Iterative Workflow for Designing, Validating, and Deploying Learning Analytics Visualizations

Science.gov (United States)

Martinez-Maldonado, Roberto; Pardo, Abelardo; Mirriahi, Negin; Yacef, Kalina; Kay, Judy; Clayphan, Andrew

2015-01-01

Designing, validating, and deploying learning analytics tools for instructors or students is a challenge that requires techniques and methods from different disciplines, such as software engineering, human-computer interaction, computer graphics, educational design, and psychology. Whilst each has established its own design methodologies, we now…

MapRat: Meaningful Explanation, Interactive Exploration and Geo-Visualization of Collaborative Ratings

OpenAIRE

Thirumuruganathan , Saravanan; Das , Mahashweta; Desai , Shrikant; Amer-Yahia , Sihem; Das , Gautam; Yu , Cong

2012-01-01

ISSN: 2150-8097 - www.vldb2012.org - Demonstration session: Information Retrieval, Web, and Mobility at VLDB 2012 (Very Large Data Bases Conference, Istanbul, Turkey, 2012); International audience; Collaborative rating sites such as IMDB and Yelp have become rich resources that users consult to form judgments about and choose from among competing items. Most of these sites either provide a plethora of information for users to interpret all by themselves or a simple overall aggregate informati...

The Application of Visual Basic Computer Programming Language to Simulate Numerical Iterations

Directory of Open Access Journals (Sweden)

Abdulkadir Baba HASSAN

2006-06-01

Full Text Available This paper examines the application of Visual Basic Computer Programming Language to Simulate Numerical Iterations, the merit of Visual Basic as a Programming Language and the difficulties faced when solving numerical iterations analytically, this research paper encourage the uses of Computer Programming methods for the execution of numerical iterations and finally fashion out and develop a reliable solution using Visual Basic package to write a program for some selected iteration problems.

Fast analytical scatter estimation using graphics processing units.

Science.gov (United States)

Ingleby, Harry; Lippuner, Jonas; Rickey, Daniel W; Li, Yue; Elbakri, Idris

2015-01-01

To develop a fast patient-specific analytical estimator of first-order Compton and Rayleigh scatter in cone-beam computed tomography, implemented using graphics processing units. The authors developed an analytical estimator for first-order Compton and Rayleigh scatter in a cone-beam computed tomography geometry. The estimator was coded using NVIDIA's CUDA environment for execution on an NVIDIA graphics processing unit. Performance of the analytical estimator was validated by comparison with high-count Monte Carlo simulations for two different numerical phantoms. Monoenergetic analytical simulations were compared with monoenergetic and polyenergetic Monte Carlo simulations. Analytical and Monte Carlo scatter estimates were compared both qualitatively, from visual inspection of images and profiles, and quantitatively, using a scaled root-mean-square difference metric. Reconstruction of simulated cone-beam projection data of an anthropomorphic breast phantom illustrated the potential of this method as a component of a scatter correction algorithm. The monoenergetic analytical and Monte Carlo scatter estimates showed very good agreement. The monoenergetic analytical estimates showed good agreement for Compton single scatter and reasonable agreement for Rayleigh single scatter when compared with polyenergetic Monte Carlo estimates. For a voxelized phantom with dimensions 128 × 128 × 128 voxels and a detector with 256 × 256 pixels, the analytical estimator required 669 seconds for a single projection, using a single NVIDIA 9800 GX2 video card. Accounting for first order scatter in cone-beam image reconstruction improves the contrast to noise ratio of the reconstructed images. The analytical scatter estimator, implemented using graphics processing units, provides rapid and accurate estimates of single scatter and with further acceleration and a method to account for multiple scatter may be useful for practical scatter correction schemes.

Implementing Operational Analytics using Big Data Technologies to Detect and Predict Sensor Anomalies

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