WorldWideScience

Sample records for integrating ontological knowledge

  1. Fuzzy knowledge bases integration based on ontology

    OpenAIRE

    Ternovoy, Maksym; Shtogrina, Olena

    2012-01-01

    the paper describes the approach for fuzzy knowledge bases integration with the usage of ontology. This approach is based on metadata-base usage for integration of different knowledge bases with common ontology. The design process of metadata-base is described.

  2. Integrating Ontological Knowledge and Textual Evidence in Estimating Gene and Gene Product Similarity

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Posse, Christian; Gopalan, Banu; Tratz, Stephen C.; Gregory, Michelle L.

    2006-06-08

    With the rising influence of the Gene On-tology, new approaches have emerged where the similarity between genes or gene products is obtained by comparing Gene Ontology code annotations associ-ated with them. So far, these approaches have solely relied on the knowledge en-coded in the Gene Ontology and the gene annotations associated with the Gene On-tology database. The goal of this paper is to demonstrate that improvements to these approaches can be obtained by integrating textual evidence extracted from relevant biomedical literature.

  3. BOWiki: an ontology-based wiki for annotation of data and integration of knowledge in biology

    Directory of Open Access Journals (Sweden)

    Gregorio Sergio E

    2009-05-01

    Full Text Available Abstract Motivation Ontology development and the annotation of biological data using ontologies are time-consuming exercises that currently require input from expert curators. Open, collaborative platforms for biological data annotation enable the wider scientific community to become involved in developing and maintaining such resources. However, this openness raises concerns regarding the quality and correctness of the information added to these knowledge bases. The combination of a collaborative web-based platform with logic-based approaches and Semantic Web technology can be used to address some of these challenges and concerns. Results We have developed the BOWiki, a web-based system that includes a biological core ontology. The core ontology provides background knowledge about biological types and relations. Against this background, an automated reasoner assesses the consistency of new information added to the knowledge base. The system provides a platform for research communities to integrate information and annotate data collaboratively. Availability The BOWiki and supplementary material is available at http://www.bowiki.net/. The source code is available under the GNU GPL from http://onto.eva.mpg.de/trac/BoWiki.

  4. Exploration and implementation of ontology-based cultural relic knowledge map integration platform

    Science.gov (United States)

    Yang, Weiqiang; Dong, Yiqiang

    2018-05-01

    To help designers to better carry out creative design and improve the ability of searching traditional cultural relic information, the ontology-based knowledge map construction method was explored and an integrated platform for cultural relic knowledge map was developed. First of all, the construction method of the ontology of cultural relics was put forward, and the construction of the knowledge map of cultural relics was completed based on the constructed cultural relic otology. Then, a personalized semantic retrieval framework for creative design was proposed. Finally, the integrated platform of the knowledge map of cultural relics was designed and realized. The platform was divided into two parts. One was the foreground display system, which was used for designers to search and browse cultural relics. The other was the background management system, which was for cultural experts to manage cultural relics' knowledge. The research results showed that the platform designed could improve the retrieval ability of cultural relic information. To sum up, the platform can provide a good support for the designer's creative design.

  5. Ontologies, Knowledge Bases and Knowledge Management

    National Research Council Canada - National Science Library

    Chalupsky, Hans

    2002-01-01

    ...) an application called Strategy Development Assistant (SDA) that uses that ontology. The JFACC ontology served as a basis for knowledge sharing among several applications in the domain of air campaign planning...

  6. development of ontological knowledge representation

    African Journals Online (AJOL)

    Preferred Customer

    ABSTRACT. This paper presents the development of an ontological knowledge organization and .... intelligence in order to facilitate knowledge sharing and reuse of acquired knowledge (15). Soon, ..... Water Chemistry, AJCE, 1(2), 50-58. 25.

  7. Ontology modeling in physical asset integrity management

    CERN Document Server

    Yacout, Soumaya

    2015-01-01

    This book presents cutting-edge applications of, and up-to-date research on, ontology engineering techniques in the physical asset integrity domain. Though a survey of state-of-the-art theory and methods on ontology engineering, the authors emphasize essential topics including data integration modeling, knowledge representation, and semantic interpretation. The book also reflects novel topics dealing with the advanced problems of physical asset integrity applications such as heterogeneity, data inconsistency, and interoperability existing in design and utilization. With a distinctive focus on applications relevant in heavy industry, Ontology Modeling in Physical Asset Integrity Management is ideal for practicing industrial and mechanical engineers working in the field, as well as researchers and graduate concerned with ontology engineering in physical systems life cycles. This book also: Introduces practicing engineers, research scientists, and graduate students to ontology engineering as a modeling techniqu...

  8. Knowledge Portals: Ontologies at Work

    OpenAIRE

    Staab, Steffen; Maedche, Alexander

    2001-01-01

    Knowledge portals provide views onto domain-specific information on the World Wide Web, thus helping their users find relevant, domain-specific information. The construction of intelligent access and the contribution of information to knowledge portals, however, remained an ad hoc task, requiring extensive manual editing and maintenance by the knowledge portal providers. To diminish these efforts, we use ontologies as a conceptual backbone for providing, accessing, and structuring information...

  9. Ontology-based data integration from heterogeneous urban systems : A knowledge representation framework for smart cities

    NARCIS (Netherlands)

    Psyllidis, A.

    2015-01-01

    This paper presents a novel knowledge representation framework for smart city planning and management that enables the semantic integration of heterogeneous urban data from diverse sources. Currently, the combination of information across city agencies is cumbersome, as the increasingly available

  10. Knowledge Representation and Ontologies

    Science.gov (United States)

    Grimm, Stephan

    Knowledge representation and reasoning aims at designing computer systems that reason about a machine-interpretable representation of the world. Knowledge-based systems have a computational model of some domain of interest in which symbols serve as surrogates for real world domain artefacts, such as physical objects, events, relationships, etc. [1]. The domain of interest can cover any part of the real world or any hypothetical system about which one desires to represent knowledge for com-putational purposes. A knowledge-based system maintains a knowledge base, which stores the symbols of the computational model in the form of statements about the domain, and it performs reasoning by manipulating these symbols. Applications can base their decisions on answers to domain-relevant questions posed to a knowledge base.

  11. An Ontology for Knowledge Representation and Applications

    OpenAIRE

    Nhon Do

    2008-01-01

    Ontology is a terminology which is used in artificial intelligence with different meanings. Ontology researching has an important role in computer science and practical applications, especially distributed knowledge systems. In this paper we present an ontology which is called Computational Object Knowledge Base Ontology. It has been used in designing some knowledge base systems for solving problems such as the system that supports studying knowledge and solving analytic ...

  12. Concepts, ontologies, and knowledge representation

    CERN Document Server

    Jakus, Grega; Omerovic, Sanida; Tomažic, Sašo

    2013-01-01

    Recording knowledge in a common framework that would make it possible to seamlessly share global knowledge remains an important challenge for researchers. This brief examines several ideas about the representation of knowledge addressing this challenge. A widespread general agreement is followed that states uniform knowledge representation should be achievable by using ontologies populated with concepts. A separate chapter is dedicated to each of the three introduced topics, following a uniform outline: definition, organization, and use. This brief is intended for those who want to get to know

  13. Formal Ontologies and Uncertainty. In Geographical Knowledge

    Directory of Open Access Journals (Sweden)

    Matteo Caglioni

    2014-05-01

    Full Text Available Formal ontologies have proved to be a very useful tool to manage interoperability among data, systems and knowledge. In this paper we will show how formal ontologies can evolve from a crisp, deterministic framework (ontologies of hard knowledge to new probabilistic, fuzzy or possibilistic frameworks (ontologies of soft knowledge. This can considerably enlarge the application potential of formal ontologies in geographic analysis and planning, where soft knowledge is intrinsically linked to the complexity of the phenomena under study.  The paper briefly presents these new uncertainty-based formal ontologies. It then highlights how ontologies are formal tools to define both concepts and relations among concepts. An example from the domain of urban geography finally shows how the cause-to-effect relation between household preferences and urban sprawl can be encoded within a crisp, a probabilistic and a possibilistic ontology, respectively. The ontology formalism will also determine the kind of reasoning that can be developed from available knowledge. Uncertain ontologies can be seen as the preliminary phase of more complex uncertainty-based models. The advantages of moving to uncertainty-based models is evident: whether it is in the analysis of geographic space or in decision support for planning, reasoning on geographic space is almost always reasoning with uncertain knowledge of geographic phenomena.

  14. Integrating systems biology models and biomedical ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Dumontier, Michel; Gennari, John H; Wimalaratne, Sarala; de Bono, Bernard; Cook, Daniel L; Gkoutos, Georgios V

    2011-08-11

    Systems biology is an approach to biology that emphasizes the structure and dynamic behavior of biological systems and the interactions that occur within them. To succeed, systems biology crucially depends on the accessibility and integration of data across domains and levels of granularity. Biomedical ontologies were developed to facilitate such an integration of data and are often used to annotate biosimulation models in systems biology. We provide a framework to integrate representations of in silico systems biology with those of in vivo biology as described by biomedical ontologies and demonstrate this framework using the Systems Biology Markup Language. We developed the SBML Harvester software that automatically converts annotated SBML models into OWL and we apply our software to those biosimulation models that are contained in the BioModels Database. We utilize the resulting knowledge base for complex biological queries that can bridge levels of granularity, verify models based on the biological phenomenon they represent and provide a means to establish a basic qualitative layer on which to express the semantics of biosimulation models. We establish an information flow between biomedical ontologies and biosimulation models and we demonstrate that the integration of annotated biosimulation models and biomedical ontologies enables the verification of models as well as expressive queries. Establishing a bi-directional information flow between systems biology and biomedical ontologies has the potential to enable large-scale analyses of biological systems that span levels of granularity from molecules to organisms.

  15. Knowledge engineering as a support for building an actor profile ontology for integrating Home-Care systems.

    Science.gov (United States)

    Gibert, Karina; Valls, Aida; Riaño, David

    2008-01-01

    One of the tasks towards the definition of a knowledge model for home care is the definition of the different roles of the users involved in the system. The roles determine the actions and services that can or must be performed by each type of user. In this paper the experience of building an ontology to represent the home-care users and their associated information is presented, in a proposal for a standard model of a Home-Care support system to the European Community.

  16. Aspects of ontology visualization and integration

    NARCIS (Netherlands)

    Dmitrieva, Joelia Borisovna

    2011-01-01

    In this thesis we will describe and discuss methodologies for ontology visualization and integration. Two visualization methods will be elaborated. In one method the ontology is visualized with the node-link technique, and with the other method the ontology is visualized with the containment

  17. Applications of Ontologies in Knowledge Management Systems

    Science.gov (United States)

    Rehman, Zobia; Kifor, Claudiu V.

    2014-12-01

    Enterprises are realizing that their core asset in 21st century is knowledge. In an organization knowledge resides in databases, knowledge bases, filing cabinets and peoples' head. Organizational knowledge is distributed in nature and its poor management causes repetition of activities across the enterprise. To get true benefits from this asset, it is important for an organization to "know what they know". That's why many organizations are investing a lot in managing their knowledge. Artificial intelligence techniques have a huge contribution in organizational knowledge management. In this article we are reviewing the applications of ontologies in knowledge management realm

  18. USE OF ONTOLOGIES FOR KNOWLEDGE BASES CREATION TUTORING COMPUTER SYSTEMS

    Directory of Open Access Journals (Sweden)

    Cheremisina Lyubov

    2014-11-01

    Full Text Available This paper deals with the use of ontology for the use and development of intelligent tutoring systems. We consider the shortcomings of educational software and distance learning systems and the advantages of using ontology’s in their design. Actuality creates educational computer systems based on systematic knowledge. We consider classification of properties, use and benefits of ontology’s. Characterized approaches to the problem of ontology mapping, the first of which – manual mapping, the second – a comparison of the names of concepts based on their lexical similarity and using special dictionaries. The analysis of languages available for the formal description of ontology. Considered a formal mathematical model of ontology’s and ontology consistency problem, which is that different developers for the same domain ontology can be created, syntactically or semantically heterogeneous, and their use requires a compatible broadcast or display. An algorithm combining ontology’s. The characteristic of the practical value of developing an ontology for electronic educational resources and recommendations for further research and development, such as implementation of other components of the system integration, formalization of the processes of integration and development of a universal expansion algorithms ontology’s software

  19. The Ontology of Knowledge Based Optimization

    OpenAIRE

    Nasution, Mahyuddin K. M.

    2012-01-01

    Optimization has been becoming a central of studies in mathematic and has many areas with different applications. However, many themes of optimization came from different area have not ties closing to origin concepts. This paper is to address some variants of optimization problems using ontology in order to building basic of knowledge about optimization, and then using it to enhance strategy to achieve knowledge based optimization.

  20. A Knowledge Engineering Approach to Develop Domain Ontology

    Science.gov (United States)

    Yun, Hongyan; Xu, Jianliang; Xiong, Jing; Wei, Moji

    2011-01-01

    Ontologies are one of the most popular and widespread means of knowledge representation and reuse. A few research groups have proposed a series of methodologies for developing their own standard ontologies. However, because this ontological construction concerns special fields, there is no standard method to build domain ontology. In this paper,…

  1. Drug target ontology to classify and integrate drug discovery data

    DEFF Research Database (Denmark)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande

    2017-01-01

    using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem...... of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target...... characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. CONCLUSIONS: DTO was built based on the need for a formal semantic model for druggable targets including various related information such as protein, gene, protein...

  2. Construction of Engineering Ontologies for Knowledge Sharing and Reuse

    NARCIS (Netherlands)

    Borst, Willem Nico; Borst, W.N.

    1997-01-01

    This thesis describes an investigation into the practical use of ontologies for the development of information systems. Ontologies are formal descriptions of shared knowledge in a domain. An ontology can be used as a specification of an information system because it specifies the knowledge that is

  3. Ontology alignment architecture for semantic sensor Web integration.

    Science.gov (United States)

    Fernandez, Susel; Marsa-Maestre, Ivan; Velasco, Juan R; Alarcos, Bernardo

    2013-09-18

    Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity). Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity's names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI) tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  4. Ontology Alignment Architecture for Semantic Sensor Web Integration

    Directory of Open Access Journals (Sweden)

    Bernardo Alarcos

    2013-09-01

    Full Text Available Sensor networks are a concept that has become very popular in data acquisition and processing for multiple applications in different fields such as industrial, medicine, home automation, environmental detection, etc. Today, with the proliferation of small communication devices with sensors that collect environmental data, semantic Web technologies are becoming closely related with sensor networks. The linking of elements from Semantic Web technologies with sensor networks has been called Semantic Sensor Web and has among its main features the use of ontologies. One of the key challenges of using ontologies in sensor networks is to provide mechanisms to integrate and exchange knowledge from heterogeneous sources (that is, dealing with semantic heterogeneity. Ontology alignment is the process of bringing ontologies into mutual agreement by the automatic discovery of mappings between related concepts. This paper presents a system for ontology alignment in the Semantic Sensor Web which uses fuzzy logic techniques to combine similarity measures between entities of different ontologies. The proposed approach focuses on two key elements: the terminological similarity, which takes into account the linguistic and semantic information of the context of the entity’s names, and the structural similarity, based on both the internal and relational structure of the concepts. This work has been validated using sensor network ontologies and the Ontology Alignment Evaluation Initiative (OAEI tests. The results show that the proposed techniques outperform previous approaches in terms of precision and recall.

  5. A Proposition Of Knowledge Management Methodology For The Purpose Of Reasoning With The Use Of An Upper-Ontology

    Directory of Open Access Journals (Sweden)

    Kamil Szymański

    2007-01-01

    Full Text Available This article describes a proposition of knowledge organization for the purpose of reasoningusing an upper-ontology. It presents a model of integrated ontologies architecture whichconsists of a domain ontologies layer with instances, a shared upper-ontology layer withadditional rules and a layer of ontologies mapping concrete domain ontologies with the upperontology.Thanks to the upper-ontology, new facts were concluded from domain ontologiesduring the reasoning process. A practical realization proposition is given as well. It is basedon some popular SemanticWeb technologies and tools, such as OWL, SWRL, nRQL, Prot´eg´eand Racer.

  6. Integrating phenotype ontologies with PhenomeNET

    KAUST Repository

    Rodriguez-Garcia, Miguel Angel

    2017-12-19

    Background Integration and analysis of phenotype data from humans and model organisms is a key challenge in building our understanding of normal biology and pathophysiology. However, the range of phenotypes and anatomical details being captured in clinical and model organism databases presents complex problems when attempting to match classes across species and across phenotypes as diverse as behaviour and neoplasia. We have previously developed PhenomeNET, a system for disease gene prioritization that includes as one of its components an ontology designed to integrate phenotype ontologies. While not applicable to matching arbitrary ontologies, PhenomeNET can be used to identify related phenotypes in different species, including human, mouse, zebrafish, nematode worm, fruit fly, and yeast. Results Here, we apply the PhenomeNET to identify related classes from two phenotype and two disease ontologies using automated reasoning. We demonstrate that we can identify a large number of mappings, some of which require automated reasoning and cannot easily be identified through lexical approaches alone. Combining automated reasoning with lexical matching further improves results in aligning ontologies. Conclusions PhenomeNET can be used to align and integrate phenotype ontologies. The results can be utilized for biomedical analyses in which phenomena observed in model organisms are used to identify causative genes and mutations underlying human disease.

  7. The MMI Device Ontology: Enabling Sensor Integration

    Science.gov (United States)

    Rueda, C.; Galbraith, N.; Morris, R. A.; Bermudez, L. E.; Graybeal, J.; Arko, R. A.; Mmi Device Ontology Working Group

    2010-12-01

    The Marine Metadata Interoperability (MMI) project has developed an ontology for devices to describe sensors and sensor networks. This ontology is implemented in the W3C Web Ontology Language (OWL) and provides an extensible conceptual model and controlled vocabularies for describing heterogeneous instrument types, with different data characteristics, and their attributes. It can help users populate metadata records for sensors; associate devices with their platforms, deployments, measurement capabilities and restrictions; aid in discovery of sensor data, both historic and real-time; and improve the interoperability of observational oceanographic data sets. We developed the MMI Device Ontology following a community-based approach. By building on and integrating other models and ontologies from related disciplines, we sought to facilitate semantic interoperability while avoiding duplication. Key concepts and insights from various communities, including the Open Geospatial Consortium (eg., SensorML and Observations and Measurements specifications), Semantic Web for Earth and Environmental Terminology (SWEET), and W3C Semantic Sensor Network Incubator Group, have significantly enriched the development of the ontology. Individuals ranging from instrument designers, science data producers and consumers to ontology specialists and other technologists contributed to the work. Applications of the MMI Device Ontology are underway for several community use cases. These include vessel-mounted multibeam mapping sonars for the Rolling Deck to Repository (R2R) program and description of diverse instruments on deepwater Ocean Reference Stations for the OceanSITES program. These trials involve creation of records completely describing instruments, either by individual instances or by manufacturer and model. Individual terms in the MMI Device Ontology can be referenced with their corresponding Uniform Resource Identifiers (URIs) in sensor-related metadata specifications (e

  8. Drug target ontology to classify and integrate drug discovery data.

    Science.gov (United States)

    Lin, Yu; Mehta, Saurabh; Küçük-McGinty, Hande; Turner, John Paul; Vidovic, Dusica; Forlin, Michele; Koleti, Amar; Nguyen, Dac-Trung; Jensen, Lars Juhl; Guha, Rajarshi; Mathias, Stephen L; Ursu, Oleg; Stathias, Vasileios; Duan, Jianbin; Nabizadeh, Nooshin; Chung, Caty; Mader, Christopher; Visser, Ubbo; Yang, Jeremy J; Bologa, Cristian G; Oprea, Tudor I; Schürer, Stephan C

    2017-11-09

    One of the most successful approaches to develop new small molecule therapeutics has been to start from a validated druggable protein target. However, only a small subset of potentially druggable targets has attracted significant research and development resources. The Illuminating the Druggable Genome (IDG) project develops resources to catalyze the development of likely targetable, yet currently understudied prospective drug targets. A central component of the IDG program is a comprehensive knowledge resource of the druggable genome. As part of that effort, we have developed a framework to integrate, navigate, and analyze drug discovery data based on formalized and standardized classifications and annotations of druggable protein targets, the Drug Target Ontology (DTO). DTO was constructed by extensive curation and consolidation of various resources. DTO classifies the four major drug target protein families, GPCRs, kinases, ion channels and nuclear receptors, based on phylogenecity, function, target development level, disease association, tissue expression, chemical ligand and substrate characteristics, and target-family specific characteristics. The formal ontology was built using a new software tool to auto-generate most axioms from a database while supporting manual knowledge acquisition. A modular, hierarchical implementation facilitate ontology development and maintenance and makes use of various external ontologies, thus integrating the DTO into the ecosystem of biomedical ontologies. As a formal OWL-DL ontology, DTO contains asserted and inferred axioms. Modeling data from the Library of Integrated Network-based Cellular Signatures (LINCS) program illustrates the potential of DTO for contextual data integration and nuanced definition of important drug target characteristics. DTO has been implemented in the IDG user interface Portal, Pharos and the TIN-X explorer of protein target disease relationships. DTO was built based on the need for a formal semantic

  9. PDON: Parkinson's disease ontology for representation and modeling of the Parkinson's disease knowledge domain.

    Science.gov (United States)

    Younesi, Erfan; Malhotra, Ashutosh; Gündel, Michaela; Scordis, Phil; Kodamullil, Alpha Tom; Page, Matt; Müller, Bernd; Springstubbe, Stephan; Wüllner, Ullrich; Scheller, Dieter; Hofmann-Apitius, Martin

    2015-09-22

    Despite the unprecedented and increasing amount of data, relatively little progress has been made in molecular characterization of mechanisms underlying Parkinson's disease. In the area of Parkinson's research, there is a pressing need to integrate various pieces of information into a meaningful context of presumed disease mechanism(s). Disease ontologies provide a novel means for organizing, integrating, and standardizing the knowledge domains specific to disease in a compact, formalized and computer-readable form and serve as a reference for knowledge exchange or systems modeling of disease mechanism. The Parkinson's disease ontology was built according to the life cycle of ontology building. Structural, functional, and expert evaluation of the ontology was performed to ensure the quality and usability of the ontology. A novelty metric has been introduced to measure the gain of new knowledge using the ontology. Finally, a cause-and-effect model was built around PINK1 and two gene expression studies from the Gene Expression Omnibus database were re-annotated to demonstrate the usability of the ontology. The Parkinson's disease ontology with a subclass-based taxonomic hierarchy covers the broad spectrum of major biomedical concepts from molecular to clinical features of the disease, and also reflects different views on disease features held by molecular biologists, clinicians and drug developers. The current version of the ontology contains 632 concepts, which are organized under nine views. The structural evaluation showed the balanced dispersion of concept classes throughout the ontology. The functional evaluation demonstrated that the ontology-driven literature search could gain novel knowledge not present in the reference Parkinson's knowledge map. The ontology was able to answer specific questions related to Parkinson's when evaluated by experts. Finally, the added value of the Parkinson's disease ontology is demonstrated by ontology-driven modeling of PINK1

  10. Ontology-centric integration and navigation of the dengue literature.

    Science.gov (United States)

    Rajapakse, Menaka; Kanagasabai, Rajaraman; Ang, Wee Tiong; Veeramani, Anitha; Schreiber, Mark J; Baker, Christopher J O

    2008-10-01

    Uninhibited access to the unstructured information distributed across the web and in scientific literature databases continues to be beyond the reach of scientists and health professionals. To address this challenge we have developed a literature driven, ontology-centric navigation infrastructure consisting of a content acquisition engine, a domain-specific ontology (in OWL-DL) and an ontology instantiation pipeline delivering sentences derived by domain-specific text mining. A visual query tool for reasoning over A-box instances in the populated ontology is presented and used to build conceptual queries that can be issued to the knowledgebase. We have deployed this generic infrastructure to facilitate data integration and knowledge sharing in the domain of dengue, which is one of the most prevalent viral diseases that continue to infect millions of people in the tropical and subtropical regions annually. Using our unique methodology we illustrate simplified search and discovery on dengue information derived from distributed resources and aggregated according to dengue ontology. Furthermore we apply data mining to the instantiated ontology to elucidate trends in the mentions of dengue serotypes in scientific abstracts since 1974.

  11. Knowledge Representation in Patient Safety Reporting: An Ontological Approach

    Directory of Open Access Journals (Sweden)

    Liang Chen

    2016-10-01

    Full Text Available Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our design, implementation, and evaluation of the ontology at its initial stage. Findings: We describe the design and initial outcomes of the ontology implementation. The evaluation results demonstrate the clinical validity of the ontology by a self-developed survey measurement. Research limitations: The proposed ontology was developed and evaluated using a small number of information sources. Presently, US data are used, but they are not essential for the ultimate structure of the ontology. Practical implications: The goal of improving patient safety can be aided through investigating patient safety reports and providing actionable knowledge to clinical practitioners. As such, constructing a domain specific ontology for patient safety reports serves as a cornerstone in information collection and text mining methods. Originality/value: The use of ontologies provides abstracted representation of semantic information and enables a wealth of applications in a reporting system. Therefore, constructing such a knowledge base is recognized as a high priority in health care.

  12. ADO: a disease ontology representing the domain knowledge specific to Alzheimer's disease.

    Science.gov (United States)

    Malhotra, Ashutosh; Younesi, Erfan; Gündel, Michaela; Müller, Bernd; Heneka, Michael T; Hofmann-Apitius, Martin

    2014-03-01

    Biomedical ontologies offer the capability to structure and represent domain-specific knowledge semantically. Disease-specific ontologies can facilitate knowledge exchange across multiple disciplines, and ontology-driven mining approaches can generate great value for modeling disease mechanisms. However, in the case of neurodegenerative diseases such as Alzheimer's disease, there is a lack of formal representation of the relevant knowledge domain. Alzheimer's disease ontology (ADO) is constructed in accordance to the ontology building life cycle. The Protégé OWL editor was used as a tool for building ADO in Ontology Web Language format. ADO was developed with the purpose of containing information relevant to four main biological views-preclinical, clinical, etiological, and molecular/cellular mechanisms-and was enriched by adding synonyms and references. Validation of the lexicalized ontology by means of named entity recognition-based methods showed a satisfactory performance (F score = 72%). In addition to structural and functional evaluation, a clinical expert in the field performed a manual evaluation and curation of ADO. Through integration of ADO into an information retrieval environment, we show that the ontology supports semantic search in scientific text. The usefulness of ADO is authenticated by dedicated use case scenarios. Development of ADO as an open ADO is a first attempt to organize information related to Alzheimer's disease in a formalized, structured manner. We demonstrate that ADO is able to capture both established and scattered knowledge existing in scientific text. Copyright © 2014 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.

  13. Knowledge Representation in Patient Safety Reporting: An Ontological Approach

    OpenAIRE

    Liang Chen; Yang Gong

    2016-01-01

    Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/methodology/approach: We propose a framework for constructing an ontological knowledge base of patient safety. The present paper describes our desig...

  14. The National Center for Biomedical Ontology: Advancing Biomedicinethrough Structured Organization of Scientific Knowledge

    Energy Technology Data Exchange (ETDEWEB)

    Rubin, Daniel L.; Lewis, Suzanna E.; Mungall, Chris J.; Misra,Sima; Westerfield, Monte; Ashburner, Michael; Sim, Ida; Chute,Christopher G.; Solbrig, Harold; Storey, Margaret-Anne; Smith, Barry; Day-Richter, John; Noy, Natalya F.; Musen, Mark A.

    2006-01-23

    The National Center for Biomedical Ontology (http://bioontology.org) is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists funded by the NIH Roadmap to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are: (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. The Center is working toward these objectives by providing tools to develop ontologies and to annotate experimental data, and by developing resources to integrate and relate existing ontologies as well as by creating repositories of biomedical data that are annotated using those ontologies. The Center is providing training workshops in ontology design, development, and usage, and is also pursuing research in ontology evaluation, quality, and use of ontologies to promote scientific discovery. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease.

  15. A modeling ontology for integrating vulnerabilities into security requirements conceptual foundations

    NARCIS (Netherlands)

    Elahi, G.; Yu, E.; Zannone, N.; Laender, A.H.F.; Castano, S.; Dayal, U.; Casati, F.; Palazzo Moreira de Oliveira, J.

    2009-01-01

    Vulnerabilities are weaknesses in the requirements, design, and implementation, which attackers exploit to compromise the system. This paper proposes a vulnerability-centric modeling ontology, which aims to integrate empirical knowledge of vulnerabilities into the system development process. In

  16. The Status Quo of Ontology Learning from Unstructured Knowledge Sources for Knowledge Management

    OpenAIRE

    Scheuermann , Andreas; Obermann , Jens

    2012-01-01

    International audience; In the global race for competitive advantage Knowledge Management gains increasing importance for companies. The purposeful and systematic creation, maintenance, and transfer of unstructured knowledge sources demands for advanced Information Technology. Ontologies constitute a basic ingredient of Knowledge Management; thus, ontology learning from unstructured knowledge sources is of particular interest since it bears the potential to bring significant advantages for Kn...

  17. USE OF ONTOLOGIES FOR KNOWLEDGE BASES CREATION TUTORING COMPUTER SYSTEMS

    OpenAIRE

    Cheremisina Lyubov

    2014-01-01

    This paper deals with the use of ontology for the use and development of intelligent tutoring systems. We consider the shortcomings of educational software and distance learning systems and the advantages of using ontology’s in their design. Actuality creates educational computer systems based on systematic knowledge. We consider classification of properties, use and benefits of ontology’s. Characterized approaches to the problem of ontology mapping, the first of which – manual mapping, the s...

  18. Summarizing an Ontology: A "Big Knowledge" Coverage Approach.

    Science.gov (United States)

    Zheng, Ling; Perl, Yehoshua; Elhanan, Gai; Ochs, Christopher; Geller, James; Halper, Michael

    2017-01-01

    Maintenance and use of a large ontology, consisting of thousands of knowledge assertions, are hampered by its scope and complexity. It is important to provide tools for summarization of ontology content in order to facilitate user "big picture" comprehension. We present a parameterized methodology for the semi-automatic summarization of major topics in an ontology, based on a compact summary of the ontology, called an "aggregate partial-area taxonomy", followed by manual enhancement. An experiment is presented to test the effectiveness of such summarization measured by coverage of a given list of major topics of the corresponding application domain. SNOMED CT's Specimen hierarchy is the test-bed. A domain-expert provided a list of topics that serves as a gold standard. The enhanced results show that the aggregate taxonomy covers most of the domain's main topics.

  19. Towards Ontology as Knowledge Representation for Intellectual Capital Measurement

    Science.gov (United States)

    Zadjabbari, B.; Wongthongtham, P.; Dillon, T. S.

    For many years, physical asset indicators were the main evidence of an organization’s successful performance. However, the situation has changed after information technology revolution in the knowledge-based economy. Since 1980’s business performance has not been limited only to physical assets instead intellectual capital are increasingly playing a major role in business performance. In this paper, we utilize ontology as a tool for knowledge representation in the domain of intellectual capital measurement. The ontology classifies ways of intangible capital measurement.

  20. Improving Interpretation of Cardiac Phenotypes and Enhancing Discovery With Expanded Knowledge in the Gene Ontology.

    Science.gov (United States)

    Lovering, Ruth C; Roncaglia, Paola; Howe, Douglas G; Laulederkind, Stanley J F; Khodiyar, Varsha K; Berardini, Tanya Z; Tweedie, Susan; Foulger, Rebecca E; Osumi-Sutherland, David; Campbell, Nancy H; Huntley, Rachael P; Talmud, Philippa J; Blake, Judith A; Breckenridge, Ross; Riley, Paul R; Lambiase, Pier D; Elliott, Perry M; Clapp, Lucie; Tinker, Andrew; Hill, David P

    2018-02-01

    A systems biology approach to cardiac physiology requires a comprehensive representation of how coordinated processes operate in the heart, as well as the ability to interpret relevant transcriptomic and proteomic experiments. The Gene Ontology (GO) Consortium provides structured, controlled vocabularies of biological terms that can be used to summarize and analyze functional knowledge for gene products. In this study, we created a computational resource to facilitate genetic studies of cardiac physiology by integrating literature curation with attention to an improved and expanded ontological representation of heart processes in the Gene Ontology. As a result, the Gene Ontology now contains terms that comprehensively describe the roles of proteins in cardiac muscle cell action potential, electrical coupling, and the transmission of the electrical impulse from the sinoatrial node to the ventricles. Evaluating the effectiveness of this approach to inform data analysis demonstrated that Gene Ontology annotations, analyzed within an expanded ontological context of heart processes, can help to identify candidate genes associated with arrhythmic disease risk loci. We determined that a combination of curation and ontology development for heart-specific genes and processes supports the identification and downstream analysis of genes responsible for the spread of the cardiac action potential through the heart. Annotating these genes and processes in a structured format facilitates data analysis and supports effective retrieval of gene-centric information about cardiac defects. © 2018 The Authors.

  1. Constructing Ontology for Knowledge Sharing of Materials Failure Analysis

    Directory of Open Access Journals (Sweden)

    Peng Shi

    2014-01-01

    Full Text Available Materials failure indicates the fault with materials or components during their performance. To avoid the reoccurrence of similar failures, materials failure analysis is executed to investigate the reasons for the failure and to propose improved strategies. The whole procedure needs sufficient domain knowledge and also produces valuable new knowledge. However, the information about the materials failure analysis is usually retained by the domain expert, and its sharing is technically difficult. This phenomenon may seriously reduce the efficiency and decrease the veracity of the failure analysis. To solve this problem, this paper adopts ontology, a novel technology from the Semantic Web, as a tool for knowledge representation and sharing and describes the construction of the ontology to obtain information concerning the failure analysis, application area, materials, and failure cases. The ontology represented information is machine-understandable and can be easily shared through the Internet. At the same time, failure case intelligent retrieval, advanced statistics, and even automatic reasoning can be accomplished based on ontology represented knowledge. Obviously this can promote the knowledge sharing of materials service safety and improve the efficiency of failure analysis. The case of a nuclear power plant area is presented to show the details and benefits of this method.

  2. Social Ontology Documentation for Knowledge Externalization

    Science.gov (United States)

    Aranda-Corral, Gonzalo A.; Borrego-Díaz, Joaquín; Jiménez-Mavillard, Antonio

    Knowledge externalization and organization is a major challenge that companies must face. Also, they have to ask whether is possible to enhance its management. Mechanical processing of information represents a chance to carry out these tasks, as well as to turn intangible knowledge assets into real assets. Machine-readable knowledge provides a basis to enhance knowledge management. A promising approach is the empowering of Knowledge Externalization by the community (users, employees). In this paper, a social semantic tool (called OntoxicWiki) for enhancing the quality of knowledge is presented.

  3. Evaluation of need for ontologies to manage domain content for the Reportable Conditions Knowledge Management System.

    Science.gov (United States)

    Eilbeck, Karen L; Lipstein, Julie; McGarvey, Sunanda; Staes, Catherine J

    2014-01-01

    The Reportable Condition Knowledge Management System (RCKMS) is envisioned to be a single, comprehensive, authoritative, real-time portal to author, view and access computable information about reportable conditions. The system is designed for use by hospitals, laboratories, health information exchanges, and providers to meet public health reporting requirements. The RCKMS Knowledge Representation Workgroup was tasked to explore the need for ontologies to support RCKMS functionality. The workgroup reviewed relevant projects and defined criteria to evaluate candidate knowledge domain areas for ontology development. The use of ontologies is justified for this project to unify the semantics used to describe similar reportable events and concepts between different jurisdictions and over time, to aid data integration, and to manage large, unwieldy datasets that evolve, and are sometimes externally managed.

  4. An ontological knowledge framework for adaptive medical workflow.

    Science.gov (United States)

    Dang, Jiangbo; Hedayati, Amir; Hampel, Ken; Toklu, Candemir

    2008-10-01

    As emerging technologies, semantic Web and SOA (Service-Oriented Architecture) allow BPMS (Business Process Management System) to automate business processes that can be described as services, which in turn can be used to wrap existing enterprise applications. BPMS provides tools and methodologies to compose Web services that can be executed as business processes and monitored by BPM (Business Process Management) consoles. Ontologies are a formal declarative knowledge representation model. It provides a foundation upon which machine understandable knowledge can be obtained, and as a result, it makes machine intelligence possible. Healthcare systems can adopt these technologies to make them ubiquitous, adaptive, and intelligent, and then serve patients better. This paper presents an ontological knowledge framework that covers healthcare domains that a hospital encompasses-from the medical or administrative tasks, to hospital assets, medical insurances, patient records, drugs, and regulations. Therefore, our ontology makes our vision of personalized healthcare possible by capturing all necessary knowledge for a complex personalized healthcare scenario involving patient care, insurance policies, and drug prescriptions, and compliances. For example, our ontology facilitates a workflow management system to allow users, from physicians to administrative assistants, to manage, even create context-aware new medical workflows and execute them on-the-fly.

  5. Knowledge Integration Reconceptualized from an Integrationist Perspective

    OpenAIRE

    Taxén, Lars

    2012-01-01

    The concept of knowledge integration remains on precarious ontological and epistemological grounds. Hence, the purpose of this contribution is to suggest a reconceptualization of knowledge integration from the integrationist perspective proposed by the English linguist Roy Harris. In this view, all knowledge is internally generated by the human capacity for sign-making and hence, knowledge arises from creative attempts to integrate the various activities of which human are capable of. Integra...

  6. Integrity and change in modular ontologies

    NARCIS (Netherlands)

    Stuckenschmidt, Heiner; Klein, Michel

    2003-01-01

    The benefits of modular representations arc well known from many areas of computer science. In this paper, we concentrate on the benefits of modular ontologies with respect to local containment of terminological reasoning. We define an architecture for modular ontologies that supports local

  7. Design and Implementation of Hydrologic Process Knowledge-base Ontology: A case study for the Infiltration Process

    Science.gov (United States)

    Elag, M.; Goodall, J. L.

    2013-12-01

    Hydrologic modeling often requires the re-use and integration of models from different disciplines to simulate complex environmental systems. Component-based modeling introduces a flexible approach for integrating physical-based processes across disciplinary boundaries. Several hydrologic-related modeling communities have adopted the component-based approach for simulating complex physical systems by integrating model components across disciplinary boundaries in a workflow. However, it is not always straightforward to create these interdisciplinary models due to the lack of sufficient knowledge about a hydrologic process. This shortcoming is a result of using informal methods for organizing and sharing information about a hydrologic process. A knowledge-based ontology provides such standards and is considered the ideal approach for overcoming this challenge. The aims of this research are to present the methodology used in analyzing the basic hydrologic domain in order to identify hydrologic processes, the ontology itself, and how the proposed ontology is integrated with the Water Resources Component (WRC) ontology. The proposed ontology standardizes the definitions of a hydrologic process, the relationships between hydrologic processes, and their associated scientific equations. The objective of the proposed Hydrologic Process (HP) Ontology is to advance the idea of creating a unified knowledge framework for components' metadata by introducing a domain-level ontology for hydrologic processes. The HP ontology is a step toward an explicit and robust domain knowledge framework that can be evolved through the contribution of domain users. Analysis of the hydrologic domain is accomplished using the Formal Concept Approach (FCA), in which the infiltration process, an important hydrologic process, is examined. Two infiltration methods, the Green-Ampt and Philip's methods, were used to demonstrate the implementation of information in the HP ontology. Furthermore, a SPARQL

  8. Two obvious intuitions : Ontology-mapping needs background knowledge and approximation

    NARCIS (Netherlands)

    Van Harmelen, Frank

    2007-01-01

    Ontology mapping (or: ontology alignment, or integration) is one of the most active areas the Semantic Web area. An increasing amount of ontologies are becoming available in recent years, and if the Semantic Web is to be taken seriously, the problem of ontology mapping must be solved. Numerous

  9. Uberon, an integrative multi-species anatomy ontology

    Science.gov (United States)

    2012-01-01

    We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.org PMID:22293552

  10. The role of collaborative ontology development in the knowledge negotiation process

    Science.gov (United States)

    Rivera, Norma

    Interdisciplinary research (IDR) collaboration can be defined as the process of integrating experts' knowledge, perspectives, and resources to advance scientific discovery. The flourishing of more complex research problems, together with the growth of scientific and technical knowledge has resulted in the need for researchers from diverse fields to provide different expertise and points of view to tackle these problems. These collaborations, however, introduce a new set of "culture" barriers as participating experts are trained to communicate in discipline-specific languages, theories, and research practices. We propose that building a common knowledge base for research using ontology development techniques can provide a starting point for interdisciplinary knowledge exchange, negotiation, and integration. The goal of this work is to extend ontology development techniques to support the knowledge negotiation process in IDR groups. Towards this goal, this work presents a methodology that extends previous work in collaborative ontology development and integrates learning strategies and tools to enhance interdisciplinary research practices. We evaluate the effectiveness of applying such methodology in three different scenarios that cover educational and research settings. The results of this evaluation confirm that integrating learning strategies can, in fact, be advantageous to overall collaborative practices in IDR groups.

  11. The use of concept maps during knowledge elicitation in ontology development processes – the nutrigenomics use case

    Directory of Open Access Journals (Sweden)

    Taylor Chris

    2006-05-01

    Full Text Available Abstract Background Incorporation of ontologies into annotations has enabled 'semantic integration' of complex data, making explicit the knowledge within a certain field. One of the major bottlenecks in developing bio-ontologies is the lack of a unified methodology. Different methodologies have been proposed for different scenarios, but there is no agreed-upon standard methodology for building ontologies. The involvement of geographically distributed domain experts, the need for domain experts to lead the design process, the application of the ontologies and the life cycles of bio-ontologies are amongst the features not considered by previously proposed methodologies. Results Here, we present a methodology for developing ontologies within the biological domain. We describe our scenario, competency questions, results and milestones for each methodological stage. We introduce the use of concept maps during knowledge acquisition phases as a feasible transition between domain expert and knowledge engineer. Conclusion The contributions of this paper are the thorough description of the steps we suggest when building an ontology, example use of concept maps, consideration of applicability to the development of lower-level ontologies and application to decentralised environments. We have found that within our scenario conceptual maps played an important role in the development process.

  12. A Case for Embedded Natural Logic for Ontological Knowledge Bases

    DEFF Research Database (Denmark)

    Andreasen, Troels; Nilsson, Jørgen Fischer

    2014-01-01

    We argue in favour of adopting a form of natural logic for ontology-structured knowledge bases as an alternative to description logic and rule based languages. Natural logic is a form of logic resembling natural language assertions, unlike description logic. This is essential e.g. in life sciences...... negation in description logic. We embed the natural logic in DATALOG clauses which is to take care of the computational inference in connection with querying...

  13. Ontology-Based Knowledge Organization for the Radiograph Images Segmentation

    Directory of Open Access Journals (Sweden)

    MATEI, O.

    2008-04-01

    Full Text Available The quantity of thoracic radiographies in the medical field is ever growing. An automated system for segmenting the images would help doctors enormously. Some approaches are knowledge-based; therefore we propose here an ontology for this purpose. Thus it is machine oriented, rather than human-oriented. That is all the structures visible on a thoracic image are described from a technical point of view.

  14. Ontology based heterogeneous materials database integration and semantic query

    Science.gov (United States)

    Zhao, Shuai; Qian, Quan

    2017-10-01

    Materials digital data, high throughput experiments and high throughput computations are regarded as three key pillars of materials genome initiatives. With the fast growth of materials data, the integration and sharing of data is very urgent, that has gradually become a hot topic of materials informatics. Due to the lack of semantic description, it is difficult to integrate data deeply in semantic level when adopting the conventional heterogeneous database integration approaches such as federal database or data warehouse. In this paper, a semantic integration method is proposed to create the semantic ontology by extracting the database schema semi-automatically. Other heterogeneous databases are integrated to the ontology by means of relational algebra and the rooted graph. Based on integrated ontology, semantic query can be done using SPARQL. During the experiments, two world famous First Principle Computational databases, OQMD and Materials Project are used as the integration targets, which show the availability and effectiveness of our method.

  15. The Bone Dysplasia Ontology: integrating genotype and phenotype information in the skeletal dysplasia domain

    Directory of Open Access Journals (Sweden)

    Groza Tudor

    2012-03-01

    Full Text Available Abstract Background Skeletal dysplasias are a rare and heterogeneous group of genetic disorders affecting skeletal development. Patients with skeletal dysplasias suffer from many complex medical issues including degenerative joint disease and neurological complications. Because the data and expertise associated with this field is both sparse and disparate, significant benefits will potentially accrue from the availability of an ontology that provides a shared conceptualisation of the domain knowledge and enables data integration, cross-referencing and advanced reasoning across the relevant but distributed data sources. Results We introduce the design considerations and implementation details of the Bone Dysplasia Ontology. We also describe the different components of the ontology, including a comprehensive and formal representation of the skeletal dysplasia domain as well as the related genotypes and phenotypes. We then briefly describe SKELETOME, a community-driven knowledge curation platform that is underpinned by the Bone Dysplasia Ontology. SKELETOME enables domain experts to use, refine and extend and apply the ontology without any prior ontology engineering experience--to advance the body of knowledge in the skeletal dysplasia field. Conclusions The Bone Dysplasia Ontology represents the most comprehensive structured knowledge source for the skeletal dysplasias domain. It provides the means for integrating and annotating clinical and research data, not only at the generic domain knowledge level, but also at the level of individual patient case studies. It enables links between individual cases and publicly available genotype and phenotype resources based on a community-driven curation process that ensures a shared conceptualisation of the domain knowledge and its continuous incremental evolution.

  16. A Case for Embedded Natural Logic for Ontological Knowledge Bases

    DEFF Research Database (Denmark)

    Andreasen, Troels; Nilsson, Jørgen Fischer

    2014-01-01

    We argue in favour of adopting a form of natural logic for ontology-structured knowledge bases as an alternative to description logic and rule based languages. Natural logic is a form of logic resembling natural language assertions, unlike description logic. This is essential e.g. in life sciences......, where the large and evolving knowledge specifications should be directly accessible to domain experts. Moreover, natural logic comes with intuitive inference rules. The considered version of natural logic leans toward the closed world assumption (CWA) unlike the open world assumption with classical...

  17. Spatial Data Integration Using Ontology-Based Approach

    Science.gov (United States)

    Hasani, S.; Sadeghi-Niaraki, A.; Jelokhani-Niaraki, M.

    2015-12-01

    In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

  18. SPATIAL DATA INTEGRATION USING ONTOLOGY-BASED APPROACH

    Directory of Open Access Journals (Sweden)

    S. Hasani

    2015-12-01

    Full Text Available In today's world, the necessity for spatial data for various organizations is becoming so crucial that many of these organizations have begun to produce spatial data for that purpose. In some circumstances, the need to obtain real time integrated data requires sustainable mechanism to process real-time integration. Case in point, the disater management situations that requires obtaining real time data from various sources of information. One of the problematic challenges in the mentioned situation is the high degree of heterogeneity between different organizations data. To solve this issue, we introduce an ontology-based method to provide sharing and integration capabilities for the existing databases. In addition to resolving semantic heterogeneity, better access to information is also provided by our proposed method. Our approach is consisted of three steps, the first step is identification of the object in a relational database, then the semantic relationships between them are modelled and subsequently, the ontology of each database is created. In a second step, the relative ontology will be inserted into the database and the relationship of each class of ontology will be inserted into the new created column in database tables. Last step is consisted of a platform based on service-oriented architecture, which allows integration of data. This is done by using the concept of ontology mapping. The proposed approach, in addition to being fast and low cost, makes the process of data integration easy and the data remains unchanged and thus takes advantage of the legacy application provided.

  19. Ontology Based Resolution of Semantic Conflicts in Information Integration

    Institute of Scientific and Technical Information of China (English)

    LU Han; LI Qing-zhong

    2004-01-01

    Semantic conflict is the conflict caused by using different ways in heterogeneous systems to express the same entity in reality.This prevents information integration from accomplishing semantic coherence.Since ontology helps to solve semantic problems, this area has become a hot topic in information integration.In this paper, we introduce semantic conflict into information integration of heterogeneous applications.We discuss the origins and categories of the conflict, and present an ontology-based schema mapping approach to eliminate semantic conflicts.

  20. Ontology Learning for Chinese Information Organization and Knowledge Discovery in Ethnology and Anthropology

    Directory of Open Access Journals (Sweden)

    Jing Kong

    2007-09-01

    Full Text Available This paper presents an ontology learning architecture that reflects the interaction between ontology learning and other applications such as ontology-engineering tools and information systems. Based on this architecture, we have developed a prototype system CHOL: a Chinese ontology learning tool. CHOL learns domain ontology from Chinese domain specific texts. On the one hand, it supports a semi-automatic domain ontology acquisition and dynamic maintenance, and on the other hand, it supports an auto-indexing and auto-classification of Chinese scholarly literature. CHOL has been applied in ethnology and anthropology for Chinese information organization and knowledge discovery.

  1. Evolving BioAssay Ontology (BAO): modularization, integration and applications.

    Science.gov (United States)

    Abeyruwan, Saminda; Vempati, Uma D; Küçük-McGinty, Hande; Visser, Ubbo; Koleti, Amar; Mir, Ahsan; Sakurai, Kunie; Chung, Caty; Bittker, Joshua A; Clemons, Paul A; Brudz, Steve; Siripala, Anosha; Morales, Arturo J; Romacker, Martin; Twomey, David; Bureeva, Svetlana; Lemmon, Vance; Schürer, Stephan C

    2014-01-01

    The lack of established standards to describe and annotate biological assays and screening outcomes in the domain of drug and chemical probe discovery is a severe limitation to utilize public and proprietary drug screening data to their maximum potential. We have created the BioAssay Ontology (BAO) project (http://bioassayontology.org) to develop common reference metadata terms and definitions required for describing relevant information of low-and high-throughput drug and probe screening assays and results. The main objectives of BAO are to enable effective integration, aggregation, retrieval, and analyses of drug screening data. Since we first released BAO on the BioPortal in 2010 we have considerably expanded and enhanced BAO and we have applied the ontology in several internal and external collaborative projects, for example the BioAssay Research Database (BARD). We describe the evolution of BAO with a design that enables modeling complex assays including profile and panel assays such as those in the Library of Integrated Network-based Cellular Signatures (LINCS). One of the critical questions in evolving BAO is the following: how can we provide a way to efficiently reuse and share among various research projects specific parts of our ontologies without violating the integrity of the ontology and without creating redundancies. This paper provides a comprehensive answer to this question with a description of a methodology for ontology modularization using a layered architecture. Our modularization approach defines several distinct BAO components and separates internal from external modules and domain-level from structural components. This approach facilitates the generation/extraction of derived ontologies (or perspectives) that can suit particular use cases or software applications. We describe the evolution of BAO related to its formal structures, engineering approaches, and content to enable modeling of complex assays and integration with other ontologies and

  2. Semantics in support of biodiversity knowledge discovery: an introduction to the biological collections ontology and related ontologies.

    Science.gov (United States)

    Walls, Ramona L; Deck, John; Guralnick, Robert; Baskauf, Steve; Beaman, Reed; Blum, Stanley; Bowers, Shawn; Buttigieg, Pier Luigi; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Morrison, Norman; Ó Tuama, Éamonn; Schildhauer, Mark; Smith, Barry; Stucky, Brian J; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers.

  3. Semantics in Support of Biodiversity Knowledge Discovery: An Introduction to the Biological Collections Ontology and Related Ontologies

    Science.gov (United States)

    Baskauf, Steve; Blum, Stanley; Bowers, Shawn; Davies, Neil; Endresen, Dag; Gandolfo, Maria Alejandra; Hanner, Robert; Janning, Alyssa; Krishtalka, Leonard; Matsunaga, Andréa; Midford, Peter; Tuama, Éamonn Ó.; Schildhauer, Mark; Smith, Barry; Stucky, Brian J.; Thomer, Andrea; Wieczorek, John; Whitacre, Jamie; Wooley, John

    2014-01-01

    The study of biodiversity spans many disciplines and includes data pertaining to species distributions and abundances, genetic sequences, trait measurements, and ecological niches, complemented by information on collection and measurement protocols. A review of the current landscape of metadata standards and ontologies in biodiversity science suggests that existing standards such as the Darwin Core terminology are inadequate for describing biodiversity data in a semantically meaningful and computationally useful way. Existing ontologies, such as the Gene Ontology and others in the Open Biological and Biomedical Ontologies (OBO) Foundry library, provide a semantic structure but lack many of the necessary terms to describe biodiversity data in all its dimensions. In this paper, we describe the motivation for and ongoing development of a new Biological Collections Ontology, the Environment Ontology, and the Population and Community Ontology. These ontologies share the aim of improving data aggregation and integration across the biodiversity domain and can be used to describe physical samples and sampling processes (for example, collection, extraction, and preservation techniques), as well as biodiversity observations that involve no physical sampling. Together they encompass studies of: 1) individual organisms, including voucher specimens from ecological studies and museum specimens, 2) bulk or environmental samples (e.g., gut contents, soil, water) that include DNA, other molecules, and potentially many organisms, especially microbes, and 3) survey-based ecological observations. We discuss how these ontologies can be applied to biodiversity use cases that span genetic, organismal, and ecosystem levels of organization. We argue that if adopted as a standard and rigorously applied and enriched by the biodiversity community, these ontologies would significantly reduce barriers to data discovery, integration, and exchange among biodiversity resources and researchers

  4. OpenKnowledge Deliverable 3.3.: A methodology for ontology matching quality evaluation

    OpenAIRE

    Yatskevich, Mikalai; Giunchiglia, Fausto; McNeill, Fiona; Shvaiko, Pavel

    2007-01-01

    This document presents an evaluation methodology for the assessment of quality results produced by ontology matchers. In particular, it discusses: (i) several standard quality measures used in the ontology matching evaluation, (ii) a methodology of how to build semiautomatically an incomplete reference alignment allowing for the assessment of quality results produced by ontology matchers and (iii) a preliminary empirical evaluation of the OpenKnowledge ontology matching component.

  5. Distributed and Collaborative Knowledge Management Using an Ontology-Based System

    OpenAIRE

    Adrian , Weronika ,; Ligęza , Antoni; Nalepa , Grzegorz ,; Kaczor , Krzysztof

    2012-01-01

    International audience; Semantic annotations and formally grounded ontologies constitute flexible yet powerful methods of knowledge representation. Using them in a system allows to perform automated reasoning and can enhance the knowledge management. In the paper, we present a system for collaborative knowledge management, in which an ontology and ontological reasoning is used. The main objective of the application is to provide information for citizens about threats in an urban environment. ...

  6. Al-Quran ontology based on knowledge themes | Ta'a | Journal of ...

    African Journals Online (AJOL)

    Islamic knowledge is gathered through the understanding the Al-Quran. It requires ontology which can capture the knowledge and present it in a machine readable structured. However, current ontology approaches is irrelevant and inaccuracy in producing true concepts of Al-Quran knowledge, because it used traditional ...

  7. Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI. Results We have examined and integrated the ChEBI structural hierarchy into the GO resource through computationally-assisted manual curation of both GO and ChEBI. Our work has resulted in the creation of computable definitions of GO terms that contain fully defined semantic relationships to corresponding chemical terms in ChEBI. Conclusions The set of logical definitions using both the GO and ChEBI has already been used to automate aspects of GO development and has the potential to allow the integration of data across the domains of biology and chemistry. These logical definitions are available as an extended version of the ontology from http://purl.obolibrary.org/obo/go/extensions/go-plus.owl. PMID:23895341

  8. Toward a Blended Ontology: Applying Knowledge Systems to ...

    Science.gov (United States)

    Bionanomedicine and environmental research share need common terms and ontologies. This study applied knowledge systems, data mining, and bibliometrics used in nano-scale ADME research from 1991 to 2011. The prominence of nano-ADME in environmental research began to exceed the publication rate in medical research in 2006. That trend appears to continue as a result of the growing products in commerce using nanotechnology, that is, 5-fold growth in number of countries with nanomaterials research centers. Funding for this research virtually did not exist prior to 2002, whereas today both medical and environmental research is funded globally. Key nanoparticle research began with pharmacology and therapeutic drug-delivery and contrasting agents, but the advances have found utility in the environmental research community. As evidence ultrafine aerosols and aquatic colloids research increased 6-fold, indicating a new emphasis on environmental nanotoxicology. User-directed expert elicitation from the engineering and chemical/ADME domains can be combined with appropriate Boolean logic and queries to define the corpus of nanoparticle interest. The study combined pharmacological expertise and informatics to identify the corpus by building logical conclusions and observations. Publication records informatics can lead to an enhanced understanding the connectivity between fields, as well as overcoming the differences in ontology between the fields. The National Exposure Resea

  9. Use of Ontologies for Data Integration and Curation

    Directory of Open Access Journals (Sweden)

    Judith Gelernter

    2011-03-01

    Full Text Available Data curation includes the goal of facilitating the re-use and combination of datasets, which is often impeded by incompatible data schema. Can we use ontologies to help with data integration? We suggest a semi-automatic process that involves the use of automatic text searching to help identify overlaps in metadata that accompany data schemas, plus human validation of suggested data matches.Problems include different text used to describe the same concept, different forms of data recording and different organizations of data. Ontologies can help by focussing attention on important words, providing synonyms to assist matching, and indicating in what context words are used. Beyond ontologies, data on the statistical behavior of data can be used to decide which data elements appear to be compatible with which other data elements. When curating data which may have hundreds or even thousands of data labels, semi-automatic assistance with data fusion should be of great help.

  10. Developmental Anatomy Ontology of Zebrafish: an Integrative semantic framework

    Directory of Open Access Journals (Sweden)

    Belmamoune Mounia

    2007-12-01

    Full Text Available Integration of information is quintessential to make use of the wealth of bioinformatics resources. One aspect of integration is to make databases interoperable through well annotated information. With new databases one strives to store complementary information and such results in collections of heterogeneous information systems. Concepts in these databases need to be connected and ontologies typically provide a common terminology to share information among different resources.

  11. Integrating reasoning and clinical archetypes using OWL ontologies and SWRL rules.

    Science.gov (United States)

    Lezcano, Leonardo; Sicilia, Miguel-Angel; Rodríguez-Solano, Carlos

    2011-04-01

    Semantic interoperability is essential to facilitate the computerized support for alerts, workflow management and evidence-based healthcare across heterogeneous electronic health record (EHR) systems. Clinical archetypes, which are formal definitions of specific clinical concepts defined as specializations of a generic reference (information) model, provide a mechanism to express data structures in a shared and interoperable way. However, currently available archetype languages do not provide direct support for mapping to formal ontologies and then exploiting reasoning on clinical knowledge, which are key ingredients of full semantic interoperability, as stated in the SemanticHEALTH report [1]. This paper reports on an approach to translate definitions expressed in the openEHR Archetype Definition Language (ADL) to a formal representation expressed using the Ontology Web Language (OWL). The formal representations are then integrated with rules expressed with Semantic Web Rule Language (SWRL) expressions, providing an approach to apply the SWRL rules to concrete instances of clinical data. Sharing the knowledge expressed in the form of rules is consistent with the philosophy of open sharing, encouraged by archetypes. Our approach also allows the reuse of formal knowledge, expressed through ontologies, and extends reuse to propositions of declarative knowledge, such as those encoded in clinical guidelines. This paper describes the ADL-to-OWL translation approach, describes the techniques to map archetypes to formal ontologies, and demonstrates how rules can be applied to the resulting representation. We provide examples taken from a patient safety alerting system to illustrate our approach. Copyright © 2010 Elsevier Inc. All rights reserved.

  12. Semantic Web Ontology and Data Integration: a Case Study in Aiding Psychiatric Drug Repurposing.

    Science.gov (United States)

    Liang, Chen; Sun, Jingchun; Tao, Cui

    2015-01-01

    There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipolar disorder and epilepsy. We constructed an ontology incorporating knowledge between the two diseases and performed semantic reasoning tasks with the ontology. The results suggested 48 candidate drugs that hold promise for further breakthrough. The evaluation demonstrated the validity our approach. Our approach prioritizes the candidate drugs that have potential associations among genes, phenotypes and symptoms, and thus facilitates the data integration and drug repurposing in psychiatric disorders.

  13. Knowledge management of eco-industrial park for efficient energy utilization through ontology-based approach

    International Nuclear Information System (INIS)

    Zhang, Chuan; Romagnoli, Alessandro; Zhou, Li; Kraft, Markus

    2017-01-01

    Highlights: •An intelligent energy management system for Eco-Industrial Park (EIP) is proposed. •An explicit domain ontology for EIP energy management is designed. •Ontology-based approach can increase knowledge interoperability within EIP. •Ontology-based approach can allow self-optimization without human intervention in EIP. •The proposed system harbours huge potential in the future scenario of Internet of Things. -- Abstract: An ontology-based approach for Eco-Industrial Park (EIP) knowledge management is proposed in this paper. The designed ontology in this study is formalized conceptualization of EIP. Based on such an ontological representation, a Knowledge-Based System (KBS) for EIP energy management named J-Park Simulator (JPS) is developed. By applying JPS to the solution of EIP waste heat utilization problem, the results of this study show that ontology is a powerful tool for knowledge management of complex systems such as EIP. The ontology-based approach can increase knowledge interoperability between different companies in EIP. The ontology-based approach can also allow intelligent decision making by using disparate data from remote databases, which implies the possibility of self-optimization without human intervention scenario of Internet of Things (IoT). It is shown through this study that KBS can bridge the communication gaps between different companies in EIP, sequentially more potential Industrial Symbiosis (IS) links can be established to improve the overall energy efficiency of the whole EIP.

  14. OpenBiodiv-O: ontology of the OpenBiodiv knowledge management system.

    Science.gov (United States)

    Senderov, Viktor; Simov, Kiril; Franz, Nico; Stoev, Pavel; Catapano, Terry; Agosti, Donat; Sautter, Guido; Morris, Robert A; Penev, Lyubomir

    2018-01-18

    The biodiversity domain, and in particular biological taxonomy, is moving in the direction of semantization of its research outputs. The present work introduces OpenBiodiv-O, the ontology that serves as the basis of the OpenBiodiv Knowledge Management System. Our intent is to provide an ontology that fills the gaps between ontologies for biodiversity resources, such as DarwinCore-based ontologies, and semantic publishing ontologies, such as the SPAR Ontologies. We bridge this gap by providing an ontology focusing on biological taxonomy. OpenBiodiv-O introduces classes, properties, and axioms in the domains of scholarly biodiversity publishing and biological taxonomy and aligns them with several important domain ontologies (FaBiO, DoCO, DwC, Darwin-SW, NOMEN, ENVO). By doing so, it bridges the ontological gap across scholarly biodiversity publishing and biological taxonomy and allows for the creation of a Linked Open Dataset (LOD) of biodiversity information (a biodiversity knowledge graph) and enables the creation of the OpenBiodiv Knowledge Management System. A key feature of the ontology is that it is an ontology of the scientific process of biological taxonomy and not of any particular state of knowledge. This feature allows it to express a multiplicity of scientific opinions. The resulting OpenBiodiv knowledge system may gain a high level of trust in the scientific community as it does not force a scientific opinion on its users (e.g. practicing taxonomists, library researchers, etc.), but rather provides the tools for experts to encode different views as science progresses. OpenBiodiv-O provides a conceptual model of the structure of a biodiversity publication and the development of related taxonomic concepts. It also serves as the basis for the OpenBiodiv Knowledge Management System.

  15. Ontology-Driven Knowledge-Based Health-Care System, An Emerging Area - Challenges And Opportunities - Indian Scenario

    Science.gov (United States)

    Sunitha, A.; Babu, G. Suresh

    2014-11-01

    Recent studies in the decision making efforts in the area of public healthcare systems have been tremendously inspired and influenced by the entry of ontology. Ontology driven systems results in the effective implementation of healthcare strategies for the policy makers. The central source of knowledge is the ontology containing all the relevant domain concepts such as locations, diseases, environments and their domain sensitive inter-relationships which is the prime objective, concern and the motivation behind this paper. The paper further focuses on the development of a semantic knowledge-base for public healthcare system. This paper describes the approach and methodologies in bringing out a novel conceptual theme in establishing a firm linkage between three different ontologies related to diseases, places and environments in one integrated platform. This platform correlates the real-time mechanisms prevailing within the semantic knowledgebase and establishing their inter-relationships for the first time in India. This is hoped to formulate a strong foundation for establishing a much awaited basic need for a meaningful healthcare decision making system in the country. Introduction through a wide range of best practices facilitate the adoption of this approach for better appreciation, understanding and long term outcomes in the area. The methods and approach illustrated in the paper relate to health mapping methods, reusability of health applications, and interoperability issues based on mapping of the data attributes with ontology concepts in generating semantic integrated data driving an inference engine for user-interfaced semantic queries.

  16. Ontology-driven data integration and visualization for exploring regional geologic time and paleontological information

    Science.gov (United States)

    Wang, Chengbin; Ma, Xiaogang; Chen, Jianguo

    2018-06-01

    Initiatives of open data promote the online publication and sharing of large amounts of geologic data. How to retrieve information and discover knowledge from the big data is an ongoing challenge. In this paper, we developed an ontology-driven data integration and visualization pilot system for exploring information of regional geologic time, paleontology, and fundamental geology. The pilot system (http://www2.cs.uidaho.edu/%7Emax/gts/)

  17. Ontology-based geographic data set integration

    NARCIS (Netherlands)

    Uitermark, H.T.J.A.; Uitermark, Harry T.; Oosterom, Peter J.M.; Mars, Nicolaas; Molenaar, Martien; Molenaar, M.

    1999-01-01

    In order to develop a system to propagate updates we investigate the semantic and spatial relationships between independently produced geographic data sets of the same region (data set integration). The goal of this system is to reduce operator intervention in update operations between corresponding

  18. Ontology-based knowledge representation for resolution of semantic heterogeneity in GIS

    Science.gov (United States)

    Liu, Ying; Xiao, Han; Wang, Limin; Han, Jialing

    2017-07-01

    Lack of semantic interoperability in geographical information systems has been identified as the main obstacle for data sharing and database integration. The new method should be found to overcome the problems of semantic heterogeneity. Ontologies are considered to be one approach to support geographic information sharing. This paper presents an ontology-driven integration approach to help in detecting and possibly resolving semantic conflicts. Its originality is that each data source participating in the integration process contains an ontology that defines the meaning of its own data. This approach ensures the automation of the integration through regulation of semantic integration algorithm. Finally, land classification in field GIS is described as the example.

  19. Ontology Language to Support Description of Experiment Control System Semantics, Collaborative Knowledge-Base Design and Ontology Reuse

    International Nuclear Information System (INIS)

    Gyurjyan, Vardan; Abbott, D.; Heyes, G.; Jastrzembski, E.; Moffit, B.; Timmer, C.; Wolin, E.

    2009-01-01

    In this paper we discuss the control domain specific ontology that is built on top of the domain-neutral Resource Definition Framework (RDF). Specifically, we will discuss the relevant set of ontology concepts along with the relationships among them in order to describe experiment control components and generic event-based state machines. Control Oriented Ontology Language (COOL) is a meta-data modeling language that provides generic means for representation of physics experiment control processes and components, and their relationships, rules and axioms. It provides a semantic reference frame that is useful for automating the communication of information for configuration, deployment and operation. COOL has been successfully used to develop a complete and dynamic knowledge-base for experiment control systems, developed using the AFECS framework.

  20. The Gene Ontology (GO) Cellular Component Ontology: integration with SAO (Subcellular Anatomy Ontology) and other recent developments

    Science.gov (United States)

    2013-01-01

    Background The Gene Ontology (GO) (http://www.geneontology.org/) contains a set of terms for describing the activity and actions of gene products across all kingdoms of life. Each of these activities is executed in a location within a cell or in the vicinity of a cell. In order to capture this context, the GO includes a sub-ontology called the Cellular Component (CC) ontology (GO-CCO). The primary use of this ontology is for GO annotation, but it has also been used for phenotype annotation, and for the annotation of images. Another ontology with similar scope to the GO-CCO is the Subcellular Anatomy Ontology (SAO), part of the Neuroscience Information Framework Standard (NIFSTD) suite of ontologies. The SAO also covers cell components, but in the domain of neuroscience. Description Recently, the GO-CCO was enriched in content and links to the Biological Process and Molecular Function branches of GO as well as to other ontologies. This was achieved in several ways. We carried out an amalgamation of SAO terms with GO-CCO ones; as a result, nearly 100 new neuroscience-related terms were added to the GO. The GO-CCO also contains relationships to GO Biological Process and Molecular Function terms, as well as connecting to external ontologies such as the Cell Ontology (CL). Terms representing protein complexes in the Protein Ontology (PRO) reference GO-CCO terms for their species-generic counterparts. GO-CCO terms can also be used to search a variety of databases. Conclusions In this publication we provide an overview of the GO-CCO, its overall design, and some recent extensions that make use of additional spatial information. One of the most recent developments of the GO-CCO was the merging in of the SAO, resulting in a single unified ontology designed to serve the needs of GO annotators as well as the specific needs of the neuroscience community. PMID:24093723

  1. The BioHub Knowledge Base: Ontology and Repository for Sustainable Biosourcing.

    Science.gov (United States)

    Read, Warren J; Demetriou, George; Nenadic, Goran; Ruddock, Noel; Stevens, Robert; Winter, Jerry

    2016-06-01

    The motivation for the BioHub project is to create an Integrated Knowledge Management System (IKMS) that will enable chemists to source ingredients from bio-renewables, rather than from non-sustainable sources such as fossil oil and its derivatives. The BioHubKB is the data repository of the IKMS; it employs Semantic Web technologies, especially OWL, to host data about chemical transformations, bio-renewable feedstocks, co-product streams and their chemical components. Access to this knowledge base is provided to other modules within the IKMS through a set of RESTful web services, driven by SPARQL queries to a Sesame back-end. The BioHubKB re-uses several bio-ontologies and bespoke extensions, primarily for chemical feedstocks and products, to form its knowledge organisation schema. Parts of plants form feedstocks, while various processes generate co-product streams that contain certain chemicals. Both chemicals and transformations are associated with certain qualities, which the BioHubKB also attempts to capture. Of immediate commercial and industrial importance is to estimate the cost of particular sets of chemical transformations (leading to candidate surfactants) performed in sequence, and these costs too are captured. Data are sourced from companies' internal knowledge and document stores, and from the publicly available literature. Both text analytics and manual curation play their part in populating the ontology. We describe the prototype IKMS, the BioHubKB and the services that it supports for the IKMS. The BioHubKB can be found via http://biohub.cs.manchester.ac.uk/ontology/biohub-kb.owl .

  2. Towards a reference plant trait ontology for modeling knowledge of plant traits and phenotypes

    Science.gov (United States)

    Ontology engineering and knowledge modeling for the plant sciences is expected to contribute to the understanding of the basis of plant traits that determine phenotypic expression in a given environment. Several crop- or clade-specific plant trait ontologies have been developed to describe plant tr...

  3. Knowledge Representation and Management. From Ontology to Annotation. Findings from the Yearbook 2015 Section on Knowledge Representation and Management.

    Science.gov (United States)

    Charlet, J; Darmoni, S J

    2015-08-13

    To summarize the best papers in the field of Knowledge Representation and Management (KRM). A comprehensive review of medical informatics literature was performed to select some of the most interesting papers of KRM published in 2014. Four articles were selected, two focused on annotation and information retrieval using an ontology. The two others focused mainly on ontologies, one dealing with the usage of a temporal ontology in order to analyze the content of narrative document, one describing a methodology for building multilingual ontologies. Semantic models began to show their efficiency, coupled with annotation tools.

  4. Studies on Experimental Ontology and Knowledge Service Development in Bio-Environmental Engineering

    Science.gov (United States)

    Zhang, Yunliang

    2018-01-01

    The existing domain-related ontology and information service patterns are analyzed, and the main problems faced by the experimental scheme knowledge service were clarified. The ontology framework model for knowledge service of Bio-environmental Engineering was proposed from the aspects of experimental materials, experimental conditions and experimental instruments, and this ontology will be combined with existing knowledge organization systems to organize scientific and technological literatures, data and experimental schemes. With the similarity and priority calculation, it can improve the related domain research.

  5. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-01

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. PMID:27733503

  6. Ontobee: A linked ontology data server to support ontology term dereferencing, linkage, query and integration.

    Science.gov (United States)

    Ong, Edison; Xiang, Zuoshuang; Zhao, Bin; Liu, Yue; Lin, Yu; Zheng, Jie; Mungall, Chris; Courtot, Mélanie; Ruttenberg, Alan; He, Yongqun

    2017-01-04

    Linked Data (LD) aims to achieve interconnected data by representing entities using Unified Resource Identifiers (URIs), and sharing information using Resource Description Frameworks (RDFs) and HTTP. Ontologies, which logically represent entities and relations in specific domains, are the basis of LD. Ontobee (http://www.ontobee.org/) is a linked ontology data server that stores ontology information using RDF triple store technology and supports query, visualization and linkage of ontology terms. Ontobee is also the default linked data server for publishing and browsing biomedical ontologies in the Open Biological Ontology (OBO) Foundry (http://obofoundry.org) library. Ontobee currently hosts more than 180 ontologies (including 131 OBO Foundry Library ontologies) with over four million terms. Ontobee provides a user-friendly web interface for querying and visualizing the details and hierarchy of a specific ontology term. Using the eXtensible Stylesheet Language Transformation (XSLT) technology, Ontobee is able to dereference a single ontology term URI, and then output RDF/eXtensible Markup Language (XML) for computer processing or display the HTML information on a web browser for human users. Statistics and detailed information are generated and displayed for each ontology listed in Ontobee. In addition, a SPARQL web interface is provided for custom advanced SPARQL queries of one or multiple ontologies. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

  7. KaBOB: ontology-based semantic integration of biomedical databases.

    Science.gov (United States)

    Livingston, Kevin M; Bada, Michael; Baumgartner, William A; Hunter, Lawrence E

    2015-04-23

    The ability to query many independent biological databases using a common ontology-based semantic model would facilitate deeper integration and more effective utilization of these diverse and rapidly growing resources. Despite ongoing work moving toward shared data formats and linked identifiers, significant problems persist in semantic data integration in order to establish shared identity and shared meaning across heterogeneous biomedical data sources. We present five processes for semantic data integration that, when applied collectively, solve seven key problems. These processes include making explicit the differences between biomedical concepts and database records, aggregating sets of identifiers denoting the same biomedical concepts across data sources, and using declaratively represented forward-chaining rules to take information that is variably represented in source databases and integrating it into a consistent biomedical representation. We demonstrate these processes and solutions by presenting KaBOB (the Knowledge Base Of Biomedicine), a knowledge base of semantically integrated data from 18 prominent biomedical databases using common representations grounded in Open Biomedical Ontologies. An instance of KaBOB with data about humans and seven major model organisms can be built using on the order of 500 million RDF triples. All source code for building KaBOB is available under an open-source license. KaBOB is an integrated knowledge base of biomedical data representationally based in prominent, actively maintained Open Biomedical Ontologies, thus enabling queries of the underlying data in terms of biomedical concepts (e.g., genes and gene products, interactions and processes) rather than features of source-specific data schemas or file formats. KaBOB resolves many of the issues that routinely plague biomedical researchers intending to work with data from multiple data sources and provides a platform for ongoing data integration and development and for

  8. A fuzzy ontology modeling for case base knowledge in diabetes mellitus domain

    Directory of Open Access Journals (Sweden)

    Shaker El-Sappagh

    2017-06-01

    Full Text Available Knowledge-Intensive Case-Based Reasoning Systems (KI-CBR mainly depend on ontologies. Ontology can play the role of case-base knowledge. The combination of ontology and fuzzy logic reasoning is critical in the medical domain. Case-base representation based on fuzzy ontology is expected to enhance the semantic and storage of CBR knowledge-base. This paper provides an advancement to the research of diabetes diagnosis CBR by proposing a novel case-base fuzzy OWL2 ontology (CBRDiabOnto. This ontology can be considered as the first fuzzy case-base ontology in the medical domain. It is based on a case-base fuzzy Extended Entity Relation (EER data model. It contains 63 (fuzzy classes, 54 (fuzzy object properties, 138 (fuzzy datatype properties, and 105 fuzzy datatypes. We populated the ontology with 60 cases and used SPARQL-DL for its query. The evaluation of CBRDiabOnto shows that it is accurate, consistent, and cover terminologies and logic of diabetes mellitus diagnosis.

  9. Knowledge retrieval from PubMed abstracts and electronic medical records with the Multiple Sclerosis Ontology.

    Science.gov (United States)

    Malhotra, Ashutosh; Gündel, Michaela; Rajput, Abdul Mateen; Mevissen, Heinz-Theodor; Saiz, Albert; Pastor, Xavier; Lozano-Rubi, Raimundo; Martinez-Lapiscina, Elena H; Martinez-Lapsicina, Elena H; Zubizarreta, Irati; Mueller, Bernd; Kotelnikova, Ekaterina; Toldo, Luca; Hofmann-Apitius, Martin; Villoslada, Pablo

    2015-01-01

    In order to retrieve useful information from scientific literature and electronic medical records (EMR) we developed an ontology specific for Multiple Sclerosis (MS). The MS Ontology was created using scientific literature and expert review under the Protégé OWL environment. We developed a dictionary with semantic synonyms and translations to different languages for mining EMR. The MS Ontology was integrated with other ontologies and dictionaries (diseases/comorbidities, gene/protein, pathways, drug) into the text-mining tool SCAIView. We analyzed the EMRs from 624 patients with MS using the MS ontology dictionary in order to identify drug usage and comorbidities in MS. Testing competency questions and functional evaluation using F statistics further validated the usefulness of MS ontology. Validation of the lexicalized ontology by means of named entity recognition-based methods showed an adequate performance (F score = 0.73). The MS Ontology retrieved 80% of the genes associated with MS from scientific abstracts and identified additional pathways targeted by approved disease-modifying drugs (e.g. apoptosis pathways associated with mitoxantrone, rituximab and fingolimod). The analysis of the EMR from patients with MS identified current usage of disease modifying drugs and symptomatic therapy as well as comorbidities, which are in agreement with recent reports. The MS Ontology provides a semantic framework that is able to automatically extract information from both scientific literature and EMR from patients with MS, revealing new pathogenesis insights as well as new clinical information.

  10. Charting taxonomic knowledge through ontologies and ranking algorithms

    Science.gov (United States)

    Huber, Robert; Klump, Jens

    2009-04-01

    Since the inception of geology as a modern science, paleontologists have described a large number of fossil species. This makes fossilized organisms an important tool in the study of stratigraphy and past environments. Since taxonomic classifications of organisms, and thereby their names, change frequently, the correct application of this tool requires taxonomic expertise in finding correct synonyms for a given species name. Much of this taxonomic information has already been published in journals and books where it is compiled in carefully prepared synonymy lists. Because this information is scattered throughout the paleontological literature, it is difficult to find and sometimes not accessible. Also, taxonomic information in the literature is often difficult to interpret for non-taxonomists looking for taxonomic synonymies as part of their research. The highly formalized structure makes Open Nomenclature synonymy lists ideally suited for computer aided identification of taxonomic synonyms. Because a synonymy list is a list of citations related to a taxon name, its bibliographic nature allows the application of bibliometric techniques to calculate the impact of synonymies and taxonomic concepts. TaxonRank is a ranking algorithm based on bibliometric analysis and Internet page ranking algorithms. TaxonRank uses published synonymy list data stored in TaxonConcept, a taxonomic information system. The basic ranking algorithm has been modified to include a measure of confidence on species identification based on the Open Nomenclature notation used in synonymy list, as well as other synonymy specific criteria. The results of our experiments show that the output of the proposed ranking algorithm gives a good estimate of the impact a published taxonomic concept has on the taxonomic opinions in the geological community. Also, our results show that treating taxonomic synonymies as part of on an ontology is a way to record and manage taxonomic knowledge, and thus contribute

  11. The Planteome database: an integrated resource for reference ontologies, plant genomics and phenomics

    Science.gov (United States)

    Cooper, Laurel; Meier, Austin; Laporte, Marie-Angélique; Elser, Justin L; Mungall, Chris; Sinn, Brandon T; Cavaliere, Dario; Carbon, Seth; Dunn, Nathan A; Smith, Barry; Qu, Botong; Preece, Justin; Zhang, Eugene; Todorovic, Sinisa; Gkoutos, Georgios; Doonan, John H; Stevenson, Dennis W; Arnaud, Elizabeth

    2018-01-01

    Abstract The Planteome project (http://www.planteome.org) provides a suite of reference and species-specific ontologies for plants and annotations to genes and phenotypes. Ontologies serve as common standards for semantic integration of a large and growing corpus of plant genomics, phenomics and genetics data. The reference ontologies include the Plant Ontology, Plant Trait Ontology and the Plant Experimental Conditions Ontology developed by the Planteome project, along with the Gene Ontology, Chemical Entities of Biological Interest, Phenotype and Attribute Ontology, and others. The project also provides access to species-specific Crop Ontologies developed by various plant breeding and research communities from around the world. We provide integrated data on plant traits, phenotypes, and gene function and expression from 95 plant taxa, annotated with reference ontology terms. The Planteome project is developing a plant gene annotation platform; Planteome Noctua, to facilitate community engagement. All the Planteome ontologies are publicly available and are maintained at the Planteome GitHub site (https://github.com/Planteome) for sharing, tracking revisions and new requests. The annotated data are freely accessible from the ontology browser (http://browser.planteome.org/amigo) and our data repository. PMID:29186578

  12. The Role of Ontology Repositories in Supporting Knowledge ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... development of the data changing as well as helping in finding the suitable ontology .... for changing data where it can be accessed easily by a large number of ... over the network using hypertext transfer protocol. (HTTP) and the .... public services of the traffic and road transport project, and electric power ...

  13. An Ontology-Based Conceptual Model For Accumulating And Reusing Knowledge In A DMAIC Process

    Science.gov (United States)

    Nguyen, ThanhDat; Kifor, Claudiu Vasile

    2015-09-01

    DMAIC (Define, Measure, Analyze, Improve, and Control) is an important process used to enhance quality of processes basing on knowledge. However, it is difficult to access DMAIC knowledge. Conventional approaches meet a problem arising from structuring and reusing DMAIC knowledge. The main reason is that DMAIC knowledge is not represented and organized systematically. In this article, we overcome the problem basing on a conceptual model that is a combination of DMAIC process, knowledge management, and Ontology engineering. The main idea of our model is to utilizing Ontologies to represent knowledge generated by each of DMAIC phases. We build five different knowledge bases for storing all knowledge of DMAIC phases with the support of necessary tools and appropriate techniques in Information Technology area. Consequently, these knowledge bases provide knowledge available to experts, managers, and web users during or after DMAIC execution in order to share and reuse existing knowledge.

  14. Ontological Analysis of Integrated Process Models: testing hypotheses

    Directory of Open Access Journals (Sweden)

    Michael Rosemann

    2001-11-01

    Full Text Available Integrated process modeling is achieving prominence in helping to document and manage business administration and IT processes in organizations. The ARIS framework is a popular example for a framework of integrated process modeling not least because it underlies the 800 or more reference models embedded in the world's most popular ERP package, SAP R/3. This paper demonstrates the usefulness of the Bunge-Wand-Weber (BWW representation model for evaluating modeling grammars such as those constituting ARIS. It reports some initial insights gained from pilot testing Green and Rosemann's (2000 evaluative propositions. Even when considering all five views of ARIS, modelers have problems representing business rules, the scope and boundary of systems, and decomposing models. However, even though it is completely ontologically redundant, users still find the function view useful in modeling.

  15. A web-based system architecture for ontology-based data integration in the domain of IT benchmarking

    Science.gov (United States)

    Pfaff, Matthias; Krcmar, Helmut

    2018-03-01

    In the domain of IT benchmarking (ITBM), a variety of data and information are collected. Although these data serve as the basis for business analyses, no unified semantic representation of such data yet exists. Consequently, data analysis across different distributed data sets and different benchmarks is almost impossible. This paper presents a system architecture and prototypical implementation for an integrated data management of distributed databases based on a domain-specific ontology. To preserve the semantic meaning of the data, the ITBM ontology is linked to data sources and functions as the central concept for database access. Thus, additional databases can be integrated by linking them to this domain-specific ontology and are directly available for further business analyses. Moreover, the web-based system supports the process of mapping ontology concepts to external databases by introducing a semi-automatic mapping recommender and by visualizing possible mapping candidates. The system also provides a natural language interface to easily query linked databases. The expected result of this ontology-based approach of knowledge representation and data access is an increase in knowledge and data sharing in this domain, which will enhance existing business analysis methods.

  16. Specifying Geographic Information - Ontology, Knowledge Representation, and Formal Constraints

    DEFF Research Database (Denmark)

    Christensen, Jesper Vinther

    2007-01-01

    as in the private sector. The theoretical background is the establishment of a representational system, which ontologically comprises a representation of notions in the "real world" and notions which include the representation of these. Thus, the thesis leans towards a traditional division between modeling...... of domains and conceptualization of these. The thesis contributes a formalization of what is understood by domain models and conceptual models, when the focus is on geographic information. Moreover, it is shown how specifications for geographic information are related to this representational system...... of requirements and rules, building on terms from the domain and concept ontologies. In combination with the theoretical basis the analysis is used for developing an underlying model of notions, which defines the individual elements in a specification and the relations between them. In the chapters of the thesis...

  17. Disease Compass- a navigation system for disease knowledge based on ontology and linked data techniques.

    Science.gov (United States)

    Kozaki, Kouji; Yamagata, Yuki; Mizoguchi, Riichiro; Imai, Takeshi; Ohe, Kazuhiko

    2017-06-19

    Medical ontologies are expected to contribute to the effective use of medical information resources that store considerable amount of data. In this study, we focused on disease ontology because the complicated mechanisms of diseases are related to concepts across various medical domains. The authors developed a River Flow Model (RFM) of diseases, which captures diseases as the causal chains of abnormal states. It represents causes of diseases, disease progression, and downstream consequences of diseases, which is compliant with the intuition of medical experts. In this paper, we discuss a fact repository for causal chains of disease based on the disease ontology. It could be a valuable knowledge base for advanced medical information systems. We developed the fact repository for causal chains of diseases based on our disease ontology and abnormality ontology. This section summarizes these two ontologies. It is developed as linked data so that information scientists can access it using SPARQL queries through an Resource Description Framework (RDF) model for causal chain of diseases. We designed the RDF model as an implementation of the RFM for the fact repository based on the ontological definitions of the RFM. 1554 diseases and 7080 abnormal states in six major clinical areas, which are extracted from the disease ontology, are published as linked data (RDF) with SPARQL endpoint (accessible API). Furthermore, the authors developed Disease Compass, a navigation system for disease knowledge. Disease Compass can browse the causal chains of a disease and obtain related information, including abnormal states, through two web services that provide general information from linked data, such as DBpedia, and 3D anatomical images. Disease Compass can provide a complete picture of disease-associated processes in such a way that fits with a clinician's understanding of diseases. Therefore, it supports user exploration of disease knowledge with access to pertinent information

  18. Combining the Generic Entity-Attribute-Value Model and Terminological Models into a Common Ontology to Enable Data Integration and Decision Support.

    Science.gov (United States)

    Bouaud, Jacques; Guézennec, Gilles; Séroussi, Brigitte

    2018-01-01

    The integration of clinical information models and termino-ontological models into a unique ontological framework is highly desirable for it facilitates data integration and management using the same formal mechanisms for both data concepts and information model components. This is particularly true for knowledge-based decision support tools that aim to take advantage of all facets of semantic web technologies in merging ontological reasoning, concept classification, and rule-based inferences. We present an ontology template that combines generic data model components with (parts of) existing termino-ontological resources. The approach is developed for the guideline-based decision support module on breast cancer management within the DESIREE European project. The approach is based on the entity attribute value model and could be extended to other domains.

  19. Organizational Knowledge Transfer Using Ontologies and a Rule-Based System

    Science.gov (United States)

    Okabe, Masao; Yoshioka, Akiko; Kobayashi, Keido; Yamaguchi, Takahira

    In recent automated and integrated manufacturing, so-called intelligence skill is becoming more and more important and its efficient transfer to next-generation engineers is one of the urgent issues. In this paper, we propose a new approach without costly OJT (on-the-job training), that is, combinational usage of a domain ontology, a rule ontology and a rule-based system. Intelligence skill can be decomposed into pieces of simple engineering rules. A rule ontology consists of these engineering rules as primitives and the semantic relations among them. A domain ontology consists of technical terms in the engineering rules and the semantic relations among them. A rule ontology helps novices get the total picture of the intelligence skill and a domain ontology helps them understand the exact meanings of the engineering rules. A rule-based system helps domain experts externalize their tacit intelligence skill to ontologies and also helps novices internalize them. As a case study, we applied our proposal to some actual job at a remote control and maintenance office of hydroelectric power stations in Tokyo Electric Power Co., Inc. We also did an evaluation experiment for this case study and the result supports our proposal.

  20. In Pursuit of Natural Logics for Ontology-Structured Knowledge Bases

    DEFF Research Database (Denmark)

    Nilsson, Jørgen Fischer

    2015-01-01

    We argue for adopting a form of natural logic for ontology-structured knowledge bases with complex sentences. This serves to ease reading of knowledge base for domain experts and to make reasoning and querying and path-finding more comprehensible. We explain natural logic as a development from tr...

  1. The Knowledge Sharing Based on PLIB Ontology and XML for Collaborative Product Commerce

    Science.gov (United States)

    Ma, Jun; Luo, Guofu; Li, Hao; Xiao, Yanqiu

    Collaborative Product Commerce (CPC) has become a brand-new commerce mode for manufacture. In order to promote information communication with each other more efficiently in CPC, a knowledge-sharing framework based on PLIB (ISO 13584) ontology and XML was presented, and its implementation method was studied. At first, according to the methodology of PLIB (ISO 13584), a common ontology—PLIB ontology was put forward which provide a coherent conceptual meaning within the context of CPC domain. Meanwhile, for the sake of knowledge intercommunion via internet, the PLIB ontology formalization description by EXPRESS mode was converted into XML Schema, and two mapping methods were presented: direct mapping approach and meta-levels mapping approach, while the latter was adopted. Based on above work, a parts resource knowledge-sharing framework (CPC-KSF) was put forward and realized, which has been applied in the process of automotive component manufacturing collaborative product commerce.

  2. Web Approach for Ontology-Based Classification, Integration, and Interdisciplinary Usage of Geoscience Metadata

    Directory of Open Access Journals (Sweden)

    B Ritschel

    2012-10-01

    Full Text Available The Semantic Web is a W3C approach that integrates the different sources of semantics within documents and services using ontology-based techniques. The main objective of this approach in the geoscience domain is the improvement of understanding, integration, and usage of Earth and space science related web content in terms of data, information, and knowledge for machines and people. The modeling and representation of semantic attributes and relations within and among documents can be realized by human readable concept maps and machine readable OWL documents. The objectives for the usage of the Semantic Web approach in the GFZ data center ISDC project are the design of an extended classification of metadata documents for product types related to instruments, platforms, and projects as well as the integration of different types of metadata related to data product providers, users, and data centers. Sources of content and semantics for the description of Earth and space science product types and related classes are standardized metadata documents (e.g., DIF documents, publications, grey literature, and Web pages. Other sources are information provided by users, such as tagging data and social navigation information. The integration of controlled vocabularies as well as folksonomies plays an important role in the design of well formed ontologies.

  3. Agent Based Knowledge Management Solution using Ontology, Semantic Web Services and GIS

    Directory of Open Access Journals (Sweden)

    Andreea DIOSTEANU

    2009-01-01

    Full Text Available The purpose of our research is to develop an agent based knowledge management application framework using a specific type of ontology that is able to facilitate semantic web service search and automatic composition. This solution can later on be used to develop complex solutions for location based services, supply chain management, etc. This application for modeling knowledge highlights the importance of agent interaction that leads to efficient enterprise interoperability. Furthermore, it proposes an "agent communication language" ontology that extends the OWL Lite standard approach and makes it more flexible in retrieving proper data for identifying the agents that can best communicate and negotiate.

  4. Knowledge integration by thinking along

    NARCIS (Netherlands)

    Berends, J.J.; Debackere, K.; Garud, R.; Weggeman, M.C.D.P.

    2004-01-01

    Organizing depends on the integration of specialized knowledge that lies distributed across individuals. There are benefits from specialization, and, yet, the integration of knowledge across boundaries is critical for organizational vitality. How do organizations benefit from knowledge that lies in

  5. Knowledge Management Framework for Emerging Infectious Diseases Preparedness and Response: Design and Development of Public Health Document Ontology.

    Science.gov (United States)

    Zhang, Zhizun; Gonzalez, Mila C; Morse, Stephen S; Venkatasubramanian, Venkat

    2017-10-11

    There are increasing concerns about our preparedness and timely coordinated response across the globe to cope with emerging infectious diseases (EIDs). This poses practical challenges that require exploiting novel knowledge management approaches effectively. This work aims to develop an ontology-driven knowledge management framework that addresses the existing challenges in sharing and reusing public health knowledge. We propose a systems engineering-inspired ontology-driven knowledge management approach. It decomposes public health knowledge into concepts and relations and organizes the elements of knowledge based on the teleological functions. Both knowledge and semantic rules are stored in an ontology and retrieved to answer queries regarding EID preparedness and response. A hybrid concept extraction was implemented in this work. The quality of the ontology was evaluated using the formal evaluation method Ontology Quality Evaluation Framework. Our approach is a potentially effective methodology for managing public health knowledge. Accuracy and comprehensiveness of the ontology can be improved as more knowledge is stored. In the future, a survey will be conducted to collect queries from public health practitioners. The reasoning capacity of the ontology will be evaluated using the queries and hypothetical outbreaks. We suggest the importance of developing a knowledge sharing standard like the Gene Ontology for the public health domain. ©Zhizun Zhang, Mila C Gonzalez, Stephen S Morse, Venkat Venkatasubramanian. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 11.10.2017.

  6. An approach to development of ontological knowledge base in the field of scientific and research activity in Russia

    Science.gov (United States)

    Murtazina, M. Sh; Avdeenko, T. V.

    2018-05-01

    The state of art and the progress in application of semantic technologies in the field of scientific and research activity have been analyzed. Even elementary empirical comparison has shown that the semantic search engines are superior in all respects to conventional search technologies. However, semantic information technologies are insufficiently used in the field of scientific and research activity in Russia. In present paper an approach to construction of ontological model of knowledge base is proposed. The ontological model is based on the upper-level ontology and the RDF mechanism for linking several domain ontologies. The ontological model is implemented in the Protégé environment.

  7. An ontological knowledge based system for selection of process monitoring and analysis tools

    DEFF Research Database (Denmark)

    Singh, Ravendra; Gernaey, Krist; Gani, Rafiqul

    2010-01-01

    monitoring and analysis tools for a wide range of operations has made their selection a difficult, time consuming and challenging task. Therefore, an efficient and systematic knowledge base coupled with an inference system is necessary to support the optimal selection of process monitoring and analysis tools......, satisfying the process and user constraints. A knowledge base consisting of the process knowledge as well as knowledge on measurement methods and tools has been developed. An ontology has been designed for knowledge representation and management. The developed knowledge base has a dual feature. On the one...... procedures has been developed to retrieve the data/information stored in the knowledge base....

  8. Ontology-Based Empirical Knowledge Verification for Professional Virtual Community

    Science.gov (United States)

    Chen, Yuh-Jen

    2011-01-01

    A professional virtual community provides an interactive platform for enterprise experts to create and share their empirical knowledge cooperatively, and the platform contains a tremendous amount of hidden empirical knowledge that knowledge experts have preserved in the discussion process. Therefore, enterprise knowledge management highly…

  9. Ontological Knowledge Base of Physical and Technical Effects for Conceptual Design of Sensors

    International Nuclear Information System (INIS)

    ASTRAKHAN CIVIL ENGINEERING INSTITUTE, Astrakhan (Russian Federation))" data-affiliation=" (Department of CAD Systems, State Autonomous Educational Institution of Astrakhan Region of Higher Professional Education ASTRAKHAN CIVIL ENGINEERING INSTITUTE, Astrakhan (Russian Federation))" >Zaripova, V M; ASTRAKHAN CIVIL ENGINEERING INSTITUTE, Astrakhan (Russian Federation))" data-affiliation=" (Department of CAD Systems, State Autonomous Educational Institution of Astrakhan Region of Higher Professional Education ASTRAKHAN CIVIL ENGINEERING INSTITUTE, Astrakhan (Russian Federation))" >Petrova, I Yu

    2015-01-01

    This article discusses design of the knowledge base of physical phenomena based on domain-specific ontology. Classification of various physical phenomena in the knowledge base is based on energy-information model of circuits (EIMC) suggested by the authors. This model is specially aimed at design of new operating principles of sensing elements (sensors). Such a knowledge base can be used to train intended engineers, specialists in sensors design

  10. Towards Agile Ontology Maintenance

    Science.gov (United States)

    Luczak-Rösch, Markus

    Ontologies are an appropriate means to represent knowledge on the Web. Research on ontology engineering reached practices for an integrative lifecycle support. However, a broader success of ontologies in Web-based information systems remains unreached while the more lightweight semantic approaches are rather successful. We assume, paired with the emerging trend of services and microservices on the Web, new dynamic scenarios gain momentum in which a shared knowledge base is made available to several dynamically changing services with disparate requirements. Our work envisions a step towards such a dynamic scenario in which an ontology adapts to the requirements of the accessing services and applications as well as the user's needs in an agile way and reduces the experts' involvement in ontology maintenance processes.

  11. The federated ontology of the pal project interfacing ontologies and integrating time-dependent data

    NARCIS (Netherlands)

    Krieger, H.U.; Peters, R.; Kiefer, B.; Van Bekkum, M.A.; Kaptein, F.; Neerincx, M.A.

    2016-01-01

    This paper describes ongoing work carried out in the European project PAL which will support childre in their diabetes self-management as well as assist health professionals and parents involved in the diabete regimen of the child. Here, we will focus on the construction of the PAL ontology which

  12. Ontology-supported research on vaccine efficacy, safety and integrative biological networks.

    Science.gov (United States)

    He, Yongqun

    2014-07-01

    While vaccine efficacy and safety research has dramatically progressed with the methods of in silico prediction and data mining, many challenges still exist. A formal ontology is a human- and computer-interpretable set of terms and relations that represent entities in a specific domain and how these terms relate to each other. Several community-based ontologies (including Vaccine Ontology, Ontology of Adverse Events and Ontology of Vaccine Adverse Events) have been developed to support vaccine and adverse event representation, classification, data integration, literature mining of host-vaccine interaction networks, and analysis of vaccine adverse events. The author further proposes minimal vaccine information standards and their ontology representations, ontology-based linked open vaccine data and meta-analysis, an integrative One Network ('OneNet') Theory of Life, and ontology-based approaches to study and apply the OneNet theory. In the Big Data era, these proposed strategies provide a novel framework for advanced data integration and analysis of fundamental biological networks including vaccine immune mechanisms.

  13. Toward a Blended Ontology: Applying Knowledge Systems to Compare Therapeutic and Toxicological Nanoscale Domains

    Science.gov (United States)

    Bionanomedicine and environmental research share need common terms and ontologies. This study applied knowledge systems, data mining, and bibliometrics used in nano-scale ADME research from 1991 to 2011. The prominence of nano-ADME in environmental research began to exceed the pu...

  14. The Integration of Knowledge

    Directory of Open Access Journals (Sweden)

    Carlos Blanco

    2016-05-01

    Full Text Available The exponential growth of knowledge demands an interdisciplinary reflection on how to integrate the different branches of the natural sciences and the humanities into a coherent picture of world, life, and mind. Insightful intellectual tools, like evolutionary Biology and Neuroscience, can facilitate this project. It is the task of Philosophy to identify those fundamental concepts whose explanatory power can illuminate the thread that leads from the most elementary realities to the most complex spheres. This article aims to explore the importance of the ideas of conservation, selection, and unification for achieving the goal.

  15. Definition of an Ontology Matching Algorithm for Context Integration in Smart Cities.

    Science.gov (United States)

    Otero-Cerdeira, Lorena; Rodríguez-Martínez, Francisco J; Gómez-Rodríguez, Alma

    2014-12-08

    In this paper we describe a novel proposal in the field of smart cities: using an ontology matching algorithm to guarantee the automatic information exchange between the agents and the smart city. A smart city is composed by different types of agents that behave as producers and/or consumers of the information in the smart city. In our proposal, the data from the context is obtained by sensor and device agents while users interact with the smart city by means of user or system agents. The knowledge of each agent, as well as the smart city's knowledge, is semantically represented using different ontologies. To have an open city, that is fully accessible to any agent and therefore to provide enhanced services to the users, there is the need to ensure a seamless communication between agents and the city, regardless of their inner knowledge representations, i.e., ontologies. To meet this goal we use ontology matching techniques, specifically we have defined a new ontology matching algorithm called OntoPhil to be deployed within a smart city, which has never been done before. OntoPhil was tested on the benchmarks provided by the well known evaluation initiative, Ontology Alignment Evaluation Initiative, and also compared to other matching algorithms, although these algorithms were not specifically designed for smart cities. Additionally, specific tests involving a smart city's ontology and different types of agents were conducted to validate the usefulness of OntoPhil in the smart city environment.

  16. The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants

    KAUST Repository

    Hoehndorf, Robert

    2016-11-14

    Background The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text. Results We have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities. Conclusions The FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established

  17. The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants.

    Science.gov (United States)

    Hoehndorf, Robert; Alshahrani, Mona; Gkoutos, Georgios V; Gosline, George; Groom, Quentin; Hamann, Thomas; Kattge, Jens; de Oliveira, Sylvia Mota; Schmidt, Marco; Sierra, Soraya; Smets, Erik; Vos, Rutger A; Weiland, Claus

    2016-11-14

    The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text. We have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities. The FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established vocabularies or ontologies, but rather

  18. Ontology Design Patterns: Bridging the Gap Between Local Semantic Use Cases and Large-Scale, Long-Term Data Integration

    Science.gov (United States)

    Shepherd, Adam; Arko, Robert; Krisnadhi, Adila; Hitzler, Pascal; Janowicz, Krzysztof; Chandler, Cyndy; Narock, Tom; Cheatham, Michelle; Schildhauer, Mark; Jones, Matt; Raymond, Lisa; Mickle, Audrey; Finin, Tim; Fils, Doug; Carbotte, Suzanne; Lehnert, Kerstin

    2015-04-01

    Integrating datasets for new use cases is one of the common drivers for adopting semantic web technologies. Even though linked data principles enables this type of activity over time, the task of reconciling new ontological commitments for newer use cases can be daunting. This situation was faced by the Biological and Chemical Oceanography Data Management Office (BCO-DMO) as it sought to integrate its existing linked data with other data repositories to address newer scientific use cases as a partner in the GeoLink Project. To achieve a successful integration with other GeoLink partners, BCO-DMO's metadata would need to be described using the new ontologies developed by the GeoLink partners - a situation that could impact semantic inferencing, pre-existing software and external users of BCO-DMO's linked data. This presentation describes the process of how GeoLink is bridging the gap between local, pre-existing ontologies to achieve scientific metadata integration for all its partners through the use of ontology design patterns. GeoLink, an NSF EarthCube Building Block, brings together experts from the geosciences, computer science, and library science in an effort to improve discovery and reuse of data and knowledge. Its participating repositories include content from field expeditions, laboratory analyses, journal publications, conference presentations, theses/reports, and funding awards that span scientific studies from marine geology to marine ecology and biogeochemistry to paleoclimatology. GeoLink's outcomes include a set of reusable ontology design patterns (ODPs) that describe core geoscience concepts, a network of Linked Data published by participating repositories using those ODPs, and tools to facilitate discovery of related content in multiple repositories.

  19. Using ontology databases for scalable query answering, inconsistency detection, and data integration

    Science.gov (United States)

    Dou, Dejing

    2011-01-01

    An ontology database is a basic relational database management system that models an ontology plus its instances. To reason over the transitive closure of instances in the subsumption hierarchy, for example, an ontology database can either unfold views at query time or propagate assertions using triggers at load time. In this paper, we use existing benchmarks to evaluate our method—using triggers—and we demonstrate that by forward computing inferences, we not only improve query time, but the improvement appears to cost only more space (not time). However, we go on to show that the true penalties were simply opaque to the benchmark, i.e., the benchmark inadequately captures load-time costs. We have applied our methods to two case studies in biomedicine, using ontologies and data from genetics and neuroscience to illustrate two important applications: first, ontology databases answer ontology-based queries effectively; second, using triggers, ontology databases detect instance-based inconsistencies—something not possible using views. Finally, we demonstrate how to extend our methods to perform data integration across multiple, distributed ontology databases. PMID:22163378

  20. OntoCAT--simple ontology search and integration in Java, R and REST/JavaScript.

    Science.gov (United States)

    Adamusiak, Tomasz; Burdett, Tony; Kurbatova, Natalja; Joeri van der Velde, K; Abeygunawardena, Niran; Antonakaki, Despoina; Kapushesky, Misha; Parkinson, Helen; Swertz, Morris A

    2011-05-29

    Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups. OntoCAT provides a seamless programming interface to query heterogeneous ontology resources including OLS and BioPortal, as well as user-specified local OWL and OBO files. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies. It is also available as a stand-alone MOLGENIS database and a Google App Engine application. OntoCAT provides a robust, configurable solution for accessing ontology terms specified locally and from remote services, is available as a stand-alone tool and has been tested thoroughly in the ArrayExpress, MOLGENIS, EFO and Gen2Phen phenotype use cases. http://www.ontocat.org.

  1. Translation of overlay models of student knowledge for relative domains based on domain ontology mapping

    DEFF Research Database (Denmark)

    Sosnovsky, Sergey; Dolog, Peter; Henze, Nicola

    2007-01-01

    The effectiveness of an adaptive educational system in many respects depends on the precision of modeling assumptions it makes about a student. One of the well-known challenges in student modeling is to adequately assess the initial level of student's knowledge when s/he starts working...... with a system. Sometimes potentially handful data are available as a part of user model from a system used by the student before. The usage of external user modeling information is troublesome because of differences in system architecture, knowledge representation, modeling constraints, etc. In this paper, we...... argue that the implementation of underlying knowledge models in a sharable format, as domain ontologies - along with application of automatic ontology mapping techniques for model alignment - can help to overcome the "new-user" problem and will greatly widen opportunities for student model translation...

  2. Dynamic knowledge representation using agent-based modeling: ontology instantiation and verification of conceptual models.

    Science.gov (United States)

    An, Gary

    2009-01-01

    The sheer volume of biomedical research threatens to overwhelm the capacity of individuals to effectively process this information. Adding to this challenge is the multiscale nature of both biological systems and the research community as a whole. Given this volume and rate of generation of biomedical information, the research community must develop methods for robust representation of knowledge in order for individuals, and the community as a whole, to "know what they know." Despite increasing emphasis on "data-driven" research, the fact remains that researchers guide their research using intuitively constructed conceptual models derived from knowledge extracted from publications, knowledge that is generally qualitatively expressed using natural language. Agent-based modeling (ABM) is a computational modeling method that is suited to translating the knowledge expressed in biomedical texts into dynamic representations of the conceptual models generated by researchers. The hierarchical object-class orientation of ABM maps well to biomedical ontological structures, facilitating the translation of ontologies into instantiated models. Furthermore, ABM is suited to producing the nonintuitive behaviors that often "break" conceptual models. Verification in this context is focused at determining the plausibility of a particular conceptual model, and qualitative knowledge representation is often sufficient for this goal. Thus, utilized in this fashion, ABM can provide a powerful adjunct to other computational methods within the research process, as well as providing a metamodeling framework to enhance the evolution of biomedical ontologies.

  3. OAHG: an integrated resource for annotating human genes with multi-level ontologies.

    Science.gov (United States)

    Cheng, Liang; Sun, Jie; Xu, Wanying; Dong, Lixiang; Hu, Yang; Zhou, Meng

    2016-10-05

    OAHG, an integrated resource, aims to establish a comprehensive functional annotation resource for human protein-coding genes (PCGs), miRNAs, and lncRNAs by multi-level ontologies involving Gene Ontology (GO), Disease Ontology (DO), and Human Phenotype Ontology (HPO). Many previous studies have focused on inferring putative properties and biological functions of PCGs and non-coding RNA genes from different perspectives. During the past several decades, a few of databases have been designed to annotate the functions of PCGs, miRNAs, and lncRNAs, respectively. A part of functional descriptions in these databases were mapped to standardize terminologies, such as GO, which could be helpful to do further analysis. Despite these developments, there is no comprehensive resource recording the function of these three important types of genes. The current version of OAHG, release 1.0 (Jun 2016), integrates three ontologies involving GO, DO, and HPO, six gene functional databases and two interaction databases. Currently, OAHG contains 1,434,694 entries involving 16,929 PCGs, 637 miRNAs, 193 lncRNAs, and 24,894 terms of ontologies. During the performance evaluation, OAHG shows the consistencies with existing gene interactions and the structure of ontology. For example, terms with more similar structure could be associated with more associated genes (Pearson correlation γ 2  = 0.2428, p < 2.2e-16).

  4. EEVADO-ontology based construction of a knowledge based system for handling radiation emergency

    International Nuclear Information System (INIS)

    Datta, D.; Hegde, A.G.

    2001-01-01

    The basic aim of handling a radiation emergency is to protect the site personnel and public in the off-site areas. Hence it is required to assess the accident to develop the protective action recommendations for the site personnel, members of the public and emergency workers. An explanation facility is required to analyze the emergency situation and make needful decision. Algorithmic based software cannot provide this support as it does not have any such facility. A knowledge based system (KBS) obviously would act as a special purpose intelligent agent on behalf or at the behest of the emergency organization. Knowledge of the KBS has been elicited on the basis of ontology, a set of definitions of classes, objects, attributes, relations and constraints. Ontology provides a vocabulary for the expression of domain knowledge. The present paper discusses the development and utility of a knowledge based system - EEVADO (Emergency Evaluation and Dosimetry). The present software is verified and validated by ontology and by conducting Desktop Exercise in training program on Emergency Preparedness. (author)

  5. An Ontology-supported Approach for Automatic Chaining of Web Services in Geospatial Knowledge Discovery

    Science.gov (United States)

    di, L.; Yue, P.; Yang, W.; Yu, G.

    2006-12-01

    Recent developments in geospatial semantic Web have shown promise for automatic discovery, access, and use of geospatial Web services to quickly and efficiently solve particular application problems. With the semantic Web technology, it is highly feasible to construct intelligent geospatial knowledge systems that can provide answers to many geospatial application questions. A key challenge in constructing such intelligent knowledge system is to automate the creation of a chain or process workflow that involves multiple services and highly diversified data and can generate the answer to a specific question of users. This presentation discusses an approach for automating composition of geospatial Web service chains by employing geospatial semantics described by geospatial ontologies. It shows how ontology-based geospatial semantics are used for enabling the automatic discovery, mediation, and chaining of geospatial Web services. OWL-S is used to represent the geospatial semantics of individual Web services and the type of the services it belongs to and the type of the data it can handle. The hierarchy and classification of service types are described in the service ontology. The hierarchy and classification of data types are presented in the data ontology. For answering users' geospatial questions, an Artificial Intelligent (AI) planning algorithm is used to construct the service chain by using the service and data logics expressed in the ontologies. The chain can be expressed as a graph with nodes representing services and connection weights representing degrees of semantic matching between nodes. The graph is a visual representation of logical geo-processing path for answering users' questions. The graph can be instantiated to a physical service workflow for execution to generate the answer to a user's question. A prototype system, which includes real world geospatial applications, is implemented to demonstrate the concept and approach.

  6. Ontology-based knowledge management for personalized adverse drug events detection.

    Science.gov (United States)

    Cao, Feng; Sun, Xingzhi; Wang, Xiaoyuan; Li, Bo; Li, Jing; Pan, Yue

    2011-01-01

    Since Adverse Drug Event (ADE) has become a leading cause of death around the world, there arises high demand for helping clinicians or patients to identify possible hazards from drug effects. Motivated by this, we present a personalized ADE detection system, with the focus on applying ontology-based knowledge management techniques to enhance ADE detection services. The development of electronic health records makes it possible to automate the personalized ADE detection, i.e., to take patient clinical conditions into account during ADE detection. Specifically, we define the ADE ontology to uniformly manage the ADE knowledge from multiple sources. We take advantage of the rich semantics from the terminology SNOMED-CT and apply it to ADE detection via the semantic query and reasoning.

  7. Aligning ontologies and integrating textual evidence for pathway analysis of microarray data

    Energy Technology Data Exchange (ETDEWEB)

    Gopalan, Banu; Posse, Christian; Sanfilippo, Antonio P.; Stenzel-Poore, Mary; Stevens, S.L.; Castano, Jose; Beagley, Nathaniel; Riensche, Roderick M.; Baddeley, Bob; Simon, R.P.; Pustejovsky, James

    2006-10-08

    Expression arrays are introducing a paradigmatic change in biology by shifting experimental approaches from single gene studies to genome-level analysis, monitoring the ex-pression levels of several thousands of genes in parallel. The massive amounts of data obtained from the microarray data needs to be integrated and interpreted to infer biological meaning within the context of information-rich pathways. In this paper, we present a methodology that integrates textual information with annotations from cross-referenced ontolo-gies to map genes to pathways in a semi-automated way. We illustrate this approach and compare it favorably to other tools by analyzing the gene expression changes underlying the biological phenomena related to stroke. Stroke is the third leading cause of death and a major disabler in the United States. Through years of study, researchers have amassed a significant knowledge base about stroke, and this knowledge, coupled with new technologies, is providing a wealth of new scientific opportunities. The potential for neu-roprotective stroke therapy is enormous. However, the roles of neurogenesis, angiogenesis, and other proliferative re-sponses in the recovery process following ischemia and the molecular mechanisms that lead to these processes still need to be uncovered. Improved annotation of genomic and pro-teomic data, including annotation of pathways in which genes and proteins are involved, is required to facilitate their interpretation and clinical application. While our approach is not aimed at replacing existing curated pathway databases, it reveals multiple hidden relationships that are not evident with the way these databases analyze functional groupings of genes from the Gene Ontology.

  8. The ins and outs of eukaryotic viruses: Knowledge base and ontology of a viral infection.

    Directory of Open Access Journals (Sweden)

    Chantal Hulo

    Full Text Available Viruses are genetically diverse, infect a wide range of tissues and host cells and follow unique processes for replicating themselves. All these processes were investigated and indexed in ViralZone knowledge base. To facilitate standardizing data, a simple ontology of viral life-cycle terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address unique viral replication cycle processes, and existing terminology was modified and adapted. The virus life-cycle is classically described by schematic pictures. Using this ontology, it can be represented by a combination of successive terms: "entry", "latency", "transcription", "replication" and "exit". Each of these parts is broken down into discrete steps. For example Zika virus "entry" is broken down in successive steps: "Attachment", "Apoptotic mimicry", "Viral endocytosis/ macropinocytosis", "Fusion with host endosomal membrane", "Viral factory". To demonstrate the utility of a standard ontology for virus biology, this work was completed by annotating virus data in the ViralZone, UniProtKB and Gene Ontology databases.

  9. A Method of Extracting Ontology Module Using Concept Relations for Sharing Knowledge in Mobile Cloud Computing Environment

    Directory of Open Access Journals (Sweden)

    Keonsoo Lee

    2014-01-01

    Full Text Available In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

  10. A method of extracting ontology module using concept relations for sharing knowledge in mobile cloud computing environment.

    Science.gov (United States)

    Lee, Keonsoo; Rho, Seungmin; Lee, Seok-Won

    2014-01-01

    In mobile cloud computing environment, the cooperation of distributed computing objects is one of the most important requirements for providing successful cloud services. To satisfy this requirement, all the members, who are employed in the cooperation group, need to share the knowledge for mutual understanding. Even if ontology can be the right tool for this goal, there are several issues to make a right ontology. As the cost and complexity of managing knowledge increase according to the scale of the knowledge, reducing the size of ontology is one of the critical issues. In this paper, we propose a method of extracting ontology module to increase the utility of knowledge. For the given signature, this method extracts the ontology module, which is semantically self-contained to fulfill the needs of the service, by considering the syntactic structure and semantic relation of concepts. By employing this module, instead of the original ontology, the cooperation of computing objects can be performed with less computing load and complexity. In particular, when multiple external ontologies need to be combined for more complex services, this method can be used to optimize the size of shared knowledge.

  11. Ontology authoring with Forza

    CSIR Research Space (South Africa)

    Keet, CM

    2014-11-01

    Full Text Available Generic, reusable ontology elements, such as a foundational ontology's categories and part-whole relations, are essential for good and interoperable knowledge representation. Ontology developers, which include domain experts and novices, face...

  12. Assessing the practice of biomedical ontology evaluation: Gaps and opportunities.

    Science.gov (United States)

    Amith, Muhammad; He, Zhe; Bian, Jiang; Lossio-Ventura, Juan Antonio; Tao, Cui

    2018-04-01

    With the proliferation of heterogeneous health care data in the last three decades, biomedical ontologies and controlled biomedical terminologies play a more and more important role in knowledge representation and management, data integration, natural language processing, as well as decision support for health information systems and biomedical research. Biomedical ontologies and controlled terminologies are intended to assure interoperability. Nevertheless, the quality of biomedical ontologies has hindered their applicability and subsequent adoption in real-world applications. Ontology evaluation is an integral part of ontology development and maintenance. In the biomedicine domain, ontology evaluation is often conducted by third parties as a quality assurance (or auditing) effort that focuses on identifying modeling errors and inconsistencies. In this work, we first organized four categorical schemes of ontology evaluation methods in the existing literature to create an integrated taxonomy. Further, to understand the ontology evaluation practice in the biomedicine domain, we reviewed a sample of 200 ontologies from the National Center for Biomedical Ontology (NCBO) BioPortal-the largest repository for biomedical ontologies-and observed that only 15 of these ontologies have documented evaluation in their corresponding inception papers. We then surveyed the recent quality assurance approaches for biomedical ontologies and their use. We also mapped these quality assurance approaches to the ontology evaluation criteria. It is our anticipation that ontology evaluation and quality assurance approaches will be more widely adopted in the development life cycle of biomedical ontologies. Copyright © 2018 Elsevier Inc. All rights reserved.

  13. Ontology-based data integration between clinical and research systems.

    Directory of Open Access Journals (Sweden)

    Sebastian Mate

    Full Text Available Data from the electronic medical record comprise numerous structured but uncoded elements, which are not linked to standard terminologies. Reuse of such data for secondary research purposes has gained in importance recently. However, the identification of relevant data elements and the creation of database jobs for extraction, transformation and loading (ETL are challenging: With current methods such as data warehousing, it is not feasible to efficiently maintain and reuse semantically complex data extraction and trans-formation routines. We present an ontology-supported approach to overcome this challenge by making use of abstraction: Instead of defining ETL procedures at the database level, we use ontologies to organize and describe the medical concepts of both the source system and the target system. Instead of using unique, specifically developed SQL statements or ETL jobs, we define declarative transformation rules within ontologies and illustrate how these constructs can then be used to automatically generate SQL code to perform the desired ETL procedures. This demonstrates how a suitable level of abstraction may not only aid the interpretation of clinical data, but can also foster the reutilization of methods for un-locking it.

  14. Domain XML semantic integration based on extraction rules and ontology mapping

    Directory of Open Access Journals (Sweden)

    Huayu LI

    2016-08-01

    Full Text Available A plenty of XML documents exist in petroleum engineering field, but traditional XML integration solution can’t provide semantic query, which leads to low data use efficiency. In light of WeXML(oil&gas well XML data semantic integration and query requirement, this paper proposes a semantic integration method based on extraction rules and ontology mapping. The method firstly defines a series of extraction rules with which elements and properties of WeXML Schema are mapped to classes and properties in WeOWL ontology, respectively; secondly, an algorithm is used to transform WeXML documents into WeOWL instances. Because WeOWL provides limited semantics, ontology mappings between two ontologies are then built to explain class and property of global ontology with terms of WeOWL, and semantic query based on global domain concepts model is provided. By constructing a WeXML data semantic integration prototype system, the proposed transformational rule, the transfer algorithm and the mapping rule are tested.

  15. Knowledge Representation and Management, It's Time to Integrate!

    Science.gov (United States)

    Dhombres, F; Charlet, J

    2017-08-01

    Objectives: To select, present, and summarize the best papers published in 2016 in the field of Knowledge Representation and Management (KRM). Methods: A comprehensive and standardized review of the medical informatics literature was performed based on a PubMed query. Results: Among the 1,421 retrieved papers, the review process resulted in the selection of four best papers focused on the integration of heterogeneous data via the development and the alignment of terminological resources. In the first article, the authors provide a curated and standardized version of the publicly available US FDA Adverse Event Reporting System. Such a resource will improve the quality of the underlying data, and enable standardized analyses using common vocabularies. The second article describes a project developed in order to facilitate heterogeneous data integration in the i2b2 framework. The originality is to allow users integrate the data described in different terminologies and to build a new repository, with a unique model able to support the representation of the various data. The third paper is dedicated to model the association between multiple phenotypic traits described within the Human Phenotype Ontology (HPO) and the corresponding genotype in the specific context of rare diseases (rare variants). Finally, the fourth paper presents solutions to annotation-ontology mapping in genome-scale data. Of particular interest in this work is the Experimental Factor Ontology (EFO) and its generic association model, the Ontology of Biomedical AssociatioN (OBAN). Conclusion: Ontologies have started to show their efficiency to integrate medical data for various tasks in medical informatics: electronic health records data management, clinical research, and knowledge-based systems development. Georg Thieme Verlag KG Stuttgart.

  16. WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

    Energy Technology Data Exchange (ETDEWEB)

    Gabriel, P. [University of Pennsylvania (United States)

    2015-06-15

    Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented.

  17. WE-F-BRB-01: The Power of Ontologies and Standardized Terminologies for Capturing Clinical Knowledge

    International Nuclear Information System (INIS)

    Gabriel, P.

    2015-01-01

    Advancements in informatics in radiotherapy are opening up opportunities to improve our ability to assess treatment plans. Models on individualizing patient dose constraints from prior patient data and shape relationships have been extensively researched and are now making their way into commercial products. New developments in knowledge based treatment planning involve understanding the impact of the radiation dosimetry on the patient. Akin to radiobiology models that have driven intensity modulated radiotherapy optimization, toxicity and outcome predictions based on treatment plans and prior patient experiences may be the next step in knowledge based planning. In order to realize these predictions, it is necessary to understand how the clinical information can be captured, structured and organized with ontologies and databases designed for recall. Large databases containing radiation dosimetry and outcomes present the opportunity to evaluate treatment plans against predictions of toxicity and disease response. Such evaluations can be based on dose volume histogram or even the full 3-dimensional dose distribution and its relation to the critical anatomy. This session will provide an understanding of ontologies and standard terminologies used to capture clinical knowledge into structured databases; How data can be organized and accessed to utilize the knowledge in planning; and examples of research and clinical efforts to incorporate that clinical knowledge into planning for improved care for our patients. Learning Objectives: Understand the role of standard terminologies, ontologies and data organization in oncology Understand methods to capture clinical toxicity and outcomes in a clinical setting Understand opportunities to learn from clinical data and its application to treatment planning Todd McNutt receives funding from Philips, Elekta and Toshiba for some of the work presented

  18. Semantic Data Integration and Ontology Use within the Global Earth Observation System of Systems (GEOSS) Global Water Cycle Data Integration System

    Science.gov (United States)

    Pozzi, W.; Fekete, B.; Piasecki, M.; McGuinness, D.; Fox, P.; Lawford, R.; Vorosmarty, C.; Houser, P.; Imam, B.

    2008-12-01

    The inadequacies of water cycle observations for monitoring long-term changes in the global water system, as well as their feedback into the climate system, poses a major constraint on sustainable development of water resources and improvement of water management practices. Hence, The Group on Earth Observations (GEO) has established Task WA-08-01, "Integration of in situ and satellite data for water cycle monitoring," an integrative initiative combining different types of satellite and in situ observations related to key variables of the water cycle with model outputs for improved accuracy and global coverage. This presentation proposes development of the Rapid, Integrated Monitoring System for the Water Cycle (Global-RIMS)--already employed by the GEO Global Terrestrial Network for Hydrology (GTN-H)--as either one of the main components or linked with the Asian system to constitute the modeling system of GEOSS for water cycle monitoring. We further propose expanded, augmented capability to run multiple grids to embrace some of the heterogeneous methods and formats of the Earth Science, Hydrology, and Hydraulic Engineering communities. Different methodologies are employed by the Earth Science (land surface modeling), the Hydrological (GIS), and the Hydraulic Engineering Communities; with each community employing models that require different input data. Data will be routed as input variables to the models through web services, allowing satellite and in situ data to be integrated together within the modeling framework. Semantic data integration will provide the automation to enable this system to operate in near-real-time. Multiple data collections for ground water, precipitation, soil moisture satellite data, such as SMAP, and lake data will require multiple low level ontologies, and an upper level ontology will permit user-friendly water management knowledge to be synthesized. These ontologies will have to have overlapping terms mapped and linked together. so

  19. An Integrated Knowledge Management System

    Directory of Open Access Journals (Sweden)

    Vasile Mazilescu

    2014-11-01

    Full Text Available The aim of this paper is to present a Knowledge Management System based on Fuzzy Logic (FLKMS, a real-time expert system to meet the challenges of the dynamic environment. The main feature of our integrated shell FLKMS is that it models and integrates the temporal relationships between the dynamic of the evolution of an economic process with some fuzzy inferential methods, using a knowledge model for control, embedded within the expert system’s operational knowledge base.

  20. An Ontology-Based Knowledge Modelling for a Sustainability Assessment Domain

    Directory of Open Access Journals (Sweden)

    Agnieszka Konys

    2018-01-01

    Full Text Available Sustainability assessment has received more and more attention from researchers and it offers a large number of opportunities to measure and evaluate the level of its accomplishment. However, proper selection of a particular sustainability assessment approach, reflecting problem properties and the evaluator’s preferences, is a complex and important issue. Due to an existing number of different approaches dedicated to assessing, supporting, or measuring the level of sustainability and their structure oriented on the particular domain usage, problems with accurate matching frequently occur. On the other hand, the efficiency of sustainability assessment depends on the available knowledge of the ongoing capabilities. Additionally, actual research trends confirm that knowledge engineering gives a method to handle domain knowledge practically and effectively. Unfortunately, literature studies confirm that there is a lack of knowledge systematization in the sustainability assessment domain, however. The practical application of knowledge-based mechanisms may cover this gap. In this paper, we provide formal, practical and technological guidance to a knowledge management-based approach to sustainability assessment. We propose ontology as a form of knowledge conceptualization and using knowledge engineering, we make gathered knowledge publicly available and reusable, especially in terms of interoperability of collected knowledge.

  1. An Approach to Formalizing Ontology Driven Semantic Integration: Concepts, Dimensions and Framework

    Science.gov (United States)

    Gao, Wenlong

    2012-01-01

    The ontology approach has been accepted as a very promising approach to semantic integration today. However, because of the diversity of focuses and its various connections to other research domains, the core concepts, theoretical and technical approaches, and research areas of this domain still remain unclear. Such ambiguity makes it difficult to…

  2. GGDonto ontology as a knowledge-base for genetic diseases and disorders of glycan metabolism and their causative genes.

    Science.gov (United States)

    Solovieva, Elena; Shikanai, Toshihide; Fujita, Noriaki; Narimatsu, Hisashi

    2018-04-18

    Inherited mutations in glyco-related genes can affect the biosynthesis and degradation of glycans and result in severe genetic diseases and disorders. The Glyco-Disease Genes Database (GDGDB), which provides information about these diseases and disorders as well as their causative genes, has been developed by the Research Center for Medical Glycoscience (RCMG) and released in April 2010. GDGDB currently provides information on about 80 genetic diseases and disorders caused by single-gene mutations in glyco-related genes. Many biomedical resources provide information about genetic disorders and genes involved in their pathogenesis, but resources focused on genetic disorders known to be related to glycan metabolism are lacking. With the aim of providing more comprehensive knowledge on genetic diseases and disorders of glycan biosynthesis and degradation, we enriched the content of the GDGDB database and improved the methods for data representation. We developed the Genetic Glyco-Diseases Ontology (GGDonto) and a RDF/SPARQL-based user interface using Semantic Web technologies. In particular, we represented the GGDonto content using Semantic Web languages, such as RDF, RDFS, SKOS, and OWL, and created an interactive user interface based on SPARQL queries. This user interface provides features to browse the hierarchy of the ontology, view detailed information on diseases and related genes, and find relevant background information. Moreover, it provides the ability to filter and search information by faceted and keyword searches. Focused on the molecular etiology, pathogenesis, and clinical manifestations of genetic diseases and disorders of glycan metabolism and developed as a knowledge-base for this scientific field, GGDonto provides comprehensive information on various topics, including links to aid the integration with other scientific resources. The availability and accessibility of this knowledge will help users better understand how genetic defects impact the

  3. Hierarchical Role Ontology-based Assessment of Trainee’s Conceptual Knowledge

    Directory of Open Access Journals (Sweden)

    V. V. Belous

    2014-01-01

    Full Text Available We believe that this knowledge base of training system structure is based on the subject semantic network (SSN containing concepts of subject domain and relations between them. The SSN is represented as a direct graph, with tops corresponding to concepts, and arcs corresponding to relations. We consider a technique for trainee’s conceptual knowledge assessment using the cognitive maps of trainees (CMT, each of which formalizes his ideas of some SSN fragment and theoretically coincides with this fragment. Assessment of trainee’s achievement of this SSN fragment comes to comparison of SSN subgraph, corresponding to this fragment, with the direct graph, which is defined by the corresponding CMT.A number of important subject domains possess the property that concepts in them have the attribute called ‘role’, and roles of concepts can be linearly sorted. The direct graph SSN, corresponding to such ontology can be presented in a tiered form.The work concerns the assessment of trainee’s conceptual knowledge in the subject domains of this class. The work represents the SSN and CMT models used, describes the offered methods to create CMT, as well metrics for trainee’s achievement of the conceptual knowledge based on his CMT.The main results of work are the following: the model of the semantic network corresponding to hierarchical role ontology, and also a model of a trainee’s cognitive map of are offered, methods for creating the trainee’s cognitive maps are developed, metrics of trainee’s achievement of conceptual knowledge are suggested.

  4. The Evidence-base for Using Ontologies and Semantic Integration Methodologies to Support Integrated Chronic Disease Management in Primary and Ambulatory Care: Realist Review. Contribution of the IMIA Primary Health Care Informatics WG.

    Science.gov (United States)

    Liyanage, H; Liaw, S-T; Kuziemsky, C; Terry, A L; Jones, S; Soler, J K; de Lusignan, S

    2013-01-01

    Most chronic diseases are managed in primary and ambulatory care. The chronic care model (CCM) suggests a wide range of community, technological, team and patient factors contribute to effective chronic disease management. Ontologies have the capability to enable formalised linkage of heterogeneous data sources as might be found across the elements of the CCM. To describe the evidence base for using ontologies and other semantic integration methods to support chronic disease management. We reviewed the evidence-base for the use of ontologies and other semantic integration methods within and across the elements of the CCM. We report them using a realist review describing the context in which the mechanism was applied, and any outcome measures. Most evidence was descriptive with an almost complete absence of empirical research and important gaps in the evidence-base. We found some use of ontologies and semantic integration methods for community support of the medical home and for care in the community. Ubiquitous information technology (IT) and other IT tools were deployed to support self-management support, use of shared registries, health behavioural models and knowledge discovery tools to improve delivery system design. Data quality issues restricted the use of clinical data; however there was an increased use of interoperable data and health system integration. Ontologies and semantic integration methods are emergent with limited evidence-base for their implementation. However, they have the potential to integrate the disparate community wide data sources to provide the information necessary for effective chronic disease management.

  5. Effective Tutorial Ontology Modeling on Organic Rice Farming for Non-Science & Technology Educated Farmers Using Knowledge Engineering

    Science.gov (United States)

    Yanchinda, Jirawit; Chakpitak, Nopasit; Yodmongkol, Pitipong

    2015-01-01

    Knowledge of the appropriate technologies for sustainable development projects has encouraged grass roots development, which has in turn promoted sustainable and successful community development, which a requirement is to share and reuse this knowledge effectively. This research aims to propose a tutorial ontology effectiveness modeling on organic…

  6. Developing an ontological explosion knowledge base for business continuity planning purposes.

    Science.gov (United States)

    Mohammadfam, Iraj; Kalatpour, Omid; Golmohammadi, Rostam; Khotanlou, Hasan

    2013-01-01

    Industrial accidents are among the most known challenges to business continuity. Many organisations have lost their reputation following devastating accidents. To manage the risks of such accidents, it is necessary to accumulate sufficient knowledge regarding their roots, causes and preventive techniques. The required knowledge might be obtained through various approaches, including databases. Unfortunately, many databases are hampered by (among other things) static data presentations, a lack of semantic features, and the inability to present accident knowledge as discrete domains. This paper proposes the use of Protégé software to develop a knowledge base for the domain of explosion accidents. Such a structure has a higher capability to improve information retrieval compared with common accident databases. To accomplish this goal, a knowledge management process model was followed. The ontological explosion knowledge base (EKB) was built for further applications, including process accident knowledge retrieval and risk management. The paper will show how the EKB has a semantic feature that enables users to overcome some of the search constraints of existing accident databases.

  7. Collaborative ontology development for the geosciences

    NARCIS (Netherlands)

    Kalbasi Khoramdashti, R.; Janowicz, K.; Reitsma, F.; Boerboom, L.G.J.; Alasheikh, A.

    2014-01-01

    Ontology-based information publishing, retrieval, reuse, and integration have become popular research topics to address the challenges involved in exchanging data between heterogeneous sources. However, in most cases ontologies are still developed in a centralized top-down manner by a few knowledge

  8. The eXtensible ontology development (XOD) principles and tool implementation to support ontology interoperability.

    Science.gov (United States)

    He, Yongqun; Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; Overton, James A; Ong, Edison

    2018-01-12

    Ontologies are critical to data/metadata and knowledge standardization, sharing, and analysis. With hundreds of biological and biomedical ontologies developed, it has become critical to ensure ontology interoperability and the usage of interoperable ontologies for standardized data representation and integration. The suite of web-based Ontoanimal tools (e.g., Ontofox, Ontorat, and Ontobee) support different aspects of extensible ontology development. By summarizing the common features of Ontoanimal and other similar tools, we identified and proposed an "eXtensible Ontology Development" (XOD) strategy and its associated four principles. These XOD principles reuse existing terms and semantic relations from reliable ontologies, develop and apply well-established ontology design patterns (ODPs), and involve community efforts to support new ontology development, promoting standardized and interoperable data and knowledge representation and integration. The adoption of the XOD strategy, together with robust XOD tool development, will greatly support ontology interoperability and robust ontology applications to support data to be Findable, Accessible, Interoperable and Reusable (i.e., FAIR).

  9. Toward a Blended Ontology: Applying Knowledge Systems to Compare Therapeutic and Toxicological Nanoscale Domains

    Directory of Open Access Journals (Sweden)

    Christopher M. Grulke

    2012-01-01

    Full Text Available Bionanomedicine and environmental research share need common terms and ontologies. This study applied knowledge systems, data mining, and bibliometrics used in nano-scale ADME research from 1991 to 2011. The prominence of nano-ADME in environmental research began to exceed the publication rate in medical research in 2006. That trend appears to continue as a result of the growing products in commerce using nanotechnology, that is, 5-fold growth in number of countries with nanomaterials research centers. Funding for this research virtually did not exist prior to 2002, whereas today both medical and environmental research is funded globally. Key nanoparticle research began with pharmacology and therapeutic drug-delivery and contrasting agents, but the advances have found utility in the environmental research community. As evidence ultrafine aerosols and aquatic colloids research increased 6-fold, indicating a new emphasis on environmental nanotoxicology. User-directed expert elicitation from the engineering and chemical/ADME domains can be combined with appropriate Boolean logic and queries to define the corpus of nanoparticle interest. The study combined pharmacological expertise and informatics to identify the corpus by building logical conclusions and observations. Publication records informatics can lead to an enhanced understanding the connectivity between fields, as well as overcoming the differences in ontology between the fields.

  10. Ontology of Public Health in University Curriculum: Exploring Basic Elements of an Interdisciplinary Field of Knowledge

    Science.gov (United States)

    Islam, Zahirul

    2017-01-01

    Public health has constituted itself as a distinct academic discipline. The present paper attempts to understand ontology of this discipline. A study has recently been carried out which concerns, first, conceptualization of ontology of public health, secondly, nature of public health, and thirdly, curriculum development. Ontology is a…

  11. Methodology for Automatic Ontology Generation Using Database Schema Information

    Directory of Open Access Journals (Sweden)

    JungHyen An

    2018-01-01

    Full Text Available An ontology is a model language that supports the functions to integrate conceptually distributed domain knowledge and infer relationships among the concepts. Ontologies are developed based on the target domain knowledge. As a result, methodologies to automatically generate an ontology from metadata that characterize the domain knowledge are becoming important. However, existing methodologies to automatically generate an ontology using metadata are required to generate the domain metadata in a predetermined template, and it is difficult to manage data that are increased on the ontology itself when the domain OWL (Ontology Web Language individuals are continuously increased. The database schema has a feature of domain knowledge and provides structural functions to efficiently process the knowledge-based data. In this paper, we propose a methodology to automatically generate ontologies and manage the OWL individual through an interaction of the database and the ontology. We describe the automatic ontology generation process with example schema and demonstrate the effectiveness of the automatically generated ontology by comparing it with existing ontologies using the ontology quality score.

  12. Ontology-based integration of topographic data sets

    NARCIS (Netherlands)

    Uitermark, HT; van Oosterom, PJM; Mars, NJI; Molenaar, M

    The integration of topographic data sets is defined as the process of establishing relationships between corresponding object instances in different, autonomously produced, topographic data sets of the same geographic space. The problem of integrating topographic data sets is in finding these

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

    Science.gov (United States)

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

    2015-01-01

    This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Primary care data is the single richest source of routine health care data. However its use, both in research and clinical work, often requires data from multiple clinical sites, clinical trials databases and registries. Data integration and interoperability are therefore of utmost importance. TRANSFoRm's general approach relies on a unified interoperability framework, described in a previous paper. We developed a core ontology for an interoperability framework based on data mediation. This article presents how such an ontology, the Clinical Data Integration Model (CDIM), can be designed to support, in conjunction with appropriate terminologies, biomedical data federation within TRANSFoRm, an EU FP7 project that aims to develop the digital infrastructure for a learning healthcare system in European Primary Care. TRANSFoRm utilizes a unified structural / terminological interoperability framework, based on the local-as-view mediation paradigm. Such an approach mandates the global information model to describe the domain of interest independently of the data sources to be explored. Following a requirement analysis process, no ontology focusing on primary care research was identified and, thus we designed a realist ontology based on Basic Formal Ontology to support our framework in collaboration with various terminologies used in primary care. The resulting ontology has 549 classes and 82 object properties and is used to support data integration for TRANSFoRm's use cases. Concepts identified by researchers were successfully expressed in queries using CDIM and pertinent terminologies. As an example, we illustrate how, in TRANSFoRm, the Query Formulation Workbench can capture eligibility criteria in a computable representation, which is based on CDIM. A unified mediation approach to semantic interoperability provides a

  14. Muscle Research and Gene Ontology: New standards for improved data integration.

    Science.gov (United States)

    Feltrin, Erika; Campanaro, Stefano; Diehl, Alexander D; Ehler, Elisabeth; Faulkner, Georgine; Fordham, Jennifer; Gardin, Chiara; Harris, Midori; Hill, David; Knoell, Ralph; Laveder, Paolo; Mittempergher, Lorenza; Nori, Alessandra; Reggiani, Carlo; Sorrentino, Vincenzo; Volpe, Pompeo; Zara, Ivano; Valle, Giorgio; Deegan, Jennifer

    2009-01-29

    The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO) Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic) experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  15. Muscle Research and Gene Ontology: New standards for improved data integration

    Directory of Open Access Journals (Sweden)

    Nori Alessandra

    2009-01-01

    Full Text Available Abstract Background The Gene Ontology Project provides structured controlled vocabularies for molecular biology that can be used for the functional annotation of genes and gene products. In a collaboration between the Gene Ontology (GO Consortium and the muscle biology community, we have made large-scale additions to the GO biological process and cellular component ontologies. The main focus of this ontology development work concerns skeletal muscle, with specific consideration given to the processes of muscle contraction, plasticity, development, and regeneration, and to the sarcomere and membrane-delimited compartments. Our aims were to update the existing structure to reflect current knowledge, and to resolve, in an accommodating manner, the ambiguity in the language used by the community. Results The updated muscle terminologies have been incorporated into the GO. There are now 159 new terms covering critical research areas, and 57 existing terms have been improved and reorganized to follow their usage in muscle literature. Conclusion The revised GO structure should improve the interpretation of data from high-throughput (e.g. microarray and proteomic experiments in the area of muscle science and muscle disease. We actively encourage community feedback on, and gene product annotation with these new terms. Please visit the Muscle Community Annotation Wiki http://wiki.geneontology.org/index.php/Muscle_Biology.

  16. Integrating Ontology Debugging and Matching into the eXtreme Design Methodology

    OpenAIRE

    Dragisic, Zlatan; Lambrix, Patrick; Blomqvist, Eva

    2015-01-01

    Ontology design patterns (ODPs) and related ontology development methodologies were designed as ways of sharing and reusing best practices in ontology engineering. However, while the use of these reduces the number of issues in the resulting ontologies defects can still be introduced into the ontology due to improper use or misinterpretation of the patterns. Thus, the quality of the developed ontologies is still a major concern. In this paper we address this issue by describing how ontology d...

  17. Representation and integration of sociological knowledge using knowledge graphs

    NARCIS (Netherlands)

    Popping, R; Strijker, [No Value

    1997-01-01

    The representation and integration of sociological knowledge using knowledge graphs, a specific kind of semantic network, is discussed. Knowledge it systematically searched this reveals. inconsistencies, reducing superfluous research and knowledge, and showing gaps in a theory. This representation

  18. Ontological Planning

    Directory of Open Access Journals (Sweden)

    Ahmet Alkan

    2017-12-01

    • Is it possible to redefine ontology within the hierarchical structure of planning? We are going to seek answers to some of these questions within the limited scope of this paper and we are going to offer the rest for discussion by just asking them. In light of these assessments, drawing attention, based on ontological knowledge relying on the wholeness of universe, to the question, on macro level planning, of whether or not the ontological realities of man, energy and movements of thinking can provide macro data for planning on a universal level as important factors affecting mankind will be one of the limited objectives of the paper.

  19. Building ontologies with basic formal ontology

    CERN Document Server

    Arp, Robert; Spear, Andrew D.

    2015-01-01

    In the era of "big data," science is increasingly information driven, and the potential for computers to store, manage, and integrate massive amounts of data has given rise to such new disciplinary fields as biomedical informatics. Applied ontology offers a strategy for the organization of scientific information in computer-tractable form, drawing on concepts not only from computer and information science but also from linguistics, logic, and philosophy. This book provides an introduction to the field of applied ontology that is of particular relevance to biomedicine, covering theoretical components of ontologies, best practices for ontology design, and examples of biomedical ontologies in use. After defining an ontology as a representation of the types of entities in a given domain, the book distinguishes between different kinds of ontologies and taxonomies, and shows how applied ontology draws on more traditional ideas from metaphysics. It presents the core features of the Basic Formal Ontology (BFO), now u...

  20. Transdisciplinary knowledge integration : cases from integrated assessment and vulnerability assessment

    NARCIS (Netherlands)

    Hinkel, J.

    2008-01-01

    Keywords: climate change, integrated assessment, knowledge integration, transdisciplinary research, vulnerability, vulnerability assessment.
    This thesis explores how transdisciplinary knowledge integration can be facilitated in the context of integrated assessments and vulnerability

  1. Automated Ontology Alignment with Fuselets for Community of Interest (COI) Integration

    National Research Council Canada - National Science Library

    Starz, James; Roberts, Joe

    2008-01-01

    Discusses the ontology alignment problem by presenting a tool called Ontrapro-the Ontology Translation Protocol, which allows users to apply a myriad of ontology alignment algorithms in an iterative fashion...

  2. Overcoming Interoperability Weaknesses in e-Government Processes: Organizing and Sharing Knowledge in Regional Development Programs Using Ontologies

    Science.gov (United States)

    Scorza, Francesco; Casas, Giuseppe Las; Murgante, Beniamino

    European Regional Policy produced several generations of programmes at both National and Regional levels. Such a complex framework tends to increase multi-level governance in the period 2007-2013, promoting a wider participation of stakeholders (including Public Administration, Local Communities, Enterprises, etc). This process has been usually accompanied by e-tools for the management of bottom-up processes, with several instances related to common problems of participation processes. Communication between "programmer" and categories of beneficiaries always presented weakness due to the ineffective system of management knowledge within the process. Relevant issues in the framework of regional development programmes are: Do stakeholders understand the meaning of general and sectoral policies? Are citizens aware of technical instruments implementing such policies? Are they conscious of ex-ante comprehensive context analysis and/or can they share possible future scenarios? A way to tackle these problems is the use of ontologies. In this work we present the structural elements of the ontology of regional development programmes analyzing major steps of the ontology design and nodal phases of the ontology building (i.e. consensus on relations and restrictions, switch from glossary to taxonomy). The result of such an application is an ontology of regional development containing more than one hundred classes.

  3. Towards an ontology for data quality in integrated chronic disease management: a realist review of the literature.

    Science.gov (United States)

    Liaw, S T; Rahimi, A; Ray, P; Taggart, J; Dennis, S; de Lusignan, S; Jalaludin, B; Yeo, A E T; Talaei-Khoei, A

    2013-01-01

    Effective use of routine data to support integrated chronic disease management (CDM) and population health is dependent on underlying data quality (DQ) and, for cross system use of data, semantic interoperability. An ontological approach to DQ is a potential solution but research in this area is limited and fragmented. Identify mechanisms, including ontologies, to manage DQ in integrated CDM and whether improved DQ will better measure health outcomes. A realist review of English language studies (January 2001-March 2011) which addressed data quality, used ontology-based approaches and is relevant to CDM. We screened 245 papers, excluded 26 duplicates, 135 on abstract review and 31 on full-text review; leaving 61 papers for critical appraisal. Of the 33 papers that examined ontologies in chronic disease management, 13 defined data quality and 15 used ontologies for DQ. Most saw DQ as a multidimensional construct, the most used dimensions being completeness, accuracy, correctness, consistency and timeliness. The majority of studies reported tool design and development (80%), implementation (23%), and descriptive evaluations (15%). Ontological approaches were used to address semantic interoperability, decision support, flexibility of information management and integration/linkage, and complexity of information models. DQ lacks a consensus conceptual framework and definition. DQ and ontological research is relatively immature with little rigorous evaluation studies published. Ontology-based applications could support automated processes to address DQ and semantic interoperability in repositories of routinely collected data to deliver integrated CDM. We advocate moving to ontology-based design of information systems to enable more reliable use of routine data to measure health mechanisms and impacts. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  4. Supplementary Material for: The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants

    KAUST Repository

    Hoehndorf, Robert

    2016-01-01

    Abstract Background The systematic analysis of a large number of comparable plant trait data can support investigations into phylogenetics and ecological adaptation, with broad applications in evolutionary biology, agriculture, conservation, and the functioning of ecosystems. Floras, i.e., books collecting the information on all known plant species found within a region, are a potentially rich source of such plant trait data. Floras describe plant traits with a focus on morphology and other traits relevant for species identification in addition to other characteristics of plant species, such as ecological affinities, distribution, economic value, health applications, traditional uses, and so on. However, a key limitation in systematically analyzing information in Floras is the lack of a standardized vocabulary for the described traits as well as the difficulties in extracting structured information from free text. Results We have developed the Flora Phenotype Ontology (FLOPO), an ontology for describing traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based on phenotype description patterns and automated reasoning to generate the FLOPO. The resulting ontology consists of 25,407 classes and is based on the PO and PATO. The classified ontology closely follows the structure of Plant Ontology in that the primary axis of classification is the observed plant anatomical structure, and more specific traits are then classified based on parthood and subclass relations between anatomical structures as well as subclass relations between phenotypic qualities. Conclusions The FLOPO is primarily intended as a framework based on which plant traits can be integrated computationally across all species and higher taxa of flowering plants. Importantly, it is not intended to replace established

  5. a New Ontological Perspective for Integration of Social and Physical Environments: Disability and Rehabilitation Context

    Science.gov (United States)

    Gharebaghi, Amin; Abolfazl Mostafavi, Mir

    2016-06-01

    Social dimension of environment is an important aspect that should be reflected in research works related to studying the interactions between human and the environment. However, this dimension is usually neglected when representing the environment in geographic information systems for different applications. For instance, disability as a result of the interaction between human and environment is influenced by social and physical dimensions of environment. Although, this aspect is highlighted in most conceptual disability models by defining various taxonomies of the environment, from ontological perspective justifying and connecting social dimension to the physical dimension of the environment is not clearly determined. Integrating social dimension of the environment with its physical dimension for disability studies is a challenging task, which is the main objective of the present study. Here, we review some of the disability models and their perspective about classifying the environment. Then, from ontological perspective, their limitations are discussed and a new approach for the classification of concepts form the environment is presented. This approach facilitates and simplifies integration of social dimension in ontologies for more effective assessment of disability issue in Geographic Information System.

  6. Ontology-based Vaccine and Drug Adverse Event Representation and Theory-guided Systematic Causal Network Analysis toward Integrative Pharmacovigilance Research.

    Science.gov (United States)

    He, Yongqun

    2016-06-01

    Compared with controlled terminologies ( e.g. , MedDRA, CTCAE, and WHO-ART), the community-based Ontology of AEs (OAE) has many advantages in adverse event (AE) classifications. The OAE-derived Ontology of Vaccine AEs (OVAE) and Ontology of Drug Neuropathy AEs (ODNAE) serve as AE knowledge bases and support data integration and analysis. The Immune Response Gene Network Theory explains molecular mechanisms of vaccine-related AEs. The OneNet Theory of Life treats the whole process of a life of an organism as a single complex and dynamic network ( i.e. , OneNet). A new "OneNet effectiveness" tenet is proposed here to expand the OneNet theory. Derived from the OneNet theory, the author hypothesizes that one human uses one single genotype-rooted mechanism to respond to different vaccinations and drug treatments, and experimentally identified mechanisms are manifestations of the OneNet blueprint mechanism under specific conditions. The theories and ontologies interact together as semantic frameworks to support integrative pharmacovigilance research.

  7. FML-based ontological agent for healthcare application with diabetes

    NARCIS (Netherlands)

    Acampora, G.; Lee, C.-S.; Wang, M.-H.

    2009-01-01

    It is well-known that classical ontologies are not sufficient to deal with imprecise and vague knowledge. On the other hand, fuzzy ontologies can effectively solve data and knowledge with uncertainty, most importantly, if they are integrated with innovative methods for developing agents’

  8. Going Deeper or Flatter: Connecting Deep Mapping, Flat Ontologies and the Democratizing of Knowledge

    Directory of Open Access Journals (Sweden)

    Selina Springett

    2015-10-01

    Full Text Available The concept of “deep mapping”, as an approach to place, has been deployed as both a descriptor of a specific suite of creative works and as a set of aesthetic practices. While its definition has been amorphous and adaptive, a number of distinct, yet related, manifestations identify as, or have been identified by, the term. In recent times, it has garnered attention beyond literary discourse, particularly within the “spatial” turn of representation in the humanities and as a result of expanded platforms of data presentation. This paper takes a brief look at the practice of “deep mapping”, considering it as a consciously performative act and tracing a number of its various manifestations. It explores how deep mapping is a reflection of epistemological trends in ontological practices of connectivity and the “flattening” of knowledge systems. In particular those put forward by post structural and cultural theorists, such as Bruno Latour, Gilles Deleuze, and Felix Guattari, as well as by theorists who associate with speculative realism. The concept of deep mapping as an aesthetic, methodological, and ideological tool, enables an approach to place that democratizes knowledge by crossing temporal, spatial, and disciplinary boundaries.

  9. Ontological knowledge engine and health screening data enabled ubiquitous personalized physical fitness (UFIT).

    Science.gov (United States)

    Su, Chuan-Jun; Chiang, Chang-Yu; Chih, Meng-Chun

    2014-03-07

    Good physical fitness generally makes the body less prone to common diseases. A personalized exercise plan that promotes a balanced approach to fitness helps promotes fitness, while inappropriate forms of exercise can have adverse consequences for health. This paper aims to develop an ontology-driven knowledge-based system for generating custom-designed exercise plans based on a user's profile and health status, incorporating international standard Health Level Seven International (HL7) data on physical fitness and health screening. The generated plan exposing Representational State Transfer (REST) style web services which can be accessed from any Internet-enabled device and deployed in cloud computing environments. To ensure the practicality of the generated exercise plans, encapsulated knowledge used as a basis for inference in the system is acquired from domain experts. The proposed Ubiquitous Exercise Plan Generation for Personalized Physical Fitness (UFIT) will not only improve health-related fitness through generating personalized exercise plans, but also aid users in avoiding inappropriate work outs.

  10. Using XML technology for the ontology-based semantic integration of life science databases.

    Science.gov (United States)

    Philippi, Stephan; Köhler, Jacob

    2004-06-01

    Several hundred internet accessible life science databases with constantly growing contents and varying areas of specialization are publicly available via the internet. Database integration, consequently, is a fundamental prerequisite to be able to answer complex biological questions. Due to the presence of syntactic, schematic, and semantic heterogeneities, large scale database integration at present takes considerable efforts. As there is a growing apprehension of extensible markup language (XML) as a means for data exchange in the life sciences, this article focuses on the impact of XML technology on database integration in this area. In detail, a general architecture for ontology-driven data integration based on XML technology is introduced, which overcomes some of the traditional problems in this area. As a proof of concept, a prototypical implementation of this architecture based on a native XML database and an expert system shell is described for the realization of a real world integration scenario.

  11. Effects of an ontology display with history representation on organizational memory information systems.

    Science.gov (United States)

    Hwang, Wonil; Salvendy, Gavriel

    2005-06-10

    Ontologies, as a possible element of organizational memory information systems, appear to support organizational learning. Ontology tools can be used to share knowledge among the members of an organization. However, current ontology-viewing user interfaces of ontology tools do not fully support organizational learning, because most of them lack proper history representation in their display. In this study, a conceptual model was developed that emphasized the role of ontology in the organizational learning cycle and explored the integration of history representation in the ontology display. Based on the experimental results from a split-plot design with 30 participants, two conclusions were derived: first, appropriately selected history representations in the ontology display help users to identify changes in the ontologies; and second, compatibility between types of ontology display and history representation is more important than ontology display and history representation in themselves.

  12. "The Human Condition" as social ontology: Hannah Arendt on society, action and knowledge.

    Science.gov (United States)

    Walsh, Philip

    2011-01-01

    Hannah Arendt is widely regarded as a political theorist who sought to rescue politics from "society," and political theory from the social sciences. This conventional view has had the effect of distracting attention from many of Arendt's most important insights concerning the constitution of "society" and the significance of the social sciences. In this article, I argue that Hannah Arendt's distinctions between labor, work, and action, as these are discussed in "The Human Condition" and elsewhere, are best understood as a set of claims about the fundamental structures of human societies. Understanding Arendt in this way introduces interesting parallels between Arendt's work and both classical and contemporary sociology. From this I draw a number of conclusions concerning Arendt's conception of "society," and extend these insights into two contemporary debates within contemporary theoretical sociology: the need for a differentiated ontology of the social world, and the changing role that novel forms of knowledge play in contemporary society as major sources of social change and order.

  13. Worm Phenotype Ontology: Integrating phenotype data within and beyond the C. elegans community

    Directory of Open Access Journals (Sweden)

    Yook Karen

    2011-01-01

    Full Text Available Abstract Background Caenorhabditis elegans gene-based phenotype information dates back to the 1970's, beginning with Sydney Brenner and the characterization of behavioral and morphological mutant alleles via classical genetics in order to understand nervous system function. Since then C. elegans has become an important genetic model system for the study of basic biological and biomedical principles, largely through the use of phenotype analysis. Because of the growth of C. elegans as a genetically tractable model organism and the development of large-scale analyses, there has been a significant increase of phenotype data that needs to be managed and made accessible to the research community. To do so, a standardized vocabulary is necessary to integrate phenotype data from diverse sources, permit integration with other data types and render the data in a computable form. Results We describe a hierarchically structured, controlled vocabulary of terms that can be used to standardize phenotype descriptions in C. elegans, namely the Worm Phenotype Ontology (WPO. The WPO is currently comprised of 1,880 phenotype terms, 74% of which have been used in the annotation of phenotypes associated with greater than 18,000 C. elegans genes. The scope of the WPO is not exclusively limited to C. elegans biology, rather it is devised to also incorporate phenotypes observed in related nematode species. We have enriched the value of the WPO by integrating it with other ontologies, thereby increasing the accessibility of worm phenotypes to non-nematode biologists. We are actively developing the WPO to continue to fulfill the evolving needs of the scientific community and hope to engage researchers in this crucial endeavor. Conclusions We provide a phenotype ontology (WPO that will help to facilitate data retrieval, and cross-species comparisons within the nematode community. In the larger scientific community, the WPO will permit data integration, and

  14. Integration of the Gene Ontology into an object-oriented architecture

    Directory of Open Access Journals (Sweden)

    Zheng W Jim

    2005-05-01

    Full Text Available Abstract Background To standardize gene product descriptions, a formal vocabulary defined as the Gene Ontology (GO has been developed. GO terms have been categorized into biological processes, molecular functions, and cellular components. However, there is no single representation that integrates all the terms into one cohesive model. Furthermore, GO definitions have little information explaining the underlying architecture that forms these terms, such as the dynamic and static events occurring in a process. In contrast, object-oriented models have been developed to show dynamic and static events. A portion of the TGF-beta signaling pathway, which is involved in numerous cellular events including cancer, differentiation and development, was used to demonstrate the feasibility of integrating the Gene Ontology into an object-oriented model. Results Using object-oriented models we have captured the static and dynamic events that occur during a representative GO process, "transforming growth factor-beta (TGF-beta receptor complex assembly" (GO:0007181. Conclusion We demonstrate that the utility of GO terms can be enhanced by object-oriented technology, and that the GO terms can be integrated into an object-oriented model by serving as a basis for the generation of object functions and attributes.

  15. Managing heterogeneous knowledge: A Theory of External Knowledge Integration

    NARCIS (Netherlands)

    Kraaijenbrink, Jeroen; Wijnhoven, Alphonsus B.J.M.

    2008-01-01

    Knowledge integration has been theorised at the levels of organisations and inter-organisational dyads. However, no theory exists yet of the integration of knowledge from an organisation's environment. This paper addresses this void in the literature by presenting a theory of external knowledge

  16. Integration of the social environment in a mobility ontology for people with motor disabilities.

    Science.gov (United States)

    Gharebaghi, Amin; Mostafavi, Mir-Abolfazl; Edwards, Geoffrey; Fougeyrollas, Patrick; Gamache, Stéphanie; Grenier, Yan

    2017-07-07

    Our contemporary understanding of disability is rooted in the idea that disability is the product of human-environment interaction processes. People may be functionally limited, but this becomes a disability only when they engage with their immediate social and physical environments. Any attempt to address issues of mobility in relation to people with disabilities should be grounded in an ontology that encompasses this understanding. The objective of this study is to provide a methodology to integrate the social and physical environments in the development of a mobility ontology for people with motor disabilities (PWMD). We propose to create subclasses of concepts based on a Nature-Development distinction rather than creating separate social and physical subclasses. This allows the relationships between social and physical elements to be modelled in a more compact and efficient way by specifying them locally within each entity, and better accommodates the complexities of the human-environment interaction as well. Based on this approach, an ontology for mobility of PWMD considering four main elements - the social and physical environmental factors, human factors, life habits related to mobility and possible goals of mobility - is presented. We demonstrate that employing the Nature-Development perspective facilitates the process of developing useful ontologies, especially for defining the relationships between the social and physical parts of the environment. This is a fundamental issue for modelling the interaction between humans and their social and physical environments for a broad range of applications, including the development of geospatial assistive technologies for navigation of PWMD. Implications for rehabilitation The proposed perspective may actually have much broader interests beyond the issue of disability - much of the interesting dynamics in city development arises from the interaction between human-developed components - the built environment and its

  17. NanoParticle Ontology for Cancer Nanotechnology Research

    Science.gov (United States)

    Thomas, Dennis G.; Pappu, Rohit V.; Baker, Nathan A.

    2010-01-01

    Data generated from cancer nanotechnology research are so diverse and large in volume that it is difficult to share and efficiently use them without informatics tools. In particular, ontologies that provide a unifying knowledge framework for annotating the data are required to facilitate the semantic integration, knowledge-based searching, unambiguous interpretation, mining and inferencing of the data using informatics methods. In this paper, we discuss the design and development of NanoParticle Ontology (NPO), which is developed within the framework of the Basic Formal Ontology (BFO), and implemented in the Ontology Web Language (OWL) using well-defined ontology design principles. The NPO was developed to represent knowledge underlying the preparation, chemical composition, and characterization of nanomaterials involved in cancer research. Public releases of the NPO are available through BioPortal website, maintained by the National Center for Biomedical Ontology. Mechanisms for editorial and governance processes are being developed for the maintenance, review, and growth of the NPO. PMID:20211274

  18. MultiLoc2: integrating phylogeny and Gene Ontology terms improves subcellular protein localization prediction

    Directory of Open Access Journals (Sweden)

    Kohlbacher Oliver

    2009-09-01

    Full Text Available Abstract Background Knowledge of subcellular localization of proteins is crucial to proteomics, drug target discovery and systems biology since localization and biological function are highly correlated. In recent years, numerous computational prediction methods have been developed. Nevertheless, there is still a need for prediction methods that show more robustness and higher accuracy. Results We extended our previous MultiLoc predictor by incorporating phylogenetic profiles and Gene Ontology terms. Two different datasets were used for training the system, resulting in two versions of this high-accuracy prediction method. One version is specialized for globular proteins and predicts up to five localizations, whereas a second version covers all eleven main eukaryotic subcellular localizations. In a benchmark study with five localizations, MultiLoc2 performs considerably better than other methods for animal and plant proteins and comparably for fungal proteins. Furthermore, MultiLoc2 performs clearly better when using a second dataset that extends the benchmark study to all eleven main eukaryotic subcellular localizations. Conclusion MultiLoc2 is an extensive high-performance subcellular protein localization prediction system. By incorporating phylogenetic profiles and Gene Ontology terms MultiLoc2 yields higher accuracies compared to its previous version. Moreover, it outperforms other prediction systems in two benchmarks studies. MultiLoc2 is available as user-friendly and free web-service, available at: http://www-bs.informatik.uni-tuebingen.de/Services/MultiLoc2.

  19. The EDEN-IW ontology model for sharing knowledge and water quality data between heterogenous databases

    DEFF Research Database (Denmark)

    Stjernholm, M.; Poslad, S.; Zuo, L.

    2004-01-01

    The Environmental Data Exchange Network for Inland Water (EDEN-IW) project's main aim is to develop a system for making disparate and heterogeneous databases of Inland Water quality more accessible to users. The core technology is based upon a combination of: ontological model to represent...... a Semantic Web based data model for IW; software agents as an infrastructure to share and reason about the IW se-mantic data model and XML to make the information accessible to Web portals and mainstream Web services. This presentation focuses on the Semantic Web or Onto-logical model. Currently, we have...

  20. XML, Ontologies, and Their Clinical Applications.

    Science.gov (United States)

    Yu, Chunjiang; Shen, Bairong

    2016-01-01

    The development of information technology has resulted in its penetration into every area of clinical research. Various clinical systems have been developed, which produce increasing volumes of clinical data. However, saving, exchanging, querying, and exploiting these data are challenging issues. The development of Extensible Markup Language (XML) has allowed the generation of flexible information formats to facilitate the electronic sharing of structured data via networks, and it has been used widely for clinical data processing. In particular, XML is very useful in the fields of data standardization, data exchange, and data integration. Moreover, ontologies have been attracting increased attention in various clinical fields in recent years. An ontology is the basic level of a knowledge representation scheme, and various ontology repositories have been developed, such as Gene Ontology and BioPortal. The creation of these standardized repositories greatly facilitates clinical research in related fields. In this chapter, we discuss the basic concepts of XML and ontologies, as well as their clinical applications.

  1. Designing Critique for Knowledge Integration

    Science.gov (United States)

    Sato, Mie Elissa

    Generating explanations is central to science and has the potential to have a powerful impact on students' conceptual understanding in science instruction. However, improving conceptual understanding by generating explanations is a fraught affair: students may struggle with the sense of false clarity that may arise from generating explanations, fail to detect gaps in their understanding, and dismiss salient information that contradict their beliefs. Critiquing explanations has the potential to counteract these pitfalls by exposing students to alternative ideas to contrast with their own. This dissertation seeks to clarify how to design critique in technology-enhanced science instruction to support students in revising their explanations about scientific phenomena, and in doing so, refining their conceptual understanding. Using the Knowledge Integration framework, I revised two technology-enhanced curriculum units, Plate Tectonics and Global Climate Change, in a design partnership between teachers, researchers, and technologists. I conducted a series of studies with sixth-grade students to investigate the conditions under which guided critique of explanations can support revision. The pilot critique study investigated the impact of the revised Plate Tectonics unit on students' understanding of convection, as well as of a preliminary design of critique where students generated and applied their own criteria for what makes a good explanation in science. The guidance study explored how incorporating a complex selection task that features meta-explanatory criteria into critique supports students in distinguishing among different criteria, as well as how students use peer or expert guidance on their initial explanation during revision. The critique study investigated how designing critique with a complex selection task that features plausible alternative ideas and giving guidance on students' critiques support students in distinguishing among a range of relevant ideas

  2. Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies

    Directory of Open Access Journals (Sweden)

    Sai Lakshmi Subramanian

    2015-08-01

    Full Text Available The large diversity and volume of extracellular RNA (exRNA data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b retrieval of a data slice from the exRNA Atlas for integrative analysis and (c interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

  3. Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies.

    Science.gov (United States)

    Subramanian, Sai Lakshmi; Kitchen, Robert R; Alexander, Roger; Carter, Bob S; Cheung, Kei-Hoi; Laurent, Louise C; Pico, Alexander; Roberts, Lewis R; Roth, Matthew E; Rozowsky, Joel S; Su, Andrew I; Gerstein, Mark B; Milosavljevic, Aleksandar

    2015-01-01

    The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

  4. DeMO: An Ontology for Discrete-event Modeling and Simulation

    Science.gov (United States)

    Silver, Gregory A; Miller, John A; Hybinette, Maria; Baramidze, Gregory; York, William S

    2011-01-01

    Several fields have created ontologies for their subdomains. For example, the biological sciences have developed extensive ontologies such as the Gene Ontology, which is considered a great success. Ontologies could provide similar advantages to the Modeling and Simulation community. They provide a way to establish common vocabularies and capture knowledge about a particular domain with community-wide agreement. Ontologies can support significantly improved (semantic) search and browsing, integration of heterogeneous information sources, and improved knowledge discovery capabilities. This paper discusses the design and development of an ontology for Modeling and Simulation called the Discrete-event Modeling Ontology (DeMO), and it presents prototype applications that demonstrate various uses and benefits that such an ontology may provide to the Modeling and Simulation community. PMID:22919114

  5. Voice-enabled Knowledge Engine using Flood Ontology and Natural Language Processing

    Science.gov (United States)

    Sermet, M. Y.; Demir, I.; Krajewski, W. F.

    2015-12-01

    The Iowa Flood Information System (IFIS) is a web-based platform developed by the Iowa Flood Center (IFC) to provide access to flood inundation maps, real-time flood conditions, flood forecasts, flood-related data, information and interactive visualizations for communities in Iowa. The IFIS is designed for use by general public, often people with no domain knowledge and limited general science background. To improve effective communication with such audience, we have introduced a voice-enabled knowledge engine on flood related issues in IFIS. Instead of navigating within many features and interfaces of the information system and web-based sources, the system provides dynamic computations based on a collection of built-in data, analysis, and methods. The IFIS Knowledge Engine connects to real-time stream gauges, in-house data sources, analysis and visualization tools to answer natural language questions. Our goal is the systematization of data and modeling results on flood related issues in Iowa, and to provide an interface for definitive answers to factual queries. The goal of the knowledge engine is to make all flood related knowledge in Iowa easily accessible to everyone, and support voice-enabled natural language input. We aim to integrate and curate all flood related data, implement analytical and visualization tools, and make it possible to compute answers from questions. The IFIS explicitly implements analytical methods and models, as algorithms, and curates all flood related data and resources so that all these resources are computable. The IFIS Knowledge Engine computes the answer by deriving it from its computational knowledge base. The knowledge engine processes the statement, access data warehouse, run complex database queries on the server-side and return outputs in various formats. This presentation provides an overview of IFIS Knowledge Engine, its unique information interface and functionality as an educational tool, and discusses the future plans

  6. Best behaviour? Ontologies and the formal description of animal behaviour.

    Science.gov (United States)

    Gkoutos, Georgios V; Hoehndorf, Robert; Tsaprouni, Loukia; Schofield, Paul N

    2015-10-01

    The development of ontologies for describing animal behaviour has proved to be one of the most difficult of all scientific knowledge domains. Ranging from neurological processes to human emotions, the range and scope needed for such ontologies is highly challenging, but if data integration and computational tools such as automated reasoning are to be fully applied in this important area the underlying principles of these ontologies need to be better established and development needs detailed coordination. Whilst the state of scientific knowledge is always paramount in ontology and formal description framework design, this is a particular problem with neurobehavioural ontologies where our understanding of the relationship between behaviour and its underlying biophysical basis is currently in its infancy. In this commentary, we discuss some of the fundamental problems in designing and using behaviour ontologies, and present some of the best developed tools in this domain.

  7. Best behaviour? Ontologies and the formal description of animal behaviour

    KAUST Repository

    Gkoutos, Georgios V.

    2015-07-28

    The development of ontologies for describing animal behaviour has proved to be one of the most difficult of all scientific knowledge domains. Ranging from neurological processes to human emotions, the range and scope needed for such ontologies is highly challenging, but if data integration and computational tools such as automated reasoning are to be fully applied in this important area the underlying principles of these ontologies need to be better established and development needs detailed coordination. Whilst the state of scientific knowledge is always paramount in ontology and formal description framework design, this is a particular problem with neurobehavioural ontologies where our understanding of the relationship between behaviour and its underlying biophysical basis is currently in its infancy. In this commentary, we discuss some of the fundamental problems in designing and using behaviour ontologies, and present some of the best developed tools in this domain. © 2015 Springer Science+Business Media New York

  8. A Framework for Ontological Policy Reconstruction : Academic Knowledge Transfer in the Netherlands as a Case Study

    NARCIS (Netherlands)

    Pauly, Marc

    2016-01-01

    This paper provides a framework for analyzing the ontology underlying a given public policy, i.e. the categories and concepts used by the policy. It pro- vides a set of questions concerning the language, logic and deontology of a policy and their development over time. The framework is applied to a

  9. Practical ontologies for information professionals

    CERN Document Server

    AUTHOR|(CDS)2071712

    2016-01-01

    Practical Ontologies for Information Professionals provides an introduction to ontologies and their development, an essential tool for fighting back against information overload. The development of robust and widely used ontologies is an increasingly important tool in the fight against information overload. The publishing and sharing of explicit explanations for a wide variety of conceptualizations, in a machine readable format, has the power to both improve information retrieval and identify new knowledge. This new book provides an accessible introduction to the following: * What is an ontology? Defining the concept and why it is increasingly important to the information professional * Ontologies and the semantic web * Existing ontologies, such as SKOS, OWL, FOAF, schema.org, and the DBpedia Ontology * Adopting and building ontologies, showing how to avoid repetition of work and how to build a simple ontology with Protege * Interrogating semantic web ontologies * The future of ontologies and the role of the ...

  10. Semantic knowledge for histopathological image analysis: from ontologies to processing portals and deep learning

    Science.gov (United States)

    Kergosien, Yannick L.; Racoceanu, Daniel

    2017-11-01

    This article presents our vision about the next generation of challenges in computational/digital pathology. The key role of the domain ontology, developed in a sustainable manner (i.e. using reference checklists and protocols, as the living semantic repositories), opens the way to effective/sustainable traceability and relevance feedback concerning the use of existing machine learning algorithms, proven to be very performant in the latest digital pathology challenges (i.e. convolutional neural networks). Being able to work in an accessible web-service environment, with strictly controlled issues regarding intellectual property (image and data processing/analysis algorithms) and medical data/image confidentiality is essential for the future. Among the web-services involved in the proposed approach, the living yellow pages in the area of computational pathology seems to be very important in order to reach an operational awareness, validation, and feasibility. This represents a very promising way to go to the next generation of tools, able to bring more guidance to the computer scientists and confidence to the pathologists, towards an effective/efficient daily use. Besides, a consistent feedback and insights will be more likely to emerge in the near future - from these sophisticated machine learning tools - back to the pathologists-, strengthening, therefore, the interaction between the different actors of a sustainable biomedical ecosystem (patients, clinicians, biologists, engineers, scientists etc.). Beside going digital/computational - with virtual slide technology demanding new workflows-, Pathology must prepare for another coming revolution: semantic web technologies now enable the knowledge of experts to be stored in databases, shared through the Internet, and accessible by machines. Traceability, disambiguation of reports, quality monitoring, interoperability between health centers are some of the associated benefits that pathologists were seeking. However

  11. COHeRE: Cross-Ontology Hierarchical Relation Examination for Ontology Quality Assurance.

    Science.gov (United States)

    Cui, Licong

    Biomedical ontologies play a vital role in healthcare information management, data integration, and decision support. Ontology quality assurance (OQA) is an indispensable part of the ontology engineering cycle. Most existing OQA methods are based on the knowledge provided within the targeted ontology. This paper proposes a novel cross-ontology analysis method, Cross-Ontology Hierarchical Relation Examination (COHeRE), to detect inconsistencies and possible errors in hierarchical relations across multiple ontologies. COHeRE leverages the Unified Medical Language System (UMLS) knowledge source and the MapReduce cloud computing technique for systematic, large-scale ontology quality assurance work. COHeRE consists of three main steps with the UMLS concepts and relations as the input. First, the relations claimed in source vocabularies are filtered and aggregated for each pair of concepts. Second, inconsistent relations are detected if a concept pair is related by different types of relations in different source vocabularies. Finally, the uncovered inconsistent relations are voted according to their number of occurrences across different source vocabularies. The voting result together with the inconsistent relations serve as the output of COHeRE for possible ontological change. The highest votes provide initial suggestion on how such inconsistencies might be fixed. In UMLS, 138,987 concept pairs were found to have inconsistent relationships across multiple source vocabularies. 40 inconsistent concept pairs involving hierarchical relationships were randomly selected and manually reviewed by a human expert. 95.8% of the inconsistent relations involved in these concept pairs indeed exist in their source vocabularies rather than being introduced by mistake in the UMLS integration process. 73.7% of the concept pairs with suggested relationship were agreed by the human expert. The effectiveness of COHeRE indicates that UMLS provides a promising environment to enhance

  12. Feasibility of automated foundational ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2014-11-01

    Full Text Available the Source Domain Ontology (sOd), with the domain knowledge com- ponent of the source ontology, the Source Foundational Ontology (sOf ) that is the foundational ontology component of the source ontology that is to be interchanged, and any equivalence... or subsumption mappings between enti- ties in sOd and sOf . – The Target Ontology (tO) which has been interchanged, which comprises the Target Domain Ontology (tOd), with the domain knowledge component of the target ontology, and the Target Foundational Ontology...

  13. Mapping between the OBO and OWL ontology languages.

    Science.gov (United States)

    Tirmizi, Syed Hamid; Aitken, Stuart; Moreira, Dilvan A; Mungall, Chris; Sequeda, Juan; Shah, Nigam H; Miranker, Daniel P

    2011-03-07

    Ontologies are commonly used in biomedicine to organize concepts to describe domains such as anatomies, environments, experiment, taxonomies etc. NCBO BioPortal currently hosts about 180 different biomedical ontologies. These ontologies have been mainly expressed in either the Open Biomedical Ontology (OBO) format or the Web Ontology Language (OWL). OBO emerged from the Gene Ontology, and supports most of the biomedical ontology content. In comparison, OWL is a Semantic Web language, and is supported by the World Wide Web consortium together with integral query languages, rule languages and distributed infrastructure for information interchange. These features are highly desirable for the OBO content as well. A convenient method for leveraging these features for OBO ontologies is by transforming OBO ontologies to OWL. We have developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web itself to guide the work. The approach reveals that the constructs of OBO can be grouped together to form a similar layer cake. Thus we were able to decompose the problem into two parts. Most OBO constructs have easy and obvious equivalence to a construct in OWL. A small subset of OBO constructs requires deeper consideration. We have defined transformations for all constructs in an effort to foster a standard common mapping between OBO and OWL. Our mapping produces OWL-DL, a Description Logics based subset of OWL with desirable computational properties for efficiency and correctness. Our Java implementation of the mapping is part of the official Gene Ontology project source. Our transformation system provides a lossless roundtrip mapping for OBO ontologies, i.e. an OBO ontology may be translated to OWL and back without loss of knowledge. In addition, it provides a roadmap for bridging the gap between the two ontology languages in order to enable the use of ontology content in a language independent manner.

  14. Grid workflow validation using ontology-based tacit knowledge: A case study for quantitative remote sensing applications

    Science.gov (United States)

    Liu, Jia; Liu, Longli; Xue, Yong; Dong, Jing; Hu, Yingcui; Hill, Richard; Guang, Jie; Li, Chi

    2017-01-01

    Workflow for remote sensing quantitative retrieval is the ;bridge; between Grid services and Grid-enabled application of remote sensing quantitative retrieval. Workflow averts low-level implementation details of the Grid and hence enables users to focus on higher levels of application. The workflow for remote sensing quantitative retrieval plays an important role in remote sensing Grid and Cloud computing services, which can support the modelling, construction and implementation of large-scale complicated applications of remote sensing science. The validation of workflow is important in order to support the large-scale sophisticated scientific computation processes with enhanced performance and to minimize potential waste of time and resources. To research the semantic correctness of user-defined workflows, in this paper, we propose a workflow validation method based on tacit knowledge research in the remote sensing domain. We first discuss the remote sensing model and metadata. Through detailed analysis, we then discuss the method of extracting the domain tacit knowledge and expressing the knowledge with ontology. Additionally, we construct the domain ontology with Protégé. Through our experimental study, we verify the validity of this method in two ways, namely data source consistency error validation and parameters matching error validation.

  15. Experiences with Aber-OWL, an Ontology Repository with OWL EL Reasoning

    KAUST Repository

    Slater, Luke

    2016-04-19

    Ontologies are widely used in biology and biomedicine for the annotation and integration of data, and hundreds of ontologies have been developed for this purpose. These ontologies also constitute large volumes of formalized domain knowledge, usually expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within them relies on the use of automated reasoning. We have developed Aber-OWL, an ontology repository that provides OWL EL reasoning to answer queries and verify the consistency of ontologies. Aber-OWL also provides a set of web services which provide ontology-based access to scientific literature in Pubmed and Pubmed Central, SPARQL query expansion to retrieve linked data, and integration with Bio2RDF. Here, we report on our experiences with Aber-OWL and outline a roadmap for future development. Aber-OWL is freely available at http://aber-owl.net.

  16. Las ontologías en la ingeniería de software: un acercamiento de dos grandes áreas del conocimiento Ontologies in software engineering: approaching two great knowledge areas

    Directory of Open Access Journals (Sweden)

    Carlos Mario Zapata Jaramillo

    2010-01-01

    Full Text Available Los conceptos ontológicos se suelen acercar más a la ingeniería del conocimiento, por lo que los ingenieros del software no los suelen aplicar para resolver problemas de su área. Es necesario que los ingenieros de software se apropien de las ontologías, pues éstas proporcionan un vocabulario común, que podría contribuir en la solución de problemas recurrentes en ingeniería del software, tales como la dificultad de la comunicación entre analista e interesado para definir los requisitos de un sistema, la baja reutilización de componentes y la escasa generación automática de código, entre otros. En este artículo se presenta un primer enlace entre las ontologías y la ingeniería de software mediante la recopilación y análisis de la literatura relativa a la utilización de las ontologías en las diferentes fases del ciclo de vida de un producto de software.Ontology concepts have been traditionally linked to knowledge engineering and software engineers have not applied them to solve problems of this area. It is necessary that software engineers use these ontologies, since they provide a common language, which can contribute to the solution of some common software engineering problems like difficulties in communication between the analyst and the interested person in order to define a system requirements, the low components re-use, and scarce automatic generation in code generation, among others. In this paper, a first encounter between ontologies and software engineering by means of a state-of-the-art analysis related to the use of ontologies in several phases of software development life cycle is presented.

  17. The Proteasix Ontology.

    Science.gov (United States)

    Arguello Casteleiro, Mercedes; Klein, Julie; Stevens, Robert

    2016-06-04

    The Proteasix Ontology (PxO) is an ontology that supports the Proteasix tool; an open-source peptide-centric tool that can be used to predict automatically and in a large-scale fashion in silico the proteases involved in the generation of proteolytic cleavage fragments (peptides) The PxO re-uses parts of the Protein Ontology, the three Gene Ontology sub-ontologies, the Chemical Entities of Biological Interest Ontology, the Sequence Ontology and bespoke extensions to the PxO in support of a series of roles: 1. To describe the known proteases and their target cleaveage sites. 2. To enable the description of proteolytic cleaveage fragments as the outputs of observed and predicted proteolysis. 3. To use knowledge about the function, species and cellular location of a protease and protein substrate to support the prioritisation of proteases in observed and predicted proteolysis. The PxO is designed to describe the biological underpinnings of the generation of peptides. The peptide-centric PxO seeks to support the Proteasix tool by separating domain knowledge from the operational knowledge used in protease prediction by Proteasix and to support the confirmation of its analyses and results. The Proteasix Ontology may be found at: http://bioportal.bioontology.org/ontologies/PXO . This ontology is free and open for use by everyone.

  18. UPCaD: A Methodology of Integration Between Ontology-Based Context-Awareness Modeling and Relational Domain Data

    Directory of Open Access Journals (Sweden)

    Vinícius Maran

    2018-01-01

    Full Text Available Context-awareness is a key feature for ubiquitous computing scenarios applications. Currently, technologies and methodologies have been proposed for the integration of context-awareness concepts in intelligent information systems to adapt them to the execution of services, user interfaces and data retrieval. Recent research proposed conceptual modeling alternatives to the integration of the domain modeling in RDBMS and context-awareness modeling. The research described using highly expressiveness ontologies. The present work describes the UPCaD (Unified Process for Integration between Context-Awareness and Domain methodology, which is composed of formalisms and processes to guide the data integration considering RDBMS and context modeling. The methodology was evaluated in a virtual learning environment application. The evaluation shows the possibility to use a highly expressive context ontology to filter the relational data query and discusses the main contributions of the methodology compared with recent approaches.

  19. Untangling knowledge creation and knowledge integration in enterprise wikis

    DEFF Research Database (Denmark)

    Beck, Roman; Rai, Arun; Fischbach, Kai

    2015-01-01

    A central challenge organizations face is how to build, store, and maintain knowledge over time. Enterprise wikis are community-based knowledge systems situated in an organizational context. These systems have the potential to play an important role in managing knowledge within organizations......, but the motivating factors that drive individuals to contribute their knowledge to these systems is not very well understood. We theorize that enterprise wiki initiatives require two separate and distinct types of knowledge-sharing behaviors to succeed: knowledge creation (KC) and knowledge integration (KI). We...... examine a Wiki initiative at a major German bank to untangle the motivating factors behind KC and KI. Our results suggest KC and KI are indeed two distinct behaviors, reconcile inconsistent findings from past studies on the role of motivational factors for knowledge sharing to establish shared electronic...

  20. COGMIR: A computer model for knowledge integration

    Energy Technology Data Exchange (ETDEWEB)

    Chen, Z.X.

    1988-01-01

    This dissertation explores some aspects of knowledge integration, namely, accumulation of scientific knowledge and performing analogical reasoning on the acquired knowledge. Knowledge to be integrated is conveyed by paragraph-like pieces referred to as documents. By incorporating some results from cognitive science, the Deutsch-Kraft model of information retrieval is extended to a model for knowledge engineering, which integrates acquired knowledge and performs intelligent retrieval. The resulting computer model is termed COGMIR, which stands for a COGnitive Model for Intelligent Retrieval. A scheme, named query invoked memory reorganization, is used in COGMIR for knowledge integration. Unlike some other schemes which realize knowledge integration through subjective understanding by representing new knowledge in terms of existing knowledge, the proposed scheme suggests at storage time only recording the possible connection of knowledge acquired from different documents. The actual binding of the knowledge acquired from different documents is deferred to query time. There is only one way to store knowledge and numerous ways to utilize the knowledge. Each document can be represented as a whole as well as its meaning. In addition, since facts are constructed from the documents, document retrieval and fact retrieval are treated in a unified way. When the requested knowledge is not available, query invoked memory reorganization can generate suggestion based on available knowledge through analogical reasoning. This is done by revising the algorithms developed for document retrieval and fact retrieval, and by incorporating Gentner's structure mapping theory. Analogical reasoning is treated as a natural extension of intelligent retrieval, so that two previously separate research areas are combined. A case study is provided. All the components are implemented as list structures similar to relational data-bases.

  1. Ontology Update in the Cognitive Model of Ontology Learning

    Directory of Open Access Journals (Sweden)

    Zhang De-Hai

    2016-01-01

    Full Text Available Ontology has been used in many hot-spot fields, but most ontology construction methods are semiautomatic, and the construction process of ontology is still a tedious and painstaking task. In this paper, a kind of cognitive models is presented for ontology learning which can simulate human being’s learning from world. In this model, the cognitive strategies are applied with the constrained axioms. Ontology update is a key step when the new knowledge adds into the existing ontology and conflict with old knowledge in the process of ontology learning. This proposal designs and validates the method of ontology update based on the axiomatic cognitive model, which include the ontology update postulates, axioms and operations of the learning model. It is proved that these operators subject to the established axiom system.

  2. Using a Foundational Ontology for Reengineering a Software Enterprise Ontology

    Science.gov (United States)

    Perini Barcellos, Monalessa; de Almeida Falbo, Ricardo

    The knowledge about software organizations is considerably relevant to software engineers. The use of a common vocabulary for representing the useful knowledge about software organizations involved in software projects is important for several reasons, such as to support knowledge reuse and to allow communication and interoperability between tools. Domain ontologies can be used to define a common vocabulary for sharing and reuse of knowledge about some domain. Foundational ontologies can be used for evaluating and re-designing domain ontologies, giving to these real-world semantics. This paper presents an evaluating of a Software Enterprise Ontology that was reengineered using the Unified Foundation Ontology (UFO) as basis.

  3. A UML profile for the OBO relation ontology

    Science.gov (United States)

    2012-01-01

    Background Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain. Results We have studied the OBO Relation Ontology, the UML metamodel and the UML profiling mechanism. Based on these studies, we have proposed an extension to the UML metamodel in conformance with the OBO Relation Ontology and we have defined a profile that implements the extended metamodel. Finally, we have applied the proposed UML profile in the development of a number of fragments from different ontologies. Particularly, we have considered the Gene Ontology (GO), the PRotein Ontology (PRO) and the Xenopus Anatomy and Development Ontology (XAO). Conclusions The use of an established and well-known graphical language in the development of biomedical ontologies provides a more

  4. An Ontology to Support the Classification of Learning Material in an Organizational Learning Environment: An Evaluation

    Science.gov (United States)

    Valaski, Joselaine; Reinehr, Sheila; Malucelli, Andreia

    2017-01-01

    Purpose: The purpose of this research was to evaluate whether ontology integrated in an organizational learning environment may support the automatic learning material classification in a specific knowledge area. Design/methodology/approach: An ontology for recommending learning material was integrated in the organizational learning environment…

  5. An Ontology-Based Approach for Knowledge Lifecycle Management within Aircraft Lifecycle Phases

    NARCIS (Netherlands)

    Verhagen, W.J.C.

    2013-01-01

    In the aerospace domain, manufacturers and operators constantly seek to improve their products and processes. Increasingly, knowledge-based applications are developed to support or automate knowledge-intensive engineering tasks, saving time and money. However, engineering knowledge changes over

  6. Ontology based integration of heterogeneous structures in the energy industry; Ontologiebasierte Integration heterogener Standards in der Energiewirtschaft

    Energy Technology Data Exchange (ETDEWEB)

    Uslar, Mathias

    2010-07-01

    substations but now also is extended to the scope of distributed energy generation systems. Both large standards families have been developed by the same task committee at IEC by different working groups having different challenges and different viewpoints which led to both structural and semantic incompatibilities to be resolved. A basic harmonization on the level of data models and identifiers is no longer possible as many vendors have adopted the standards for their products. Therefore, the semantic gap has to be closed using other techniques. The approach to use ontologies in order to explicitly specify conceptualisations has spread wide in both science and industry. The goal of this work is to create a semantic description of individual standards in order to have a model and a formal specification of the standards. The next step in the aligning process is to create a mediator ontology which closes the semantic gap between two ontological representations of two or more standards by explicitly and formally stating the equivalent or similar concepts between two standards. This ontology can be used as an artifact in systems like enterprise application integration frameworks in order to provide rules and descriptions how to convert instances and, therefore, leads to an indirect practical harmonization of the standards mentioned before. (orig.)

  7. Integrated knowledge translation: digging deeper, moving forward.

    Science.gov (United States)

    Kothari, Anita; Wathen, C Nadine

    2017-06-01

    Integrated knowledge translation has risen in popularity as a solution to the underuse of research in policy and practice settings. It engages knowledge users-policymakers, practitioners, patients/consumers or their advocates, and members of the wider public-in mutually beneficial research that can involve the joint development of research questions, data collection, analysis and dissemination of findings. Knowledge that is co-produced has a better chance of being implemented. The purpose of this paper is to update developments in the field of integrated knowledge translation through a deeper analysis of the approach in practice-oriented and policy-oriented health research. We present collaborative models that fall outside the scope of integrated knowledge translation, but then explore consensus-based approaches and networks as alternate sites of knowledge co-production. We discuss the need to advance the field through the development, or use, of data collection and interpretation tools that creatively engage knowledge users in the research process. Most importantly, conceptually relevant outcomes need to be identified, including ones that focus on team transformation through the co-production of knowledge. We explore some of these challenges and benefits in detail to help researchers understand what integrated knowledge translation means, and whether the approach's potential added value is worth the investment of time, energy and other resources. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  8. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Directory of Open Access Journals (Sweden)

    Daniel L Cook

    Full Text Available As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB, a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration.

  9. Physical properties of biological entities: an introduction to the ontology of physics for biology.

    Science.gov (United States)

    Cook, Daniel L; Bookstein, Fred L; Gennari, John H

    2011-01-01

    As biomedical investigators strive to integrate data and analyses across spatiotemporal scales and biomedical domains, they have recognized the benefits of formalizing languages and terminologies via computational ontologies. Although ontologies for biological entities-molecules, cells, organs-are well-established, there are no principled ontologies of physical properties-energies, volumes, flow rates-of those entities. In this paper, we introduce the Ontology of Physics for Biology (OPB), a reference ontology of classical physics designed for annotating biophysical content of growing repositories of biomedical datasets and analytical models. The OPB's semantic framework, traceable to James Clerk Maxwell, encompasses modern theories of system dynamics and thermodynamics, and is implemented as a computational ontology that references available upper ontologies. In this paper we focus on the OPB classes that are designed for annotating physical properties encoded in biomedical datasets and computational models, and we discuss how the OPB framework will facilitate biomedical knowledge integration. © 2011 Cook et al.

  10. Huilliche energy. Experiments in integration and ontological disagreements in a wind farm

    Directory of Open Access Journals (Sweden)

    Manuel Tironi

    2017-12-01

    Full Text Available The island of Chiloé, in southern Chile, was the mise-en-scene of an unprecedented project: the development of a wind farm in which the Hulliche community, the ancestral people of the area, would own and run the operation. With the support of the Inter-American Development Bank, the aim of the project was the production of sustainable and renewable energies, but more importantly the integration of indigenous communities into the Chilean society via their participation in a high-value economic enterprise. Drawing on the idea of citizen participation as a form of experimentation, in this article we follow ethnographically the process of incubation, development and failure of this project. The case, we argue, allows a reflection about the risk of cultural aggression embedded in participatory experiments, but also about their capacities to crack open productive spaces for identity, political and ethical speculation. We coin the term “ontological disagreements” to indicate the ambivalences of participatory experiments and to debate about the future of indigenous engagement in energy projects.

  11. Ontology-based Information Retrieval

    DEFF Research Database (Denmark)

    Styltsvig, Henrik Bulskov

    In this thesis, we will present methods for introducing ontologies in information retrieval. The main hypothesis is that the inclusion of conceptual knowledge such as ontologies in the information retrieval process can contribute to the solution of major problems currently found in information...... retrieval. This utilization of ontologies has a number of challenges. Our focus is on the use of similarity measures derived from the knowledge about relations between concepts in ontologies, the recognition of semantic information in texts and the mapping of this knowledge into the ontologies in use......, as well as how to fuse together the ideas of ontological similarity and ontological indexing into a realistic information retrieval scenario. To achieve the recognition of semantic knowledge in a text, shallow natural language processing is used during indexing that reveals knowledge to the level of noun...

  12. Building a Chemical Ontology using Methontology and the Ontology Design Environment

    OpenAIRE

    Fernández López, Mariano; Gómez-Pérez, A.; Pazos Sierra, Alejandro; Pazos Sierra, Juan

    1999-01-01

    METHONTOLOGY PROVIDES GUIDELINES FOR SPECIFYING ONTOLOGIES AT THE KNOWLEDGE LEVEL, AS A SPECIFICATION OF A CONCEPTUALIZATION. ODE ENABLES ONTOLOGY CONSTRUCTION, COVERING THE ENTIRE LIFE CYCLE AND AUTOMATICALLY IMPLEMENTING ONTOLOGIES

  13. Interoperability between phenotype and anatomy ontologies.

    Science.gov (United States)

    Hoehndorf, Robert; Oellrich, Anika; Rebholz-Schuhmann, Dietrich

    2010-12-15

    Phenotypic information is important for the analysis of the molecular mechanisms underlying disease. A formal ontological representation of phenotypic information can help to identify, interpret and infer phenotypic traits based on experimental findings. The methods that are currently used to represent data and information about phenotypes fail to make the semantics of the phenotypic trait explicit and do not interoperate with ontologies of anatomy and other domains. Therefore, valuable resources for the analysis of phenotype studies remain unconnected and inaccessible to automated analysis and reasoning. We provide a framework to formalize phenotypic descriptions and make their semantics explicit. Based on this formalization, we provide the means to integrate phenotypic descriptions with ontologies of other domains, in particular anatomy and physiology. We demonstrate how our framework leads to the capability to represent disease phenotypes, perform powerful queries that were not possible before and infer additional knowledge. http://bioonto.de/pmwiki.php/Main/PheneOntology.

  14. Process and Tool Support for Ontology-Aware Life Support System Development and Integration, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Recent advances in ontology development support a rich description of entities that are modeled within a domain and how these entities relate to each other. However,...

  15. Constructive Ontology Engineering

    Science.gov (United States)

    Sousan, William L.

    2010-01-01

    The proliferation of the Semantic Web depends on ontologies for knowledge sharing, semantic annotation, data fusion, and descriptions of data for machine interpretation. However, ontologies are difficult to create and maintain. In addition, their structure and content may vary depending on the application and domain. Several methods described in…

  16. A Concept Lattice for Semantic Integration of Geo-Ontologies Based on Weight of Inclusion Degree Importance and Information Entropy

    Directory of Open Access Journals (Sweden)

    Jia Xiao

    2016-11-01

    Full Text Available Constructing a merged concept lattice with formal concept analysis (FCA is an important research direction in the field of integrating multi-source geo-ontologies. Extracting essential geographical properties and reducing the concept lattice are two key points of previous research. A formal integration method is proposed to address the challenges in these two areas. We first extract essential properties from multi-source geo-ontologies and use FCA to build a merged formal context. Second, the combined importance weight of each single attribute of the formal context is calculated by introducing the inclusion degree importance from rough set theory and information entropy; then a weighted formal context is built from the merged formal context. Third, a combined weighted concept lattice is established from the weighted formal context with FCA and the importance weight value of every concept is defined as the sum of weight of attributes belonging to the concept’s intent. Finally, semantic granularity of concept is defined by its importance weight; we, then gradually reduce the weighted concept lattice by setting up diminishing threshold of semantic granularity. Additionally, all of those reduced lattices are organized into a regular hierarchy structure based on the threshold of semantic granularity. A workflow is designed to demonstrate this procedure. A case study is conducted to show feasibility and validity of this method and the procedure to integrate multi-source geo-ontologies.

  17. Ion Channel ElectroPhysiology Ontology (ICEPO) - a case study of text mining assisted ontology development.

    Science.gov (United States)

    Elayavilli, Ravikumar Komandur; Liu, Hongfang

    2016-01-01

    Computational modeling of biological cascades is of great interest to quantitative biologists. Biomedical text has been a rich source for quantitative information. Gathering quantitative parameters and values from biomedical text is one significant challenge in the early steps of computational modeling as it involves huge manual effort. While automatically extracting such quantitative information from bio-medical text may offer some relief, lack of ontological representation for a subdomain serves as impedance in normalizing textual extractions to a standard representation. This may render textual extractions less meaningful to the domain experts. In this work, we propose a rule-based approach to automatically extract relations involving quantitative data from biomedical text describing ion channel electrophysiology. We further translated the quantitative assertions extracted through text mining to a formal representation that may help in constructing ontology for ion channel events using a rule based approach. We have developed Ion Channel ElectroPhysiology Ontology (ICEPO) by integrating the information represented in closely related ontologies such as, Cell Physiology Ontology (CPO), and Cardiac Electro Physiology Ontology (CPEO) and the knowledge provided by domain experts. The rule-based system achieved an overall F-measure of 68.93% in extracting the quantitative data assertions system on an independently annotated blind data set. We further made an initial attempt in formalizing the quantitative data assertions extracted from the biomedical text into a formal representation that offers potential to facilitate the integration of text mining into ontological workflow, a novel aspect of this study. This work is a case study where we created a platform that provides formal interaction between ontology development and text mining. We have achieved partial success in extracting quantitative assertions from the biomedical text and formalizing them in ontological

  18. The Systematization of Experiences and Knowledge from the Ontology towards the Praxeology of Educational Research in the University Context

    Directory of Open Access Journals (Sweden)

    Mario Morales Guerrero

    2018-05-01

    Full Text Available Currently in the context of the social sciences, specifically in the practice of university education it is necessary to visualize the methodology of research work that is implemented in research seminars where the systematization of experiences and knowledge is suggested as an alternative to the social research that consists in the systematization of everyday life with a vision of scientific work under the paradigm of cultural and historical phenomenon and the dialogue of the community. This methodology, from a perspective of praxeological - gnoseological, aims to recognize the wealth of knowledge generated in practice, recover those that have been valuable and relevant in various contexts and make them understandable and friendly so that others can use these experiences. Be part of a journey through this work methodology and to share the implementation that is achieved from the ontological plane of reality to enrich the formative trajectory of the students together with the social actors in common scenarios for the protagonists, which implies resizing the use of language leading to a reinterpretation of linguistic codes, generating a reconstruction of feeling and doing through the collective senses. The importance of systematization could be seen as a specific form of research that allows the recovery of knowledge and knowledge that has been effective to intervene in teaching and learning processes.

  19. Overcoming Knowledge Gaps in Postmerger Integration

    DEFF Research Database (Denmark)

    Alaranta, Maria Eliisa; Martela, Eero

    2012-01-01

    Over 50% of mergers and acquisitions (M&As) fail, mainly because of integration problems. In such integrations, much of the experiential (learning-by-doing) knowledge critical for running the business becomes redundant or is lost. However, we know virtually nothing about what type of mechanisms...

  20. An Integrated Knowledge Translation Experience

    Science.gov (United States)

    Bagatto, Marlene P.; Miller, Linda T.; Kothari, Anita; Seewald, Richard; Scollie, Susan D.

    2011-01-01

    Pediatric audiologists lack evidence-based, age-appropriate outcome evaluation tools with well-developed normative data that could be used to evaluate the auditory development and performance of children aged birth to 6 years with permanent childhood hearing impairment. Bagatto and colleagues recommend a battery of outcome tools that may be used with this population. This article provides results of an evaluation of the individual components of the University of Western Ontario Pediatric Audiological Monitoring Protocol (UWO PedAMP) version 1.0 by the audiologists associated with the Network of Pediatric Audiologists of Canada. It also provides information regarding barriers and facilitators to implementing outcome measures in clinical practice. Results indicate that when compared to the Parents’ Evaluation of Aural/Oral Performance of Children (PEACH) Diary, audiologists found the PEACH Rating Scale to be a more clinically feasible evaluation tool to implement in practice from a time, task, and consistency of use perspective. Results also indicate that the LittlEARS® Auditory Questionnaire could be used to evaluate the auditory development and performance of children aged birth to 6 years with permanent childhood hearing impairment (PCHI). The most cited barrier to implementation is time. The result of this social collaboration was the creation of a knowledge product, the UWO PedAMP v1.0, which has the potential to be useful to audiologists and the children and families they serve. PMID:22194315

  1. A semantic representation of the knowledge management enablers domain: The aKMEOnt ontology

    OpenAIRE

    Sabri, M.; Odeh, M. ed; Saad, M. ed

    2017-01-01

    Knowledge management is a significant driver for any enterprise development and evolution as it is engaged with planning, implementing, controlling, monitoring and improving enterprise’s processes and systems. However, organisations are still at a disadvantage when applying knowledge management in a real environment. A resourced-based view of knowledge management stimulates the consideration of knowledge management enablers (KMEs) as factors that should be employed during the development and ...

  2. Towards an Integrative Model of Knowledge Transfer

    DEFF Research Database (Denmark)

    Turcan, Romeo V.; Heslop, Ben

    This paper aims to contribute towards the advancement of an efficient architecture of a single market for knowledge through the development of an integrative model of knowledge transfer. Within this aim, several points of departure can be singled out. One, the article builds on the call of the Eu......This paper aims to contribute towards the advancement of an efficient architecture of a single market for knowledge through the development of an integrative model of knowledge transfer. Within this aim, several points of departure can be singled out. One, the article builds on the call...... business and academia, and implementing the respective legislature are enduring. The research objectives were to explore (i) the process of knowledge transfer in universities, including the nature of tensions, obstacles and incentives, (ii) the relationships between key stakeholders in the KT market...... of the emergent integrative model of knowledge transfer. In an attempt to bring it to a higher level of generalizability, the integrative model of KT is further conceptualized from a ‘sociology of markets’ perspective resulting in an emergent architecture of a single market for knowledge. Future research...

  3. Supplementary Material for: The flora phenotype ontology (FLOPO): tool for integrating morphological traits and phenotypes of vascular plants

    KAUST Repository

    Hoehndorf, Robert; AlShahrani, Mona; Gkoutos, Georgios; Gosline, George; Groom, Quentin; Hamann, Thomas; Kattge, Jens; Oliveira, Sylvia de; Schmidt, Marco; Sierra, Soraya; Smets, Erik; Vos, Rutger; Weiland, Claus

    2016-01-01

    traits of plant species found in Floras. We used the Plant Ontology (PO) and the Phenotype And Trait Ontology (PATO) to extract entity-quality relationships from digitized taxon descriptions in Floras, and used a formal ontological approach based

  4. Ontology-based configuration of problem-solving methods and generation of knowledge-acquisition tools: application of PROTEGE-II to protocol-based decision support.

    Science.gov (United States)

    Tu, S W; Eriksson, H; Gennari, J H; Shahar, Y; Musen, M A

    1995-06-01

    PROTEGE-II is a suite of tools and a methodology for building knowledge-based systems and domain-specific knowledge-acquisition tools. In this paper, we show how PROTEGE-II can be applied to the task of providing protocol-based decision support in the domain of treating HIV-infected patients. To apply PROTEGE-II, (1) we construct a decomposable problem-solving method called episodic skeletal-plan refinement, (2) we build an application ontology that consists of the terms and relations in the domain, and of method-specific distinctions not already captured in the domain terms, and (3) we specify mapping relations that link terms from the application ontology to the domain-independent terms used in the problem-solving method. From the application ontology, we automatically generate a domain-specific knowledge-acquisition tool that is custom-tailored for the application. The knowledge-acquisition tool is used for the creation and maintenance of domain knowledge used by the problem-solving method. The general goal of the PROTEGE-II approach is to produce systems and components that are reusable and easily maintained. This is the rationale for constructing ontologies and problem-solving methods that can be composed from a set of smaller-grained methods and mechanisms. This is also why we tightly couple the knowledge-acquisition tools to the application ontology that specifies the domain terms used in the problem-solving systems. Although our evaluation is still preliminary, for the application task of providing protocol-based decision support, we show that these goals of reusability and easy maintenance can be achieved. We discuss design decisions and the tradeoffs that have to be made in the development of the system.

  5. Automating data acquisition into ontologies from pharmacogenetics relational data sources using declarative object definitions and XML.

    Science.gov (United States)

    Rubin, Daniel L; Hewett, Micheal; Oliver, Diane E; Klein, Teri E; Altman, Russ B

    2002-01-01

    Ontologies are useful for organizing large numbers of concepts having complex relationships, such as the breadth of genetic and clinical knowledge in pharmacogenomics. But because ontologies change and knowledge evolves, it is time consuming to maintain stable mappings to external data sources that are in relational format. We propose a method for interfacing ontology models with data acquisition from external relational data sources. This method uses a declarative interface between the ontology and the data source, and this interface is modeled in the ontology and implemented using XML schema. Data is imported from the relational source into the ontology using XML, and data integrity is checked by validating the XML submission with an XML schema. We have implemented this approach in PharmGKB (http://www.pharmgkb.org/), a pharmacogenetics knowledge base. Our goals were to (1) import genetic sequence data, collected in relational format, into the pharmacogenetics ontology, and (2) automate the process of updating the links between the ontology and data acquisition when the ontology changes. We tested our approach by linking PharmGKB with data acquisition from a relational model of genetic sequence information. The ontology subsequently evolved, and we were able to rapidly update our interface with the external data and continue acquiring the data. Similar approaches may be helpful for integrating other heterogeneous information sources in order make the diversity of pharmacogenetics data amenable to computational analysis.

  6. Summarization by domain ontology navigation

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2013-01-01

    of the subject. In between these two extremes, conceptual summaries encompass selected concepts derived using background knowledge. We address in this paper an approach where conceptual summaries are provided through a conceptualization as given by an ontology. The ontology guiding the summarization can...... be a simple taxonomy or a generative domain ontology. A domain ontology can be provided by a preanalysis of a domain corpus and can be used to condense improved summaries that better reflects the conceptualization of a given domain....

  7. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration.

    Science.gov (United States)

    Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

    2016-07-08

    This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) BACKGROUND: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) METHODS: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) RESULTS: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) CONCLUSION: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database.

  8. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

    Directory of Open Access Journals (Sweden)

    Min-Jung Yoo

    2016-07-01

    Full Text Available This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT. The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI and Open Data Format (O-DF, which ensures data communication. (1 Background: Based on an existing product lifecycle management (PLM methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2 Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA uses the message format as a common protocol of product-service lifecycle data transfer; (3 Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4 Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5 Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF database.

  9. Closed-Loop Lifecycle Management of Service and Product in the Internet of Things: Semantic Framework for Knowledge Integration

    Science.gov (United States)

    Yoo, Min-Jung; Grozel, Clément; Kiritsis, Dimitris

    2016-01-01

    This paper describes our conceptual framework of closed-loop lifecycle information sharing for product-service in the Internet of Things (IoT). The framework is based on the ontology model of product-service and a type of IoT message standard, Open Messaging Interface (O-MI) and Open Data Format (O-DF), which ensures data communication. (1) Background: Based on an existing product lifecycle management (PLM) methodology, we enhanced the ontology model for the purpose of integrating efficiently the product-service ontology model that was newly developed; (2) Methods: The IoT message transfer layer is vertically integrated into a semantic knowledge framework inside which a Semantic Info-Node Agent (SINA) uses the message format as a common protocol of product-service lifecycle data transfer; (3) Results: The product-service ontology model facilitates information retrieval and knowledge extraction during the product lifecycle, while making more information available for the sake of service business creation. The vertical integration of IoT message transfer, encompassing all semantic layers, helps achieve a more flexible and modular approach to knowledge sharing in an IoT environment; (4) Contribution: A semantic data annotation applied to IoT can contribute to enhancing collected data types, which entails a richer knowledge extraction. The ontology-based PLM model enables as well the horizontal integration of heterogeneous PLM data while breaking traditional vertical information silos; (5) Conclusion: The framework was applied to a fictive case study with an electric car service for the purpose of demonstration. For the purpose of demonstrating the feasibility of the approach, the semantic model is implemented in Sesame APIs, which play the role of an Internet-connected Resource Description Framework (RDF) database. PMID:27399717

  10. Ontology for Semantic Data Integration in the Domain of IT Benchmarking.

    Science.gov (United States)

    Pfaff, Matthias; Neubig, Stefan; Krcmar, Helmut

    2018-01-01

    A domain-specific ontology for IT benchmarking has been developed to bridge the gap between a systematic characterization of IT services and their data-based valuation. Since information is generally collected during a benchmark exercise using questionnaires on a broad range of topics, such as employee costs, software licensing costs, and quantities of hardware, it is commonly stored as natural language text; thus, this information is stored in an intrinsically unstructured form. Although these data form the basis for identifying potentials for IT cost reductions, neither a uniform description of any measured parameters nor the relationship between such parameters exists. Hence, this work proposes an ontology for the domain of IT benchmarking, available at https://w3id.org/bmontology. The design of this ontology is based on requirements mainly elicited from a domain analysis, which considers analyzing documents and interviews with representatives from Small- and Medium-Sized Enterprises and Information and Communications Technology companies over the last eight years. The development of the ontology and its main concepts is described in detail (i.e., the conceptualization of benchmarking events, questionnaires, IT services, indicators and their values) together with its alignment with the DOLCE-UltraLite foundational ontology.

  11. Integration of low level and ontology derived features for automatic weapon recognition and identification

    Science.gov (United States)

    Sirakov, Nikolay M.; Suh, Sang; Attardo, Salvatore

    2011-06-01

    This paper presents a further step of a research toward the development of a quick and accurate weapons identification methodology and system. A basic stage of this methodology is the automatic acquisition and updating of weapons ontology as a source of deriving high level weapons information. The present paper outlines the main ideas used to approach the goal. In the next stage, a clustering approach is suggested on the base of hierarchy of concepts. An inherent slot of every node of the proposed ontology is a low level features vector (LLFV), which facilitates the search through the ontology. Part of the LLFV is the information about the object's parts. To partition an object a new approach is presented capable of defining the objects concavities used to mark the end points of weapon parts, considered as convexities. Further an existing matching approach is optimized to determine whether an ontological object matches the objects from an input image. Objects from derived ontological clusters will be considered for the matching process. Image resizing is studied and applied to decrease the runtime of the matching approach and investigate its rotational and scaling invariance. Set of experiments are preformed to validate the theoretical concepts.

  12. EHR-based disease registries to support integrated care in a health neighbourhood: an ontology-based methodology.

    Science.gov (United States)

    Liaw, Siaw-Teng; Taggart, Jane; Yu, Hairong

    2014-01-01

    Disease registries derived from Electronic Health Records (EHRs) are widely used for chronic disease management. We approached registries from the perspective of integrated care in a health neighbourhood, considering data quality issues such as semantic interoperability (consistency), accuracy, completeness and duplication. Our proposition is that a realist ontological approach is required to accurately identify patients in an EHR or data repository, assess data quality and fitness for use by the multidisciplinary integrated care team. We report on this approach with routinely collected data in a practice based research network in Australia.

  13. Accelerating knowledge discovery through community data sharing and integration.

    Science.gov (United States)

    Yip, Y L

    2009-01-01

    To summarize current excellent research in the field of bioinformatics. Synopsis of the articles selected for the IMIA Yearbook 2009. The selection process for this yearbook's section on Bioinformatics results in six excellent articles highlighting several important trends First, it can be noted that Semantic Web technology continues to play an important role in heterogeneous data integration. Novel applications also put more emphasis on its ability to make logical inferences leading to new insights and discoveries. Second, translational research, due to its complex nature, increasingly relies on collective intelligence made available through the adoption of community-defined protocols or software architectures for secure data annotation, sharing and analysis. Advances in systems biology, bio-ontologies and text-ming can also be noted. Current biomedical research gradually evolves towards an environment characterized by intensive collaboration and more sophisticated knowledge processing activities. Enabling technologies, either Semantic Web or other solutions, are expected to play an increasingly important role in generating new knowledge in the foreseeable future.

  14. Nuclear Nonproliferation Ontology Assessment Team Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Strasburg, Jana D.; Hohimer, Ryan E.

    2012-01-01

    Final Report for the NA22 Simulations, Algorithm and Modeling (SAM) Ontology Assessment Team's efforts from FY09-FY11. The Ontology Assessment Team began in May 2009 and concluded in September 2011. During this two-year time frame, the Ontology Assessment team had two objectives: (1) Assessing the utility of knowledge representation and semantic technologies for addressing nuclear nonproliferation challenges; and (2) Developing ontological support tools that would provide a framework for integrating across the Simulation, Algorithm and Modeling (SAM) program. The SAM Program was going through a large assessment and strategic planning effort during this time and as a result, the relative importance of these two objectives changed, altering the focus of the Ontology Assessment Team. In the end, the team conducted an assessment of the state of art, created an annotated bibliography, and developed a series of ontological support tools, demonstrations and presentations. A total of more than 35 individuals from 12 different research institutions participated in the Ontology Assessment Team. These included subject matter experts in several nuclear nonproliferation-related domains as well as experts in semantic technologies. Despite the diverse backgrounds and perspectives, the Ontology Assessment team functioned very well together and aspects could serve as a model for future inter-laboratory collaborations and working groups. While the team encountered several challenges and learned many lessons along the way, the Ontology Assessment effort was ultimately a success that led to several multi-lab research projects and opened up a new area of scientific exploration within the Office of Nuclear Nonproliferation and Verification.

  15. OpenDMAP: An open source, ontology-driven concept analysis engine, with applications to capturing knowledge regarding protein transport, protein interactions and cell-type-specific gene expression

    Directory of Open Access Journals (Sweden)

    Johnson Helen L

    2008-01-01

    Full Text Available Abstract Background Information extraction (IE efforts are widely acknowledged to be important in harnessing the rapid advance of biomedical knowledge, particularly in areas where important factual information is published in a diverse literature. Here we report on the design, implementation and several evaluations of OpenDMAP, an ontology-driven, integrated concept analysis system. It significantly advances the state of the art in information extraction by leveraging knowledge in ontological resources, integrating diverse text processing applications, and using an expanded pattern language that allows the mixing of syntactic and semantic elements and variable ordering. Results OpenDMAP information extraction systems were produced for extracting protein transport assertions (transport, protein-protein interaction assertions (interaction and assertions that a gene is expressed in a cell type (expression. Evaluations were performed on each system, resulting in F-scores ranging from .26 – .72 (precision .39 – .85, recall .16 – .85. Additionally, each of these systems was run over all abstracts in MEDLINE, producing a total of 72,460 transport instances, 265,795 interaction instances and 176,153 expression instances. Conclusion OpenDMAP advances the performance standards for extracting protein-protein interaction predications from the full texts of biomedical research articles. Furthermore, this level of performance appears to generalize to other information extraction tasks, including extracting information about predicates of more than two arguments. The output of the information extraction system is always constructed from elements of an ontology, ensuring that the knowledge representation is grounded with respect to a carefully constructed model of reality. The results of these efforts can be used to increase the efficiency of manual curation efforts and to provide additional features in systems that integrate multiple sources for

  16. Course Ontology-Based User's Knowledge Requirement Acquisition from Behaviors within E-Learning Systems

    Science.gov (United States)

    Zeng, Qingtian; Zhao, Zhongying; Liang, Yongquan

    2009-01-01

    User's knowledge requirement acquisition and analysis are very important for a personalized or user-adaptive learning system. Two approaches to capture user's knowledge requirement about course content within an e-learning system are proposed and implemented in this paper. The first approach is based on the historical data accumulated by an…

  17. The Porifera Ontology (PORO): enhancing sponge systematics with an anatomy ontology.

    Science.gov (United States)

    Thacker, Robert W; Díaz, Maria Cristina; Kerner, Adeline; Vignes-Lebbe, Régine; Segerdell, Erik; Haendel, Melissa A; Mungall, Christopher J

    2014-01-01

    Porifera (sponges) are ancient basal metazoans that lack organs. They provide insight into key evolutionary transitions, such as the emergence of multicellularity and the nervous system. In addition, their ability to synthesize unusual compounds offers potential biotechnical applications. However, much of the knowledge of these organisms has not previously been codified in a machine-readable way using modern web standards. The Porifera Ontology is intended as a standardized coding system for sponge anatomical features currently used in systematics. The ontology is available from http://purl.obolibrary.org/obo/poro.owl, or from the project homepage http://porifera-ontology.googlecode.com/. The version referred to in this manuscript is permanently available from http://purl.obolibrary.org/obo/poro/releases/2014-03-06/. By standardizing character representations, we hope to facilitate more rapid description and identification of sponge taxa, to allow integration with other evolutionary database systems, and to perform character mapping across the major clades of sponges to better understand the evolution of morphological features. Future applications of the ontology will focus on creating (1) ontology-based species descriptions; (2) taxonomic keys that use the nested terms of the ontology to more quickly facilitate species identifications; and (3) methods to map anatomical characters onto molecular phylogenies of sponges. In addition to modern taxa, the ontology is being extended to include features of fossil taxa.

  18. Matching disease and phenotype ontologies in the ontology alignment evaluation initiative.

    Science.gov (United States)

    Harrow, Ian; Jiménez-Ruiz, Ernesto; Splendiani, Andrea; Romacker, Martin; Woollard, Peter; Markel, Scott; Alam-Faruque, Yasmin; Koch, Martin; Malone, James; Waaler, Arild

    2017-12-02

    The disease and phenotype track was designed to evaluate the relative performance of ontology matching systems that generate mappings between source ontologies. Disease and phenotype ontologies are important for applications such as data mining, data integration and knowledge management to support translational science in drug discovery and understanding the genetics of disease. Eleven systems (out of 21 OAEI participating systems) were able to cope with at least one of the tasks in the Disease and Phenotype track. AML, FCA-Map, LogMap(Bio) and PhenoMF systems produced the top results for ontology matching in comparison to consensus alignments. The results against manually curated mappings proved to be more difficult most likely because these mapping sets comprised mostly subsumption relationships rather than equivalence. Manual assessment of unique equivalence mappings showed that AML, LogMap(Bio) and PhenoMF systems have the highest precision results. Four systems gave the highest performance for matching disease and phenotype ontologies. These systems coped well with the detection of equivalence matches, but struggled to detect semantic similarity. This deserves more attention in the future development of ontology matching systems. The findings of this evaluation show that such systems could help to automate equivalence matching in the workflow of curators, who maintain ontology mapping services in numerous domains such as disease and phenotype.

  19. Matching biomedical ontologies based on formal concept analysis.

    Science.gov (United States)

    Zhao, Mengyi; Zhang, Songmao; Li, Weizhuo; Chen, Guowei

    2018-03-19

    The goal of ontology matching is to identify correspondences between entities from different yet overlapping ontologies so as to facilitate semantic integration, reuse and interoperability. As a well developed mathematical model for analyzing individuals and structuring concepts, Formal Concept Analysis (FCA) has been applied to ontology matching (OM) tasks since the beginning of OM research, whereas ontological knowledge exploited in FCA-based methods is limited. This motivates the study in this paper, i.e., to empower FCA with as much as ontological knowledge as possible for identifying mappings across ontologies. We propose a method based on Formal Concept Analysis to identify and validate mappings across ontologies, including one-to-one mappings, complex mappings and correspondences between object properties. Our method, called FCA-Map, incrementally generates a total of five types of formal contexts and extracts mappings from the lattices derived. First, the token-based formal context describes how class names, labels and synonyms share lexical tokens, leading to lexical mappings (anchors) across ontologies. Second, the relation-based formal context describes how classes are in taxonomic, partonomic and disjoint relationships with the anchors, leading to positive and negative structural evidence for validating the lexical matching. Third, the positive relation-based context can be used to discover structural mappings. Afterwards, the property-based formal context describes how object properties are used in axioms to connect anchor classes across ontologies, leading to property mappings. Last, the restriction-based formal context describes co-occurrence of classes across ontologies in anonymous ancestors of anchors, from which extended structural mappings and complex mappings can be identified. Evaluation on the Anatomy, the Large Biomedical Ontologies, and the Disease and Phenotype track of the 2016 Ontology Alignment Evaluation Initiative campaign

  20. Integrating the Ontological, Epistemological, and Sociocultural Aspects: A Holistic View of Teacher Education

    Science.gov (United States)

    Huang, Teng

    2016-01-01

    The three aspects of teacher change--ontological, epistemological, and sociocultural--are traditionally regarded as independent. Usually only the epistemological aspect is highlighted in formal teacher education. In this paper, I argue that a holistic and interdependent view of these aspects is needed. Thus, this paper aims to explore the process…

  1. Biomedical ontologies: toward scientific debate.

    Science.gov (United States)

    Maojo, V; Crespo, J; García-Remesal, M; de la Iglesia, D; Perez-Rey, D; Kulikowski, C

    2011-01-01

    Biomedical ontologies have been very successful in structuring knowledge for many different applications, receiving widespread praise for their utility and potential. Yet, the role of computational ontologies in scientific research, as opposed to knowledge management applications, has not been extensively discussed. We aim to stimulate further discussion on the advantages and challenges presented by biomedical ontologies from a scientific perspective. We review various aspects of biomedical ontologies going beyond their practical successes, and focus on some key scientific questions in two ways. First, we analyze and discuss current approaches to improve biomedical ontologies that are based largely on classical, Aristotelian ontological models of reality. Second, we raise various open questions about biomedical ontologies that require further research, analyzing in more detail those related to visual reasoning and spatial ontologies. We outline significant scientific issues that biomedical ontologies should consider, beyond current efforts of building practical consensus between them. For spatial ontologies, we suggest an approach for building "morphospatial" taxonomies, as an example that could stimulate research on fundamental open issues for biomedical ontologies. Analysis of a large number of problems with biomedical ontologies suggests that the field is very much open to alternative interpretations of current work, and in need of scientific debate and discussion that can lead to new ideas and research directions.

  2. Vertical Integration: Teachers' Knowledge and Teachers' Voice.

    Science.gov (United States)

    Corrie, L.

    1995-01-01

    Traces the theoretical basis for vertical integration in early school years. Contrasts transmission-based pedagogy with a higher level of teacher control, and acquirer-based pedagogy with a higher level of student control. Suggests that early childhood pedagogy will be maintained when teachers are able to articulate their pedagogical knowledge and…

  3. Conceptual querying through ontologies

    DEFF Research Database (Denmark)

    Andreasen, Troels; Bulskov, Henrik

    2009-01-01

    is motivated by an obvious need for users to survey huge volumes of objects in query answers. An ontology formalism and a special notion of-instantiated ontology" are introduced. The latter is a structure reflecting the content in the document collection in that; it is a restriction of a general world......We present here ail approach to conceptual querying where the aim is, given a collection of textual database objects or documents, to target an abstraction of the entire database content in terms of the concepts appearing in documents, rather than the documents in the collection. The approach...... knowledge ontology to the concepts instantiated in the collection. The notion of ontology-based similarity is briefly described, language constructs for direct navigation and retrieval of concepts in the ontology are discussed and approaches to conceptual summarization are presented....

  4. Survey on Ontology Mapping

    Science.gov (United States)

    Zhu, Junwu

    To create a sharable semantic space in which the terms from different domain ontology or knowledge system, Ontology mapping become a hot research point in Semantic Web Community. In this paper, motivated factors of ontology mapping research are given firstly, and then 5 dominating theories and methods, such as information accessing technology, machine learning, linguistics, structure graph and similarity, are illustrated according their technology class. Before we analyses the new requirements and takes a long view, the contributions of these theories and methods are summarized in details. At last, this paper suggest to design a group of semantic connector with the ability of migration learning for OWL-2 extended with constrains and the ontology mapping theory of axiom, so as to provide a new methodology for ontology mapping.

  5. Geobiology of the Critical Zone: the Hierarchies of Process, Form and Life provide an Integrated Ontology

    Science.gov (United States)

    Cotterill, Fenton P. D.

    2016-04-01

    geomorphology characterize Africa's older surfaces, many of which qualify as palimpsests: overwritten and reshaped repeatedly over timescales of 10 000-100 000 000 yr. Inheritance, equifinality, and exhumation are commonly invoked to explain such landscape patterns, but are difficult to measure and thus test; here Africa's vast, deep regoliths epitomize the starkness of these challenges facing researchers across much of the continent. These deficiencies and problems are magnified when we consider the knowledge we seek of African landscape evolution toward resolving the complex history of the African plate since its individuation. The credentials of this knowledge are prescribed by the evidence needed to test competing hypotheses, especially invoking first order determinants of landscape dynamics e.g. membrane tectonics (Oxburgh ER & Turcotte DL 1974. Earth Planet. Sci. Lett. 22:133-140) versus plumes (Foulger G 2013. Plates vs Plumes: A Geological Controversy. Wiley Blackwell). The evidence needed to test such competing hypotheses demands robust reconstructions of the individuated histories of landforms; in the African context, robustness pertains to the representativeness of events reconstructed in form and space (up to continental scales) and back through time from the Neogene into the Late Mesozoic. The ideal map of quantitative evidence must aim to integrate salient details in the trajectories of individuated landforms representing the principal landscapes of all Africa's margins, basins and watersheds. This in turn demands measurements - in mesoscale detail - of relief, drainage and regolith back though time, wherever keystone packages of evidence have survived Gondwana break up and its aftermath. Such a strategy is indeed ambitious, and it may well be dismissed as impractical. Nevertheless, the alternatives fall short. If it is to be representative of the history it purports to explain, we need the mesoscale facts to inform any narrative of a larger landscape (regional

  6. Combining Linked Data and knowledge engineering best practices to design a lightweight role ontology

    NARCIS (Netherlands)

    Passant, A; Isaac, A.H.J.C.A.; Laublet, P

    2011-01-01

    Defining roles of agents (i.e., people, organisations, etc.) is required in various Semantic Web applications, including access control, knowledge management and skill repository. So far, many theoretical discussions have taken place on the nature of roles and how to represent them. In this paper,

  7. Knowledge Representation and Data Mining of Neuronal Morphologies Using Neuroinformatics Tools and Formal Ontologies

    Science.gov (United States)

    Polavaram, Sridevi

    2016-01-01

    Neuroscience can greatly benefit from using novel methods in computer science and informatics, which enable knowledge discovery in unexpected ways. Currently one of the biggest challenges in Neuroscience is to map the functional circuitry of the brain. The applications of this goal range from understanding structural reorganization of neurons to…

  8. Integrating ergonomic knowledge into engineering design processes

    DEFF Research Database (Denmark)

    Hall-Andersen, Lene Bjerg

    Integrating ergonomic knowledge into engineering design processes has been shown to contribute to healthy and effective designs of workplaces. However, it is also well-recognized that, in practice, ergonomists often have difficulties gaining access to and impacting engineering design processes...... employed in the same company, constituted a supporting factor for the possibilities to integrate ergonomic knowledge into the engineering design processes. However, the integration activities remained discrete and only happened in some of the design projects. A major barrier was related to the business...... to the ergonomic ambitions of the clients. The ergonomists’ ability to navigate, act strategically, and compromise on ergonomic inputs is also important in relation to having an impact in the engineering design processes. Familiarity with the engineering design terminology and the setup of design projects seems...

  9. Benchmarking ontologies: bigger or better?

    Directory of Open Access Journals (Sweden)

    Lixia Yao

    2011-01-01

    Full Text Available A scientific ontology is a formal representation of knowledge within a domain, typically including central concepts, their properties, and relations. With the rise of computers and high-throughput data collection, ontologies have become essential to data mining and sharing across communities in the biomedical sciences. Powerful approaches exist for testing the internal consistency of an ontology, but not for assessing the fidelity of its domain representation. We introduce a family of metrics that describe the breadth and depth with which an ontology represents its knowledge domain. We then test these metrics using (1 four of the most common medical ontologies with respect to a corpus of medical documents and (2 seven of the most popular English thesauri with respect to three corpora that sample language from medicine, news, and novels. Here we show that our approach captures the quality of ontological representation and guides efforts to narrow the breach between ontology and collective discourse within a domain. Our results also demonstrate key features of medical ontologies, English thesauri, and discourse from different domains. Medical ontologies have a small intersection, as do English thesauri. Moreover, dialects characteristic of distinct domains vary strikingly as many of the same words are used quite differently in medicine, news, and novels. As ontologies are intended to mirror the state of knowledge, our methods to tighten the fit between ontology and domain will increase their relevance for new areas of biomedical science and improve the accuracy and power of inferences computed across them.

  10. Quantum ontologies

    International Nuclear Information System (INIS)

    Stapp, H.P.

    1988-12-01

    Quantum ontologies are conceptions of the constitution of the universe that are compatible with quantum theory. The ontological orientation is contrasted to the pragmatic orientation of science, and reasons are given for considering quantum ontologies both within science, and in broader contexts. The principal quantum ontologies are described and evaluated. Invited paper at conference: Bell's Theorem, Quantum Theory, and Conceptions of the Universe, George Mason University, October 20-21, 1988. 16 refs

  11. Gene Ontology

    Directory of Open Access Journals (Sweden)

    Gaston K. Mazandu

    2012-01-01

    Full Text Available The wide coverage and biological relevance of the Gene Ontology (GO, confirmed through its successful use in protein function prediction, have led to the growth in its popularity. In order to exploit the extent of biological knowledge that GO offers in describing genes or groups of genes, there is a need for an efficient, scalable similarity measure for GO terms and GO-annotated proteins. While several GO similarity measures exist, none adequately addresses all issues surrounding the design and usage of the ontology. We introduce a new metric for measuring the distance between two GO terms using the intrinsic topology of the GO-DAG, thus enabling the measurement of functional similarities between proteins based on their GO annotations. We assess the performance of this metric using a ROC analysis on human protein-protein interaction datasets and correlation coefficient analysis on the selected set of protein pairs from the CESSM online tool. This metric achieves good performance compared to the existing annotation-based GO measures. We used this new metric to assess functional similarity between orthologues, and show that it is effective at determining whether orthologues are annotated with similar functions and identifying cases where annotation is inconsistent between orthologues.

  12. CONCEPTION OF ONTOLOGY-BASED SECTOR EDUCATIONAL SPACE

    Directory of Open Access Journals (Sweden)

    V. I. Khabarov

    2014-09-01

    Full Text Available PurposeThe aim of the research is to demonstrate the need for the Conception of Ontology-based Sector Educational Space. This Conception could become the basis for the integration of transport sector university information resources into the open virtual network information resource and global educational space. Its content will be presented by standardized ontology-based knowledge packages for educational programs in Russian and English languages.MethodologyComplex-based, ontological, content-based approaches and scientific principles of interdisciplinarity and standardization of knowledge are suggested as the methodological basis of the research. ResultsThe Conception of Ontology-based Sector Educational Space (railway transport, the method of the development of knowledge packages as ontologies in Russian and English languages, the Russian-English Transport Glossary as a separate ontology are among the expected results of the project implementation.Practical implicationsThe Conception could become the basis for the open project to establish the common resource center for transport universities (railway transport. The Conception of ontology-based sector educational space (railway transport could be adapted to the activity of universities of other economic sectors.

  13. Integrating ontologies and argumentation for decision-making in breast cancer

    OpenAIRE

    Williams, M. H.

    2009-01-01

    This thesis describes some of the problems in providing care for patients with breast cancer. These are then used to motivate the development of an extension to an existing theory of argumentation, which I call the Ontology-based Argumentation Formalism (OAF). The work is assessed in both theoretical and empirical ways. From a clinical perspective, there is a problem with the provision of care. Numerous reports have noted the failure to provide uniformly high quality care, as w...

  14. Perspectives on ontology learning

    CERN Document Server

    Lehmann, J

    2014-01-01

    Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c

  15. Expert2OWL: A Methodology for Pattern-Based Ontology Development.

    Science.gov (United States)

    Tahar, Kais; Xu, Jie; Herre, Heinrich

    2017-01-01

    The formalization of expert knowledge enables a broad spectrum of applications employing ontologies as underlying technology. These include eLearning, Semantic Web and expert systems. However, the manual construction of such ontologies is time-consuming and thus expensive. Moreover, experts are often unfamiliar with the syntax and semantics of formal ontology languages such as OWL and usually have no experience in developing formal ontologies. To overcome these barriers, we developed a new method and tool, called Expert2OWL that provides efficient features to support the construction of OWL ontologies using GFO (General Formal Ontology) as a top-level ontology. This method allows a close and effective collaboration between ontologists and domain experts. Essentially, this tool integrates Excel spreadsheets as part of a pattern-based ontology development and refinement process. Expert2OWL enables us to expedite the development process and modularize the resulting ontologies. We applied this method in the field of Chinese Herbal Medicine (CHM) and used Expert2OWL to automatically generate an accurate Chinese Herbology ontology (CHO). The expressivity of CHO was tested and evaluated using ontology query languages SPARQL and DL. CHO shows promising results and can generate answers to important scientific questions such as which Chinese herbal formulas contain which substances, which substances treat which diseases, and which ones are the most frequently used in CHM.

  16. Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice

    Directory of Open Access Journals (Sweden)

    Rosemary eShrestha

    2012-08-01

    Full Text Available The Crop Ontology (CO of the Generation Challenge Program (GCP (http://cropontology.org/ is developed for the Integrated Breeding Platform (https://www.integratedbreeding.net/ by several centers of The Consultative Group on International Agricultural Research (CGIAR: Bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The Crop Ontology provides validated trait names used by the crop communities of practice for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB fieldbooks are synchronized with the Crop Ontology terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum and wheat. Online curation and annotation tools facilitate (http://cropontology.org direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology and Trait Ontology. Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS. Cross-referencing and annotation will be further applied in the Integrated Breeding Platform.

  17. Integration of an OWL-DL knowledge base with an EHR prototype and providing customized information.

    Science.gov (United States)

    Jing, Xia; Kay, Stephen; Marley, Tom; Hardiker, Nicholas R

    2014-09-01

    When clinicians use electronic health record (EHR) systems, their ability to obtain general knowledge is often an important contribution to their ability to make more informed decisions. In this paper we describe a method by which an external, formal representation of clinical and molecular genetic knowledge can be integrated into an EHR such that customized knowledge can be delivered to clinicians in a context-appropriate manner.Web Ontology Language-Description Logic (OWL-DL) is a formal knowledge representation language that is widely used for creating, organizing and managing biomedical knowledge through the use of explicit definitions, consistent structure and a computer-processable format, particularly in biomedical fields. In this paper we describe: 1) integration of an OWL-DL knowledge base with a standards-based EHR prototype, 2) presentation of customized information from the knowledge base via the EHR interface, and 3) lessons learned via the process. The integration was achieved through a combination of manual and automatic methods. Our method has advantages for scaling up to and maintaining knowledge bases of any size, with the goal of assisting clinicians and other EHR users in making better informed health care decisions.

  18. The First Organ-Based Ontology for Arthropods (Ontology of Arthropod Circulatory Systems - OArCS) and its Integration into a Novel Formalization Scheme for Morphological Descriptions.

    Science.gov (United States)

    Wirkner, Christian S; Göpel, Torben; Runge, Jens; Keiler, Jonas; Klussmann-Fricke, Bastian-Jesper; Huckstorf, Katarina; Scholz, Stephan; Mikó, István; J Yoder, Matthew; Richter, Stefan

    2017-09-01

    Morphology, the oldest discipline in the biosciences, is currently experiencing a renaissance in the field of comparative phenomics. However, morphological/phenotypic research still suffers on various levels from a lack of standards. This shortcoming, first highlighted as the "linguistic problem of morphology", concerns the usage of terminology and also the need for formalization of morphological descriptions themselves, something of paramount importance not only to the field of morphology but also when it comes to the use of phenotypic data in systematics and evolutionary biology. We therefore argue, that for morphological descriptions, the basis of all systematic and evolutionary interpretations, ontologies need to be utilized which are based exclusively on structural qualities/properties and which in no case include statements about homology and/or function. Statements about homology and function constitute interpretations on a different or higher level. Based on these "anatomy ontologies", further ontological dimensions (e.g., referring to functional properties or homology) may be exerted for a broad use in evolutionary phenomics. To this end we present the first organ-based ontology for the most species-rich animal group, the Arthropoda. Our Ontology of Arthropod Circulatory Systems (OArCS) contains a comprehensive collection of 383 terms (i.e., labels) tied to 296 concepts (i.e., definitions) collected from the literature on phenotypic aspects of circulatory organ features in arthropods. All of the concepts used in OArCS are based exclusively on structural features, and in the context of the ontology are independent of homology and functional assumptions. We cannot rule out that in some cases, terms are used which in traditional usage and previous accounts might have implied homology and/or function (e.g. heart, sternal artery). Concepts are composed of descriptive elements that are used to classify observed instances into the organizational framework of the

  19. Electronic health records and disease registries to support integrated care in a health neighbourhood: an ontology-based methodology.

    Science.gov (United States)

    Liaw, Siaw-Teng; Taggart, Jane; Yu, Hairong; Rahimi, Alireza

    2014-01-01

    Disease registries derived from Electronic Health Records (EHRs) are widely used for chronic disease management (CDM). However, unlike national registries which are specialised data collections, they are usually specific to an EHR or organization such as a medical home. We approached registries from the perspective of integrated care in a health neighbourhood, considering data quality issues such as semantic interoperability (consistency), accuracy, completeness and duplication. Our proposition is that a realist ontological approach is required to systematically and accurately identify patients in an EHR or data repository of EHRs, assess intrinsic data quality and fitness for use by members of the multidisciplinary integrated care team. We report on this approach as applied to routinely collected data in an electronic practice based research network in Australia.

  20. Challenges of knowledge integration in small and medium enterprises

    Directory of Open Access Journals (Sweden)

    Kavoos Mohannak

    2014-03-01

    Full Text Available This study attempts to develop a better understanding of the challenges of knowledge integration (KI within the innovation process in Small and Medium Enterprises (SMEs. Using several case studies, this study investigates how knowledge integration may be managed within the context of innovation in SMEs. The research places particular focus on identifying the challenges of knowledge integration in SMEs in relation to three aspects of knowledge integration activities, namely knowledge identification, knowledge acquisition, and knowledge sharing. Four distinct tasks emerged in the knowledge integration process, namely team building capability, capturing tacit knowledge, role of knowledge management (KM systems, and technological systemic integration. The paper suggests that managing knowledge integration in SMEs can be best managed by focusing on these four tasks, which in turn will lead to innovation.

  1. Integrating Vygotsky's theory of relational ontology into early childhood science education

    Science.gov (United States)

    Kirch, Susan A.

    2014-03-01

    In Science Education during Early Childhood: A Cultural- Historical Perspective, Wolff-Michael Roth, Maria Inês Mafra Goulart and Katerina Plakitsi explore the practical application of Vygotsky's relational ontological theory of human development to early childhood science teaching and teacher development. In this review, I interrogate how Roth et al. conceptualize "emergent curriculum" within the Eurocentric cultural-historical traditions of early childhood education that evolved primarily from the works of Vygotsky and Piaget and compare it to the conceptualizations from other prominent early childhood researchers and curriculum developers. I examine the implications of the authors' interpretation of emergence for early childhood science education and teacher preparation.

  2. The Electronic Notebook Ontology

    OpenAIRE

    Chalk, Stuart

    2016-01-01

    Science is rapidly being brought into the electronic realm and electronic laboratory notebooks (ELN) are a big part of this activity. The representation of the scientific process in the context of an ELN is an important component to making the data recorded in ELNs semantically integrated. This presentation will outline initial developments of an Electronic Notebook Ontology (ENO) that will help tie together the ExptML ontology, HCLS Community Profile data descriptions, and the VIVO-ISF ontol...

  3. Presentation planning using an integrated knowledge base

    Science.gov (United States)

    Arens, Yigal; Miller, Lawrence; Sondheimer, Norman

    1988-01-01

    A description is given of user interface research aimed at bringing together multiple input and output modes in a way that handles mixed mode input (commands, menus, forms, natural language), interacts with a diverse collection of underlying software utilities in a uniform way, and presents the results through a combination of output modes including natural language text, maps, charts and graphs. The system, Integrated Interfaces, derives much of its ability to interact uniformly with the user and the underlying services and to build its presentations, from the information present in a central knowledge base. This knowledge base integrates models of the application domain (Navy ships in the Pacific region, in the current demonstration version); the structure of visual displays and their graphical features; the underlying services (data bases and expert systems); and interface functions. The emphasis is on a presentation planner that uses the knowledge base to produce multi-modal output. There has been a flurry of recent work in user interface management systems. (Several recent examples are listed in the references). Existing work is characterized by an attempt to relieve the software designer of the burden of handcrafting an interface for each application. The work has generally focused on intelligently handling input. This paper deals with the other end of the pipeline - presentations.

  4. An Integrated Model of Knowledge Acquisition and Innovation: Examining the Mediation Effects of Knowledge Integration and Knowledge Application

    Science.gov (United States)

    Dahiyat, Samer E.

    2015-01-01

    The aim of this research is to empirically investigate the relationships among the three vital knowledge management processes of acquisition, integration and application, and their effects on organisational innovation in the pharmaceutical manufacturing industry in Jordan; a knowledge-intensive business service (KIBS) sector. Structural equation…

  5. TrhOnt: building an ontology to assist rehabilitation processes.

    Science.gov (United States)

    Berges, Idoia; Antón, David; Bermúdez, Jesús; Goñi, Alfredo; Illarramendi, Arantza

    2016-10-04

    One of the current research efforts in the area of biomedicine is the representation of knowledge in a structured way so that reasoning can be performed on it. More precisely, in the field of physiotherapy, information such as the physiotherapy record of a patient or treatment protocols for specific disorders must be adequately modeled, because they play a relevant role in the management of the evolutionary recovery process of a patient. In this scenario, we introduce TRHONT, an application ontology that can assist physiotherapists in the management of the patients' evolution via reasoning supported by semantic technology. The ontology was developed following the NeOn Methodology. It integrates knowledge from ontological (e.g. FMA ontology) and non-ontological resources (e.g. a database of movements, exercises and treatment protocols) as well as additional physiotherapy-related knowledge. We demonstrate how the ontology fulfills the purpose of providing a reference model for the representation of the physiotherapy-related information that is needed for the whole physiotherapy treatment of patients, since they step for the first time into the physiotherapist's office, until they are discharged. More specifically, we present the results for each of the intended uses of the ontology listed in the document that specifies its requirements, and show how TRHONT can answer the competency questions defined within that document. Moreover, we detail the main steps of the process followed to build the TRHONT ontology in order to facilitate its reproducibility in a similar context. Finally, we show an evaluation of the ontology from different perspectives. TRHONT has achieved the purpose of allowing for a reasoning process that changes over time according to the patient's state and performance.

  6. Integrating knowledge seeking into knowledge management models and frameworks

    Directory of Open Access Journals (Sweden)

    Francois Lottering

    2012-09-01

    Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking. Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies. Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing. Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies.

  7. Integrating knowledge seeking into knowledge management models and frameworks

    Directory of Open Access Journals (Sweden)

    Francois Lottering

    2012-02-01

    Full Text Available Background: A striking feature of the knowledge management (KM literature is that the standard list of KM processes either subsumes or overlooks the process of knowledge seeking. Knowledge seeking is manifestly under-theorised, making the need to address this gap in KM theory and practice clear and urgent.Objectives: This article investigates the theoretical status of the knowledge-seeking process in extant KM models and frameworks. It also statistically describes knowledge seeking and knowledge sharing practices in a sample of South African companies. Using this data, it proposes a KM model based on knowledge seeking.Method: Knowledge seeking is traced in a number of KM models and frameworks with a specific focus on Han Lai and Margaret Graham’s adapted KM cycle model, which separates knowledge seeking from knowledge sharing. This empirical investigation used a questionnaire to examine knowledge seeking and knowledge sharing practices in a sample of South African companies.Results: This article critiqued and elaborated on the adapted KM cycle model of Lai and Graham. It identified some of the key features of knowledge seeking practices in the workplace. It showed that knowledge seeking and sharing are human-centric actions and that seeking knowledge uses trust and loyalty as its basis. It also showed that one cannot separate knowledge seeking from knowledge sharing.Conclusion: The knowledge seeking-based KM model elaborates on Lai and Graham’s model. It provides insight into how and where people seek and share knowledge in the workplace. The article concludes that it is necessary to cement the place of knowledge seeking in KM models as well as frameworks and suggests that organisations should apply its findings to improving their knowledge management strategies. 

  8. Integrating indigenous games and knowledge into Physical Education

    African Journals Online (AJOL)

    Integrating indigenous games and knowledge into Physical Education: Implications for ... The aim of this study was to analyse indigenous Zulu games towards integrating indigenous game skill and knowledge ... AJOL African Journals Online.

  9. Mining rare associations between biological ontologies.

    Science.gov (United States)

    Benites, Fernando; Simon, Svenja; Sapozhnikova, Elena

    2014-01-01

    The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  10. Mining rare associations between biological ontologies.

    Directory of Open Access Journals (Sweden)

    Fernando Benites

    Full Text Available The constantly increasing volume and complexity of available biological data requires new methods for their management and analysis. An important challenge is the integration of information from different sources in order to discover possible hidden relations between already known data. In this paper we introduce a data mining approach which relates biological ontologies by mining cross and intra-ontology pairwise generalized association rules. Its advantage is sensitivity to rare associations, for these are important for biologists. We propose a new class of interestingness measures designed for hierarchically organized rules. These measures allow one to select the most important rules and to take into account rare cases. They favor rules with an actual interestingness value that exceeds the expected value. The latter is calculated taking into account the parent rule. We demonstrate this approach by applying it to the analysis of data from Gene Ontology and GPCR databases. Our objective is to discover interesting relations between two different ontologies or parts of a single ontology. The association rules that are thus discovered can provide the user with new knowledge about underlying biological processes or help improve annotation consistency. The obtained results show that produced rules represent meaningful and quite reliable associations.

  11. Addressing issues in foundational ontology mediation

    CSIR Research Space (South Africa)

    Khan, ZC

    2013-09-01

    Full Text Available An approach in achieving semantic interoperability among heterogeneous systems is to offer infrastructure to assist with linking and integration using a foundational ontology. Due to the creation of multiple foundational ontologies, this also means...

  12. ONTOLOGY IN PHARMACY

    Directory of Open Access Journals (Sweden)

    L. Yu. Babintseva

    2015-05-01

    Full Text Available It’s considered ontological models for formalization of knowledge in pharmacy. There is emphasized the view that the possibility of rapid exchange of information in the pharmaceutical industry, it is necessary to create a single information space. This means not only the establishment of uniform standards for the presentation of information on pharmaceutical groups pharmacotherapeutic classifications, but also the creation of a unified and standardized system for the transfer and renewal of knowledge. It is the organization of information in the ontology helps quickly in the future to build expert systems and applications to work with data.

  13. Constructing a Geology Ontology Using a Relational Database

    Science.gov (United States)

    Hou, W.; Yang, L.; Yin, S.; Ye, J.; Clarke, K.

    2013-12-01

    In geology community, the creation of a common geology ontology has become a useful means to solve problems of data integration, knowledge transformation and the interoperation of multi-source, heterogeneous and multiple scale geological data. Currently, human-computer interaction methods and relational database-based methods are the primary ontology construction methods. Some human-computer interaction methods such as the Geo-rule based method, the ontology life cycle method and the module design method have been proposed for applied geological ontologies. Essentially, the relational database-based method is a reverse engineering of abstracted semantic information from an existing database. The key is to construct rules for the transformation of database entities into the ontology. Relative to the human-computer interaction method, relational database-based methods can use existing resources and the stated semantic relationships among geological entities. However, two problems challenge the development and application. One is the transformation of multiple inheritances and nested relationships and their representation in an ontology. The other is that most of these methods do not measure the semantic retention of the transformation process. In this study, we focused on constructing a rule set to convert the semantics in a geological database into a geological ontology. According to the relational schema of a geological database, a conversion approach is presented to convert a geological spatial database to an OWL-based geological ontology, which is based on identifying semantics such as entities, relationships, inheritance relationships, nested relationships and cluster relationships. The semantic integrity of the transformation was verified using an inverse mapping process. In a geological ontology, an inheritance and union operations between superclass and subclass were used to present the nested relationship in a geochronology and the multiple inheritances

  14. Interdisciplinarity to Integrate Knowledge in Engineering

    Directory of Open Access Journals (Sweden)

    Stella Abreu

    2017-06-01

    Full Text Available This paper is an extension of work originally presented at the 2nd International Conference of the Portuguese Society for Engineering Education and aims to describe an interdisciplinarity teaching experiment involving three subjects of the scientific area of Mathematics and a fourth one in the area of Management. Using only one project, the students developed skills, in an integrated way, in the fields of the subjects involved. The structure of the project is described in detail. It is shown how the knowledge obtained in the different subjects is needed and how it connects together to answer the proposed challenges. We report the progress of the students’ work, the main difficulties and the skills developed during this process. We conclude with a reflection on the main problems and gains that may arise in similar projects.

  15. Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

    Science.gov (United States)

    Lamy, Jean-Baptiste

    2017-07-01

    Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Owlready has been successfully

  16. THE PRINCIPLES AND METHODS OF INFORMATION AND EDUCATIONAL SPACE SEMANTIC STRUCTURING BASED ON ONTOLOGIC APPROACH REALIZATION

    Directory of Open Access Journals (Sweden)

    Yurij F. Telnov

    2014-01-01

    Full Text Available This article reveals principles of semantic structuring of information and educational space of objects of knowledge and scientific and educational services with use of methods of ontologic engineering. Novelty of offered approach is interface of ontology of a content and ontology of scientific and educational services that allows to carry out effective composition of services and objects of knowledge according to models of professional competences and requirements being trained. As a result of application of methods of information and educational space semantic structuring integration of use of the diverse distributed scientific and educational content by educational institutions for carrying out scientific researches, methodical development and training is provided.

  17. A Lexical-Ontological Resource for Consumer Healthcare

    Science.gov (United States)

    Cardillo, Elena; Serafini, Luciano; Tamilin, Andrei

    In Consumer Healthcare Informatics it is still difficult for laypeople to find, understand and act on health information, due to the persistent communication gap between specialized medical terminology and that used by healthcare consumers. Furthermore, existing clinically-oriented terminologies cannot provide sufficient support when integrated into consumer-oriented applications, so there is a need to create consumer-friendly terminologies reflecting the different ways healthcare consumers express and think about health topics. Following this direction, this work suggests a way to support the design of an ontology-based system that mitigates this gap, using knowledge engineering and semantic web technologies. The system is based on the development of a consumer-oriented medical terminology that will be integrated with other medical domain ontologies and terminologies into a medical ontology repository. This will support consumer-oriented healthcare systems, such as Personal Health Records, by providing many knowledge services to help users in accessing and managing their healthcare data.

  18. A Lexical-Ontological Resource for Consumer Heathcare

    Science.gov (United States)

    Cardillo, Elena

    In Consumer Healthcare Informatics it is still difficult for laypersons to understand and act on health information, due to the persistent communication gap between specialized medical terminology and that used by healthcare consumers. Furthermore, existing clinically-oriented terminologies cannot provide sufficient support when integrated into consumer-oriented applications, so there is a need to create consumer-friendly terminologies reflecting the different ways healthcare consumers express and think about health topics. Following this direction, this work suggests a way to support the design of an ontology-based system that mitigates this gap, using knowledge engineering and Semantic Web technologies. The system is based on the development of a consumer-oriented medical terminology which will be integrated with other existing domain ontologies/terminologies into a medical ontology repository. This will support consumer-oriented healthcare systems by providing many knowledge services to help users in accessing and managing their healthcare data.

  19. A knowledge integration approach to flood vulnerability

    Science.gov (United States)

    Mazzorana, Bruno; Fuchs, Sven

    2014-05-01

    Understanding, qualifying and quantifying vulnerability is an essential need for implementing effective and efficient flood risk mitigation strategies; in particular if possible synergies between different mitigation alternatives, such as active and passive measures, should be achieved. In order to combine different risk management options it is necessary to take an interdisciplinary approach to vulnerability reduction, and as a result the affected society may be willing to accept a certain degree of self-responsibility. However, due to differing mono-disciplinary approaches and regional foci undertaken until now, different aspects of vulnerability to natural hazards in general and to floods in particular remain uncovered and as a result the developed management options remain sub-optimal. Taking an even more fundamental viewpoint, the empirical vulnerability functions used in risk assessment specifically fail to capture physical principles of the damage-generating mechanisms to the build environment. The aim of this paper is to partially close this gap by discussing a balanced knowledge integration approach which can be used to resolve the multidisciplinary disorder in flood vulnerability research. Modelling techniques such as mathematical-physical modelling of the flood hazard impact to and response from the building envelope affected, and formative scenario analyses of possible consequences in terms of damage and loss are used in synergy to provide an enhanced understanding of vulnerability and to render the derived knowledge into interdisciplinary mitigation strategies. The outlined formal procedure allows for a convincing knowledge alignment of quantified, but partial, information about vulnerability as a result of the application of physical and engineering notions and valuable, but often underspecified, qualitative argumentation strings emerging from the adopted socio-economic viewpoint.

  20. Ontological engineering versus metaphysics

    Science.gov (United States)

    Tataj, Emanuel; Tomanek, Roman; Mulawka, Jan

    2011-10-01

    It has been recognized that ontologies are a semantic version of world wide web and can be found in knowledge-based systems. A recent time survey of this field also suggest that practical artificial intelligence systems may be motivated by this research. Especially strong artificial intelligence as well as concept of homo computer can also benefit from their use. The main objective of this contribution is to present and review already created ontologies and identify the main advantages which derive such approach for knowledge management systems. We would like to present what ontological engineering borrows from metaphysics and what a feedback it can provide to natural language processing, simulations and modelling. The potential topics of further development from philosophical point of view is also underlined.

  1. An Ontology-Based Approach to Enable Knowledge Representation and Reasoning in Worker–Cobot Agile Manufacturing

    Directory of Open Access Journals (Sweden)

    Ahmed R. Sadik

    2017-11-01

    accomplish the cooperative manufacturing concept, a proper approach is required to describe the shared environment between the worker and the cobot. The cooperative manufacturing shared environment includes the cobot, the co-worker, and other production components such as the product itself. Furthermore, the whole cooperative manufacturing system components need to communicate and share their knowledge, to reason and process the shared information, which eventually gives the control solution the capability of obtaining collective manufacturing decisions. Putting into consideration that the control solution should also provide a natural language which is human readable and in the same time can be understood by the machine (i.e., the cobot. Accordingly, a distributed control solution which combines an ontology-based Multi-Agent System (MAS and a Business Rule Management System (BRMS is proposed, in order to solve the mentioned challenges in the cooperative manufacturing, which are: manufacturing knowledge representation, sharing, and reasoning.

  2. An ontological approach to domain engineering

    NARCIS (Netherlands)

    Falbo, R.A.; Guizzardi, G.; Duarte, K.

    2002-01-01

    Domain engineering aims to support systematic reuse, focusing on modeling common knowledge in a problem domain. Ontologies have also been pointed as holding great promise for software reuse. In this paper, we present ODE (Ontology-based Domain Engineering), an ontological approach for domain

  3. The Ontology for Biomedical Investigations.

    Science.gov (United States)

    Bandrowski, Anita; Brinkman, Ryan; Brochhausen, Mathias; Brush, Matthew H; Bug, Bill; Chibucos, Marcus C; Clancy, Kevin; Courtot, Mélanie; Derom, Dirk; Dumontier, Michel; Fan, Liju; Fostel, Jennifer; Fragoso, Gilberto; Gibson, Frank; Gonzalez-Beltran, Alejandra; Haendel, Melissa A; He, Yongqun; Heiskanen, Mervi; Hernandez-Boussard, Tina; Jensen, Mark; Lin, Yu; Lister, Allyson L; Lord, Phillip; Malone, James; Manduchi, Elisabetta; McGee, Monnie; Morrison, Norman; Overton, James A; Parkinson, Helen; Peters, Bjoern; Rocca-Serra, Philippe; Ruttenberg, Alan; Sansone, Susanna-Assunta; Scheuermann, Richard H; Schober, Daniel; Smith, Barry; Soldatova, Larisa N; Stoeckert, Christian J; Taylor, Chris F; Torniai, Carlo; Turner, Jessica A; Vita, Randi; Whetzel, Patricia L; Zheng, Jie

    2016-01-01

    The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed

  4. Bridging the phenotypic and genetic data useful for integrated breeding through a data annotation using the Crop Ontology developed by the crop communities of practice

    Science.gov (United States)

    Shrestha, Rosemary; Matteis, Luca; Skofic, Milko; Portugal, Arllet; McLaren, Graham; Hyman, Glenn; Arnaud, Elizabeth

    2012-01-01

    The Crop Ontology (CO) of the Generation Challenge Program (GCP) (http://cropontology.org/) is developed for the Integrated Breeding Platform (IBP) (http://www.integratedbreeding.net/) by several centers of The Consultative Group on International Agricultural Research (CGIAR): bioversity, CIMMYT, CIP, ICRISAT, IITA, and IRRI. Integrated breeding necessitates that breeders access genotypic and phenotypic data related to a given trait. The CO provides validated trait names used by the crop communities of practice (CoP) for harmonizing the annotation of phenotypic and genotypic data and thus supporting data accessibility and discovery through web queries. The trait information is completed by the description of the measurement methods and scales, and images. The trait dictionaries used to produce the Integrated Breeding (IB) fieldbooks are synchronized with the CO terms for an automatic annotation of the phenotypic data measured in the field. The IB fieldbook provides breeders with direct access to the CO to get additional descriptive information on the traits. Ontologies and trait dictionaries are online for cassava, chickpea, common bean, groundnut, maize, Musa, potato, rice, sorghum, and wheat. Online curation and annotation tools facilitate (http://cropontology.org) direct maintenance of the trait information and production of trait dictionaries by the crop communities. An important feature is the cross referencing of CO terms with the Crop database trait ID and with their synonyms in Plant Ontology (PO) and Trait Ontology (TO). Web links between cross referenced terms in CO provide online access to data annotated with similar ontological terms, particularly the genetic data in Gramene (University of Cornell) or the evaluation and climatic data in the Global Repository of evaluation trials of the Climate Change, Agriculture and Food Security programme (CCAFS). Cross-referencing and annotation will be further applied in the IBP. PMID:22934074

  5. The design ontology

    DEFF Research Database (Denmark)

    Storga, Mario; Andreasen, Mogens Myrup; Marjanovic, Dorian

    2010-01-01

    The article presents the research of the nature, building and practical role of a Design Ontology as a potential framework for the more efficient product development (PD) data-, information- and knowledge- description, -explanation, -understanding and -reusing. In the methodology for development ...

  6. Knowledge integration, teamwork and performance in health care.

    Science.gov (United States)

    Körner, Mirjam; Lippenberger, Corinna; Becker, Sonja; Reichler, Lars; Müller, Christian; Zimmermann, Linda; Rundel, Manfred; Baumeister, Harald

    2016-01-01

    Knowledge integration is the process of building shared mental models. The integration of the diverse knowledge of the health professions in shared mental models is a precondition for effective teamwork and team performance. As it is known that different groups of health care professionals often tend to work in isolation, the authors compared the perceptions of knowledge integration. It can be expected that based on this isolation, knowledge integration is assessed differently. The purpose of this paper is to test these differences in the perception of knowledge integration between the professional groups and to identify to what extent knowledge integration predicts perceptions of teamwork and team performance and to determine if teamwork has a mediating effect. The study is a multi-center cross-sectional study with a descriptive-explorative design. Data were collected by means of a staff questionnaire for all health care professionals working in the rehabilitation clinics. The results showed that there are significant differences in knowledge integration within interprofessional health care teams. Furthermore, it could be shown that knowledge integration is significantly related to patient-centered teamwork as well as to team performance. Mediation analysis revealed partial mediation of the effect of knowledge integration on team performance through teamwork. PRACTICAL/IMPLICATIONS: In practice, the results of the study provide a valuable starting point for team development interventions. This is the first study that explored knowledge integration in medical rehabilitation teams and its relation to patient-centered teamwork and team performance.

  7. An ontological case base engineering methodology for diabetes management.

    Science.gov (United States)

    El-Sappagh, Shaker H; El-Masri, Samir; Elmogy, Mohammed; Riad, A M; Saddik, Basema

    2014-08-01

    Ontology engineering covers issues related to ontology development and use. In Case Based Reasoning (CBR) system, ontology plays two main roles; the first as case base and the second as domain ontology. However, the ontology engineering literature does not provide adequate guidance on how to build, evaluate, and maintain ontologies. This paper proposes an ontology engineering methodology to generate case bases in the medical domain. It mainly focuses on the research of case representation in the form of ontology to support the case semantic retrieval and enhance all knowledge intensive CBR processes. A case study on diabetes diagnosis case base will be provided to evaluate the proposed methodology.

  8. Learning expressive ontologies

    CERN Document Server

    Völker, J

    2009-01-01

    This publication advances the state-of-the-art in ontology learning by presenting a set of novel approaches to the semi-automatic acquisition, refinement and evaluation of logically complex axiomatizations. It has been motivated by the fact that the realization of the semantic web envisioned by Tim Berners-Lee is still hampered by the lack of ontological resources, while at the same time more and more applications of semantic technologies emerge from fast-growing areas such as e-business or life sciences. Such knowledge-intensive applications, requiring large scale reasoning over complex domai

  9. Axiology on the Integration of Knowledge, Islam and Science

    Directory of Open Access Journals (Sweden)

    Mas’ud Zein

    2014-07-01

    Full Text Available The integration of Islamic and science was done through integration-interconnected, referring to ontological, epistemological dan axiological perspectives. This paper will focus on the integration of Islam and science from axiological perspective.  In the view of axiology, science is seen as neutral and value-free; the value of science is given by its users. This condition motivates Muslim scholars to reintegrate science and religion. The first attempt made is my giving ideas on the Islamization of science. The attempt to Islamize the science in the Islamic world is dilemmatic, whether to wrap western science with the label of Islam or Islamic, or transforming religious norms based the Qur’an and the Hadith to fit empirical data. Both strategies are difficult if the effort is not based on the critic of epistemology.

  10. Consistent data models and security standards for power system control through their standard compliant integration via ontologies; Einheitliche Datenmodelle und Sicherheitsstandards in der Netzleittechnik durch ihre standardkonforme Integration mittels Ontologien

    Energy Technology Data Exchange (ETDEWEB)

    Uslar, Mathias; Beenken, Petra; Beer, Sebastian [OFFIS, Oldenburg (Germany)

    2009-07-01

    The ongoing integration of distributed energy recourses into the existing power grid has lead to both grown communication costs and an increased need for interoperability between the involved actors. In this context, standardized and ontology- based data models help to reduce integration costs in heterogeneous system landscapes. Using ontology-based security profiles, such models can be extended with meta-data containing information about security measures for energyrelated data in need of protection. By this approach, we achieve both a unified data model and a unified security level. (orig.)

  11. Semantic Data Integration and Knowledge Management to Represent Biological Network Associations.

    Science.gov (United States)

    Losko, Sascha; Heumann, Klaus

    2017-01-01

    The vast quantities of information generated by academic and industrial research groups are reflected in a rapidly growing body of scientific literature and exponentially expanding resources of formalized data, including experimental data, originating from a multitude of "-omics" platforms, phenotype information, and clinical data. For bioinformatics, the challenge remains to structure this information so that scientists can identify relevant information, to integrate this information as specific "knowledge bases," and to formalize this knowledge across multiple scientific domains to facilitate hypothesis generation and validation. Here we report on progress made in building a generic knowledge management environment capable of representing and mining both explicit and implicit knowledge and, thus, generating new knowledge. Risk management in drug discovery and clinical research is used as a typical example to illustrate this approach. In this chapter we introduce techniques and concepts (such as ontologies, semantic objects, typed relationships, contexts, graphs, and information layers) that are used to represent complex biomedical networks. The BioXM™ Knowledge Management Environment is used as an example to demonstrate how a domain such as oncology is represented and how this representation is utilized for research.

  12. Ontology and medical diagnosis.

    Science.gov (United States)

    Bertaud-Gounot, Valérie; Duvauferrier, Régis; Burgun, Anita

    2012-03-01

    Ontology and associated generic tools are appropriate for knowledge modeling and reasoning, but most of the time, disease definitions in existing description logic (DL) ontology are not sufficient to classify patient's characteristics under a particular disease because they do not formalize operational definitions of diseases (association of signs and symptoms=diagnostic criteria). The main objective of this study is to propose an ontological representation which takes into account the diagnostic criteria on which specific patient conditions may be classified under a specific disease. This method needs as a prerequisite a clear list of necessary and sufficient diagnostic criteria as defined for lots of diseases by learned societies. It does not include probability/uncertainty which Web Ontology Language (OWL 2.0) cannot handle. We illustrate it with spondyloarthritis (SpA). Ontology has been designed in Protégé 4.1 OWL-DL2.0. Several kinds of criteria were formalized: (1) mandatory criteria, (2) picking two criteria among several diagnostic criteria, (3) numeric criteria. Thirty real patient cases were successfully classified with the reasoner. This study shows that it is possible to represent operational definitions of diseases with OWL and successfully classify real patient cases. Representing diagnostic criteria as descriptive knowledge (instead of rules in Semantic Web Rule Language or Prolog) allows us to take advantage of tools already available for OWL. While we focused on Assessment of SpondyloArthritis international Society SpA criteria, we believe that many of the representation issues addressed here are relevant to using OWL-DL for operational definition of other diseases in ontology.

  13. Intelligent Assistants for Distributed Knowledge Acquisition, Integration, Validation, and Maintenance

    National Research Council Canada - National Science Library

    Tecuci, Gheorghe; Boicu, Mihai

    2008-01-01

    This research has developed an integrated set of tools, called Disciple 2008 learning agent shell, for continuous acquisition of knowledge directly from subject matter experts, and for the integration...

  14. The Plant Phenology Ontology: A New Informatics Resource for Large-Scale Integration of Plant Phenology Data.

    Science.gov (United States)

    Stucky, Brian J; Guralnick, Rob; Deck, John; Denny, Ellen G; Bolmgren, Kjell; Walls, Ramona

    2018-01-01

    Plant phenology - the timing of plant life-cycle events, such as flowering or leafing out - plays a fundamental role in the functioning of terrestrial ecosystems, including human agricultural systems. Because plant phenology is often linked with climatic variables, there is widespread interest in developing a deeper understanding of global plant phenology patterns and trends. Although phenology data from around the world are currently available, truly global analyses of plant phenology have so far been difficult because the organizations producing large-scale phenology data are using non-standardized terminologies and metrics during data collection and data processing. To address this problem, we have developed the Plant Phenology Ontology (PPO). The PPO provides the standardized vocabulary and semantic framework that is needed for large-scale integration of heterogeneous plant phenology data. Here, we describe the PPO, and we also report preliminary results of using the PPO and a new data processing pipeline to build a large dataset of phenology information from North America and Europe.

  15. Un enfoque basado en ontología para la gestión integrada del medio ambiente y de la seguridad y la salud en obra An ontology-based approach for on-site integrated environmental and health and safety management

    Directory of Open Access Journals (Sweden)

    Marta Gangolells

    2012-12-01

    demonstrated interactions between environmental impacts and health and safety risks (Gangolells et al., 2009, Gangolells et al., 2010 led us to develop a domain ontology to build an integrated knowledge model for operational control at construction sites. The ontology-based approach that we have developed is strongly influenced by the methodology provided by Noy and McGuiness (2001 and models the key concepts and their relations in the domain in a structured, extendable, flexible, reusable and shareable way. The ontology-based approach is implemented through Pro-tégé 3.4 beta and properly evaluated by means of competency questions, internal verifications and expert validation interviews. This paper represents the first attempt at representing, sharing, reusing and managing the knowledge related to on-site integrated operational control of environmental and health and safety incidences and lays the ground for overcoming some barriers that contractors must face when they implement an integrated management system.

  16. SUGOI: automated ontology interchangeability

    CSIR Research Space (South Africa)

    Khan, ZC

    2015-04-01

    Full Text Available A foundational ontology can solve interoperability issues among the domain ontologies aligned to it. However, several foundational ontologies have been developed, hence such interoperability issues exist among domain ontologies. The novel SUGOI tool...

  17. Local Integration Ontological Model of Creative Class Migrants for Creative Cities

    Science.gov (United States)

    Sangkakorn, Korawan; Chakpitak, Nopasit; Yodmongkol, Pitipong

    2015-01-01

    An innovative creative class drives creative cities, urban areas in which diverse cultures are integrated into social and economic functions. The creative city of Chiang Mai, Thailand is renowned for its vibrant Lan Na culture and traditions, and draws new migrants from other areas in Thailand seeking to become part of the creative class. This…

  18. The use of semantic similarity measures for optimally integrating heterogeneous Gene Ontology data from large scale annotation pipelines

    Directory of Open Access Journals (Sweden)

    Gaston K Mazandu

    2014-08-01

    Full Text Available With the advancement of new high throughput sequencing technologies, there has been an increase in the number of genome sequencing projects worldwide, which has yielded complete genome sequences of human, animals and plants. Subsequently, several labs have focused on genome annotation, consisting of assigning functions to gene products, mostly using Gene Ontology (GO terms. As a consequence, there is an increased heterogeneity in annotations across genomes due to different approaches used by different pipelines to infer these annotations and also due to the nature of the GO structure itself. This makes a curator's task difficult, even if they adhere to the established guidelines for assessing these protein annotations. Here we develop a genome-scale approach for integrating GO annotations from different pipelines using semantic similarity measures. We used this approach to identify inconsistencies and similarities in functional annotations between orthologs of human and Drosophila melanogaster, to assess the quality of GO annotations derived from InterPro2GO mappings compared to manually annotated GO annotations for the Drosophila melanogaster proteome from a FlyBase dataset and human, and to filter GO annotation data for these proteomes. Results obtained indicate that an efficient integration of GO annotations eliminates redundancy up to 27.08 and 22.32% in the Drosophila melanogaster and human GO annotation datasets, respectively. Furthermore, we identified lack of and missing annotations for some orthologs, and annotation mismatches between InterPro2GO and manual pipelines in these two proteomes, thus requiring further curation. This simplifies and facilitates tasks of curators in assessing protein annotations, reduces redundancy and eliminates inconsistencies in large annotation datasets for ease of comparative functional genomics.

  19. Semi-automated ontology generation and evolution

    Science.gov (United States)

    Stirtzinger, Anthony P.; Anken, Craig S.

    2009-05-01

    Extending the notion of data models or object models, ontology can provide rich semantic definition not only to the meta-data but also to the instance data of domain knowledge, making these semantic definitions available in machine readable form. However, the generation of an effective ontology is a difficult task involving considerable labor and skill. This paper discusses an Ontology Generation and Evolution Processor (OGEP) aimed at automating this process, only requesting user input when un-resolvable ambiguous situations occur. OGEP directly attacks the main barrier which prevents automated (or self learning) ontology generation: the ability to understand the meaning of artifacts and the relationships the artifacts have to the domain space. OGEP leverages existing lexical to ontological mappings in the form of WordNet, and Suggested Upper Merged Ontology (SUMO) integrated with a semantic pattern-based structure referred to as the Semantic Grounding Mechanism (SGM) and implemented as a Corpus Reasoner. The OGEP processing is initiated by a Corpus Parser performing a lexical analysis of the corpus, reading in a document (or corpus) and preparing it for processing by annotating words and phrases. After the Corpus Parser is done, the Corpus Reasoner uses the parts of speech output to determine the semantic meaning of a word or phrase. The Corpus Reasoner is the crux of the OGEP system, analyzing, extrapolating, and evolving data from free text into cohesive semantic relationships. The Semantic Grounding Mechanism provides a basis for identifying and mapping semantic relationships. By blending together the WordNet lexicon and SUMO ontological layout, the SGM is given breadth and depth in its ability to extrapolate semantic relationships between domain entities. The combination of all these components results in an innovative approach to user assisted semantic-based ontology generation. This paper will describe the OGEP technology in the context of the architectural

  20. An exploration of knowledge integration problems in interdisciplinary research teams

    NARCIS (Netherlands)

    Bayerl, P.S.; Steinheider, B.

    2009-01-01

    The integration of function-specific expertise into a shared knowledge base is a crucial, but complex process for success in interdisciplinary teams. This paper presents an empirically derived typology of knowledge integration problems and links their occurrence to degree of heterogeneity and

  1. Knowledge-sharing Behavior and Post-acquisition Integration Failure

    DEFF Research Database (Denmark)

    Gammelgaard, Jens; Husted, Kenneth; Michailova, Snejina

    2004-01-01

    AbstractNot achieving the anticipated synergy effects in the post-acquisition integration context is a serious causefor the high acquisition failure rate. While existing studies on failures of acquisitions exist fromeconomics, finance, strategy, organization theory, and human resources management......, this paper appliesinsights from the knowledge-sharing literature. The paper establishes a conceptual link between obstaclesin the post-acquisition integration processes and individual knowledge-sharing behavior as related toknowledge transmitters and knowledge receivers. We argue that such an angle offers...... important insights toexplaining the high failure rate in acquisitions.Descriptors: post-acquisition integration, acquisition failure, individual knowledge-sharing behavior...

  2. Integrating technologies for effective knowledge management

    Energy Technology Data Exchange (ETDEWEB)

    Beaugrand, F.S.; Curtis, T.A. [Public Petroleum Data Model, PPDM Association, Calgary, AB (Canada)

    2002-06-01

    In order to succeed in today's business environment, effective knowledge management strategies are needed along with effective tools to solve real business problems. Relational databases provide accessible and practical tools that can be used to manage corporate knowledge assets. However, technology is growing so rapidly that it is difficult and too expensive for individual corporations to pursue each line of development independently. Collaborative efforts are needed to improve access to shared knowledge. The PPDM Association is an international not for profit standards body that is working collaboratively with the petroleum exploration and production industry to develop standards for managing data and knowledge, spatially enabling data, standardizing data content and data exchange. The PPDM Association provides a vendor-neutral environment for development, technical support and a methodology for designing, developing and publishing technical deliverables.

  3. From Knowledge Theory to Management Practice: Towards an Integrated Approach.

    Science.gov (United States)

    Shin, Minsoo; Holden, Tony; Schmidt, Ruth A.

    2001-01-01

    Critically contrasts the three main schools of thought on knowledge and assesses the resulting implications for knowledge management. Presents a conceptual model to integrate theoretical and practical themes to serve as a framework for developing a future research agenda for the development of knowledge management business tools and applications.…

  4. Building a developmental toxicity ontology.

    Science.gov (United States)

    Baker, Nancy; Boobis, Alan; Burgoon, Lyle; Carney, Edward; Currie, Richard; Fritsche, Ellen; Knudsen, Thomas; Laffont, Madeleine; Piersma, Aldert H; Poole, Alan; Schneider, Steffen; Daston, George

    2018-04-03

    As more information is generated about modes of action for developmental toxicity and more data are generated using high-throughput and high-content technologies, it is becoming necessary to organize that information. This report discussed the need for a systematic representation of knowledge about developmental toxicity (i.e., an ontology) and proposes a method to build one based on knowledge of developmental biology and mode of action/ adverse outcome pathways in developmental toxicity. This report is the result of a consensus working group developing a plan to create an ontology for developmental toxicity that spans multiple levels of biological organization. This report provide a description of some of the challenges in building a developmental toxicity ontology and outlines a proposed methodology to meet those challenges. As the ontology is built on currently available web-based resources, a review of these resources is provided. Case studies on one of the most well-understood morphogens and developmental toxicants, retinoic acid, are presented as examples of how such an ontology might be developed. This report outlines an approach to construct a developmental toxicity ontology. Such an ontology will facilitate computer-based prediction of substances likely to induce human developmental toxicity. © 2018 Wiley Periodicals, Inc.

  5. Development of an Ontology for Periodontitis.

    Science.gov (United States)

    Suzuki, Asami; Takai-Igarashi, Takako; Nakaya, Jun; Tanaka, Hiroshi

    2015-01-01

    In the clinical dentists and periodontal researchers' community, there is an obvious demand for a systems model capable of linking the clinical presentation of periodontitis to underlying molecular knowledge. A computer-readable representation of processes on disease development will give periodontal researchers opportunities to elucidate pathways and mechanisms of periodontitis. An ontology for periodontitis can be a model for integration of large variety of factors relating to a complex disease such as chronic inflammation in different organs accompanied by bone remodeling and immune system disorders, which has recently been referred to as osteoimmunology. Terms characteristic of descriptions related to the onset and progression of periodontitis were manually extracted from 194 review articles and PubMed abstracts by experts in periodontology. We specified all the relations between the extracted terms and constructed them into an ontology for periodontitis. We also investigated matching between classes of our ontology and that of Gene Ontology Biological Process. We developed an ontology for periodontitis called Periodontitis-Ontology (PeriO). The pathological progression of periodontitis is caused by complex, multi-factor interrelationships. PeriO consists of all the required concepts to represent the pathological progression and clinical treatment of periodontitis. The pathological processes were formalized with reference to Basic Formal Ontology and Relation Ontology, which accounts for participants in the processes realized by biological objects such as molecules and cells. We investigated the peculiarity of biological processes observed in pathological progression and medical treatments for the disease in comparison with Gene Ontology Biological Process (GO-BP) annotations. The results indicated that peculiarities of Perio existed in 1) granularity and context dependency of both the conceptualizations, and 2) causality intrinsic to the pathological processes

  6. A fuzzy-ontology-oriented case-based reasoning framework for semantic diabetes diagnosis.

    Science.gov (United States)

    El-Sappagh, Shaker; Elmogy, Mohammed; Riad, A M

    2015-11-01

    Case-based reasoning (CBR) is a problem-solving paradigm that uses past knowledge to interpret or solve new problems. It is suitable for experience-based and theory-less problems. Building a semantically intelligent CBR that mimic the expert thinking can solve many problems especially medical ones. Knowledge-intensive CBR using formal ontologies is an evolvement of this paradigm. Ontologies can be used for case representation and storage, and it can be used as a background knowledge. Using standard medical ontologies, such as SNOMED CT, enhances the interoperability and integration with the health care systems. Moreover, utilizing vague or imprecise knowledge further improves the CBR semantic effectiveness. This paper proposes a fuzzy ontology-based CBR framework. It proposes a fuzzy case-base OWL2 ontology, and a fuzzy semantic retrieval algorithm that handles many feature types. This framework is implemented and tested on the diabetes diagnosis problem. The fuzzy ontology is populated with 60 real diabetic cases. The effectiveness of the proposed approach is illustrated with a set of experiments and case studies. The resulting system can answer complex medical queries related to semantic understanding of medical concepts and handling of vague terms. The resulting fuzzy case-base ontology has 63 concepts, 54 (fuzzy) object properties, 138 (fuzzy) datatype properties, 105 fuzzy datatypes, and 2640 instances. The system achieves an accuracy of 97.67%. We compare our framework with existing CBR systems and a set of five machine-learning classifiers; our system outperforms all of these systems. Building an integrated CBR system can improve its performance. Representing CBR knowledge using the fuzzy ontology and building a case retrieval algorithm that treats different features differently improves the accuracy of the resulting systems. Copyright © 2015 Elsevier B.V. All rights reserved.

  7. Audit Validation Using Ontologies

    Directory of Open Access Journals (Sweden)

    Ion IVAN

    2015-01-01

    Full Text Available Requirements to increase quality audit processes in enterprises are defined. It substantiates the need for assessment and management audit processes using ontologies. Sets of rules, ways to assess the consistency of rules and behavior within the organization are defined. Using ontologies are obtained qualifications that assess the organization's audit. Elaboration of the audit reports is a perfect algorithm-based activity characterized by generality, determinism, reproducibility, accuracy and a well-established. The auditors obtain effective levels. Through ontologies obtain the audit calculated level. Because the audit report is qualitative structure of information and knowledge it is very hard to analyze and interpret by different groups of users (shareholders, managers or stakeholders. Developing ontology for audit reports validation will be a useful instrument for both auditors and report users. In this paper we propose an instrument for validation of audit reports contain a lot of keywords that calculates indicators, a lot of indicators for each key word there is an indicator, qualitative levels; interpreter who builds a table of indicators, levels of actual and calculated levels.

  8. Behavior change interventions: the potential of ontologies for advancing science and practice.

    Science.gov (United States)

    Larsen, Kai R; Michie, Susan; Hekler, Eric B; Gibson, Bryan; Spruijt-Metz, Donna; Ahern, David; Cole-Lewis, Heather; Ellis, Rebecca J Bartlett; Hesse, Bradford; Moser, Richard P; Yi, Jean

    2017-02-01

    A central goal of behavioral medicine is the creation of evidence-based interventions for promoting behavior change. Scientific knowledge about behavior change could be more effectively accumulated using "ontologies." In information science, an ontology is a systematic method for articulating a "controlled vocabulary" of agreed-upon terms and their inter-relationships. It involves three core elements: (1) a controlled vocabulary specifying and defining existing classes; (2) specification of the inter-relationships between classes; and (3) codification in a computer-readable format to enable knowledge generation, organization, reuse, integration, and analysis. This paper introduces ontologies, provides a review of current efforts to create ontologies related to behavior change interventions and suggests future work. This paper was written by behavioral medicine and information science experts and was developed in partnership between the Society of Behavioral Medicine's Technology Special Interest Group (SIG) and the Theories and Techniques of Behavior Change Interventions SIG. In recent years significant progress has been made in the foundational work needed to develop ontologies of behavior change. Ontologies of behavior change could facilitate a transformation of behavioral science from a field in which data from different experiments are siloed into one in which data across experiments could be compared and/or integrated. This could facilitate new approaches to hypothesis generation and knowledge discovery in behavioral science.

  9. Ontology-based semantic information technology for safeguards: opportunities and challenges

    International Nuclear Information System (INIS)

    McDaniel, Michael

    2014-01-01

    The challenge of efficiently handling large volumes of heterogeneous information is a barrier to more effective safeguards implementation. With the emergence of new technologies for generating and collecting information this is an issue common to many industries and problem domains. Several diverse information‑intensive fields are developing and adopting ontology‑based semantic information technology solutions to address issues of information integration, federation and interoperability. Ontology, in this context, refers to the formal specification of the content, structure, and logic of knowledge within a domain of interest. Ontology‑based semantic information technologies have the potential to impact nearly every level of safeguards implementation, from information collection and integration, to personnel training and knowledge retention, to planning and analysis. However, substantial challenges remain before the full benefits of semantic technology can be realized. Perhaps the most significant challenge is the development of a nuclear fuel cycle ontology. For safeguards, existing knowledge resources such as the IAEA’s Physical Model and established upper level ontologies can be used as starting points for ontology development, but a concerted effort must be taken by the safeguards community for such an activity to be successful. This paper provides a brief background of ontologies and semantic information technology, demonstrates how these technologies are used in other areas, offers examples of how ontologies can be applied to safeguards, and discusses the challenges of developing and implementing this technology as well as a possible path forward.

  10. DEPONTO: A Reusable Dependability Domain Ontology

    Directory of Open Access Journals (Sweden)

    Teodora Sanislav

    2015-08-01

    Full Text Available This paper proposes a dependability reusable ontology for knowledge representation. The fundamental knowledge related to dependability follows its taxonomy. Thus, this paper gives an analysis of what is the dependability domain ontology andof its components.The dependability domain ontology plays an important role in ensuring the dependability of information systems by providing support for their diagnosis in case of faults, errors and failures.The proposed ontology is used as a dependability framework in two case study Cyber-Physical Systemswhich demonstrate its reusability within this category of systems.

  11. Learning Resources Organization Using Ontological Framework

    Science.gov (United States)

    Gavrilova, Tatiana; Gorovoy, Vladimir; Petrashen, Elena

    The paper describes the ontological approach to the knowledge structuring for the e-learning portal design as it turns out to be efficient and relevant to current domain conditions. It is primarily based on the visual ontology-based description of the content of the learning materials and this helps to provide productive and personalized access to these materials. The experience of ontology developing for Knowledge Engineering coursetersburg State University is discussed and “OntolingeWiki” tool for creating ontology-based e-learning portals is described.

  12. Phenex: ontological annotation of phenotypic diversity.

    Directory of Open Access Journals (Sweden)

    James P Balhoff

    2010-05-01

    Full Text Available Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge.Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices.Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.

  13. Phenex: ontological annotation of phenotypic diversity.

    Science.gov (United States)

    Balhoff, James P; Dahdul, Wasila M; Kothari, Cartik R; Lapp, Hilmar; Lundberg, John G; Mabee, Paula; Midford, Peter E; Westerfield, Monte; Vision, Todd J

    2010-05-05

    Phenotypic differences among species have long been systematically itemized and described by biologists in the process of investigating phylogenetic relationships and trait evolution. Traditionally, these descriptions have been expressed in natural language within the context of individual journal publications or monographs. As such, this rich store of phenotype data has been largely unavailable for statistical and computational comparisons across studies or integration with other biological knowledge. Here we describe Phenex, a platform-independent desktop application designed to facilitate efficient and consistent annotation of phenotypic similarities and differences using Entity-Quality syntax, drawing on terms from community ontologies for anatomical entities, phenotypic qualities, and taxonomic names. Phenex can be configured to load only those ontologies pertinent to a taxonomic group of interest. The graphical user interface was optimized for evolutionary biologists accustomed to working with lists of taxa, characters, character states, and character-by-taxon matrices. Annotation of phenotypic data using ontologies and globally unique taxonomic identifiers will allow biologists to integrate phenotypic data from different organisms and studies, leveraging decades of work in systematics and comparative morphology.

  14. Gene Ontology Consortium: going forward.

    Science.gov (United States)

    2015-01-01

    The Gene Ontology (GO; http://www.geneontology.org) is a community-based bioinformatics resource that supplies information about gene product function using ontologies to represent biological knowledge. Here we describe improvements and expansions to several branches of the ontology, as well as updates that have allowed us to more efficiently disseminate the GO and capture feedback from the research community. The Gene Ontology Consortium (GOC) has expanded areas of the ontology such as cilia-related terms, cell-cycle terms and multicellular organism processes. We have also implemented new tools for generating ontology terms based on a set of logical rules making use of templates, and we have made efforts to increase our use of logical definitions. The GOC has a new and improved web site summarizing new developments and documentation, serving as a portal to GO data. Users can perform GO enrichment analysis, and search the GO for terms, annotations to gene products, and associated metadata across multiple species using the all-new AmiGO 2 browser. We encourage and welcome the input of the research community in all biological areas in our continued effort to improve the Gene Ontology. © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research.

  15. Ontology-based intelligent fuzzy agent for diabetes application

    NARCIS (Netherlands)

    Acampora, G.; Lee, C.-S.; Wang, M.-H.; Hsu, C.-Y.; Loia, V.

    2009-01-01

    It is widely pointed out that classical ontologies are not sufficient to deal with imprecise and vague knowledge for some real world applications, but the fuzzy ontology can effectively solve data and knowledge with uncertainty. In this paper, an ontology-based intelligent fuzzy agent (OIFA),

  16. LOGISTICS OPTIMIZATION USING ONTOLOGIES

    OpenAIRE

    Hendi , Hayder; Ahmad , Adeel; Bouneffa , Mourad; Fonlupt , Cyril

    2014-01-01

    International audience; Logistics processes involve complex physical flows and integration of different elements. It is widely observed that the uncontrolled processes can decline the state of logistics. The optimization of logistic processes can support the desired growth and consistent continuity of logistics. In this paper, we present a software framework for logistic processes optimization. It primarily defines logistic ontologies and then optimize them. It intends to assist the design of...

  17. Integrating ICT in Agriculture for Knowledge-Based Economy

    African Journals Online (AJOL)

    agriculture –based livelihoods, demands the integration of ICT knowledge with agriculture. .... (CGIAR) shows the vital role of Agricultural development in Rwanda's ... Network, Rwanda National Backbone Project, Regional Communication.

  18. Text Mining to inform construction of Earth and Environmental Science Ontologies

    Science.gov (United States)

    Schildhauer, M.; Adams, B.; Rebich Hespanha, S.

    2013-12-01

    There is a clear need for better semantic representation of Earth and environmental concepts, to facilitate more effective discovery and re-use of information resources relevant to scientists doing integrative research. In order to develop general-purpose Earth and environmental science ontologies, however, it is necessary to represent concepts and relationships that span usage across multiple disciplines and scientific specialties. Traditional knowledge modeling through ontologies utilizes expert knowledge but inevitably favors the particular perspectives of the ontology engineers, as well as the domain experts who interacted with them. This often leads to ontologies that lack robust coverage of synonymy, while also missing important relationships among concepts that can be extremely useful for working scientists to be aware of. In this presentation we will discuss methods we have developed that utilize statistical topic modeling on a large corpus of Earth and environmental science articles, to expand coverage and disclose relationships among concepts in the Earth sciences. For our work we collected a corpus of over 121,000 abstracts from many of the top Earth and environmental science journals. We performed latent Dirichlet allocation topic modeling on this corpus to discover a set of latent topics, which consist of terms that commonly co-occur in abstracts. We match terms in the topics to concept labels in existing ontologies to reveal gaps, and we examine which terms are commonly associated in natural language discourse, to identify relationships that are important to formally model in ontologies. Our text mining methodology uncovers significant gaps in the content of some popular existing ontologies, and we show how, through a workflow involving human interpretation of topic models, we can bootstrap ontologies to have much better coverage and richer semantics. Because we base our methods directly on what working scientists are communicating about their

  19. Integrating Indigenous Knowledge in Climate Risk Management in ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    27 mars 2008 ... Integrating Indigenous Knowledge in Climate Risk Management in support of Community Based Adaptation. Traditionally, African farmers have used indigenous knowledge to understand weather and climate patterns and make decisions about crop and irrigation cycles. However, increased variability ...

  20. Biomarker Gene Signature Discovery Integrating Network Knowledge

    Directory of Open Access Journals (Sweden)

    Holger Fröhlich

    2012-02-01

    Full Text Available Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.

  1. Integrating knowledge based functionality in commercial hospital information systems.

    Science.gov (United States)

    Müller, M L; Ganslandt, T; Eich, H P; Lang, K; Ohmann, C; Prokosch, H U

    2000-01-01

    Successful integration of knowledge-based functions in the electronic patient record depends on direct and context-sensitive accessibility and availability to clinicians and must suit their workflow. In this paper we describe an exemplary integration of an existing standalone scoring system for acute abdominal pain into two different commercial hospital information systems using Java/Corba technolgy.

  2. Knowledge and information management for integrated water resource management

    Science.gov (United States)

    Watershed information systems that integrate data and analytical tools are critical enabling technologies to support Integrated Water Resource Management (IWRM) by converting data into information, and information into knowledge. Many factors bring people to the table to participate in an IWRM fra...

  3. Ontological Surprises

    DEFF Research Database (Denmark)

    Leahu, Lucian

    2016-01-01

    a hybrid approach where machine learning algorithms are used to identify objects as well as connections between them; finally, it argues for remaining open to ontological surprises in machine learning as they may enable the crafting of different relations with and through technologies.......This paper investigates how we might rethink design as the technological crafting of human-machine relations in the context of a machine learning technique called neural networks. It analyzes Google’s Inceptionism project, which uses neural networks for image recognition. The surprising output...

  4. Integrating pedagogical content knowledge and pedagogical/psychological knowledge in mathematics

    Science.gov (United States)

    Harr, Nora; Eichler, Andreas; Renkl, Alexander

    2014-01-01

    In teacher education at universities, general pedagogical and psychological principles are often treated separately from subject matter knowledge and therefore run the risk of not being applied in the teaching subject. In an experimental study (N = 60 mathematics student teachers) we investigated the effects of providing aspects of general pedagogical/psychological knowledge (PPK) and pedagogical content knowledge (PCK) in an integrated or separated way. In both conditions (“integrated” vs. “separated”), participants individually worked on computer-based learning environments addressing the same topic: use and handling of multiple external representations, a central issue in mathematics. We experimentally varied whether PPK aspects and PCK aspects were treated integrated or apart from one another. As expected, the integrated condition led to greater application of pedagogical/psychological aspects and an increase in applying both knowledge types simultaneously compared to the separated condition. Overall, our findings indicate beneficial effects of an integrated design in teacher education. PMID:25191300

  5. BioPortal: An Open-Source Community-Based Ontology Repository

    Science.gov (United States)

    Noy, N.; NCBO Team

    2011-12-01

    Advances in computing power and new computational techniques have changed the way researchers approach science. In many fields, one of the most fruitful approaches has been to use semantically aware software to break down the barriers among disparate domains, systems, data sources, and technologies. Such software facilitates data aggregation, improves search, and ultimately allows the detection of new associations that were previously not detectable. Achieving these analyses requires software systems that take advantage of the semantics and that can intelligently negotiate domains and knowledge sources, identifying commonality across systems that use different and conflicting vocabularies, while understanding apparent differences that may be concealed by the use of superficially similar terms. An ontology, a semantically rich vocabulary for a domain of interest, is the cornerstone of software for bridging systems, domains, and resources. However, as ontologies become the foundation of all semantic technologies in e-science, we must develop an infrastructure for sharing ontologies, finding and evaluating them, integrating and mapping among them, and using ontologies in applications that help scientists process their data. BioPortal [1] is an open-source on-line community-based ontology repository that has been used as a critical component of semantic infrastructure in several domains, including biomedicine and bio-geochemical data. BioPortal, uses the social approaches in the Web 2.0 style to bring structure and order to the collection of biomedical ontologies. It enables users to provide and discuss a wide array of knowledge components, from submitting the ontologies themselves, to commenting on and discussing classes in the ontologies, to reviewing ontologies in the context of their own ontology-based projects, to creating mappings between overlapping ontologies and discussing and critiquing the mappings. Critically, it provides web-service access to all its

  6. Merged ontology for engineering design: Contrasting empirical and theoretical approaches to develop engineering ontologies

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Storga, M

    2009-01-01

    to developing the ontology engineering design integrated taxonomies (EDIT) with a theoretical approach in which concepts and relations are elicited from engineering design theories ontology (DO) The limitations and advantages of each approach are discussed. The research methodology adopted is to map......This paper presents a comparison of two previous and separate efforts to develop an ontology in the engineering design domain, together with an ontology proposal from which ontologies for a specific application may be derived. The research contrasts an empirical, user-centered approach...

  7. Building a biomedical ontology recommender web service

    Directory of Open Access Journals (Sweden)

    Jonquet Clement

    2010-06-01

    Full Text Available Abstract Background Researchers in biomedical informatics use ontologies and terminologies to annotate their data in order to facilitate data integration and translational discoveries. As the use of ontologies for annotation of biomedical datasets has risen, a common challenge is to identify ontologies that are best suited to annotating specific datasets. The number and variety of biomedical ontologies is large, and it is cumbersome for a researcher to figure out which ontology to use. Methods We present the Biomedical Ontology Recommender web service. The system uses textual metadata or a set of keywords describing a domain of interest and suggests appropriate ontologies for annotating or representing the data. The service makes a decision based on three criteria. The first one is coverage, or the ontologies that provide most terms covering the input text. The second is connectivity, or the ontologies that are most often mapped to by other ontologies. The final criterion is size, or the number of concepts in the ontologies. The service scores the ontologies as a function of scores of the annotations created using the National Center for Biomedical Ontology (NCBO Annotator web service. We used all the ontologies from the UMLS Metathesaurus and the NCBO BioPortal. Results We compare and contrast our Recommender by an exhaustive functional comparison to previously published efforts. We evaluate and discuss the results of several recommendation heuristics in the context of three real world use cases. The best recommendations heuristics, rated ‘very relevant’ by expert evaluators, are the ones based on coverage and connectivity criteria. The Recommender service (alpha version is available to the community and is embedded into BioPortal.

  8. Integrating knowledge and knowledge processes: A critical incident study of product development projects.

    NARCIS (Netherlands)

    Kraaijenbrink, Jeroen

    2012-01-01

    Various scholars have argued that knowledge processes in organizations are integrally linked in practice. The extant literature though treats them separately and thereby disregards the interactions and tensions between them. A result of this way of studying knowledge processes is that little is

  9. Learning knowledge as an integral part of competencies in higher education: Effects on students' knowledge

    NARCIS (Netherlands)

    Van Bommel, Marijke; Boshuizen, Els; Kwakman, Kitty

    2011-01-01

    Van Bommel, M., Boshuizen, H. P. A., & Kwakman, K. (2010, 25-27 August). Learning knowledge as an integral part of competencies in higher education: Effects on students' knowledge. Paper presented at the 5th EARLI-SIG14 Learning and Professional Development, Munich, Germany.

  10. OIntEd: online ontology instance editor enabling a new approach to ontology development

    NARCIS (Netherlands)

    Wibisono, A.; Koning, R.; Grosso, P.; Belloum, A.; Bubak, M.; de Laat, C.

    2013-01-01

    Ontology development involves people with different background knowledge and expertise. It is an elaborate process, where sophisticated tools for experienced knowledge engineers are available. However, domain experts need simple tools that they can use to focus on ontology instantiation. In this

  11. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  12. Ontological Engineering for the Cadastral Domain

    DEFF Research Database (Denmark)

    Stubkjær, Erik; Stuckenschmidt, Heiner

    2000-01-01

    conceptualization of the world is that much information remains implicit. Ontologies have set out to overcome the problem of implicit and hidden knowledge by making the conceptualization of a domain (e.g. mathematics) explicit. Ontological engineering is thus an approach to achieve a conceptual rigor...... that characterizes established academic disciplines, like geodesy. Many university courses address more application oriented fields, like cadastral law, and spatial planning, and they may benefit from the ontological engineering approach. The paper provides an introduction to the field of ontological engineering...

  13. A Process for the Representation of openEHR ADL Archetypes in OWL Ontologies.

    Science.gov (United States)

    Porn, Alex Mateus; Peres, Leticia Mara; Didonet Del Fabro, Marcos

    2015-01-01

    ADL is a formal language to express archetypes, independent of standards or domain. However, its specification is not precise enough in relation to the specialization and semantic of archetypes, presenting difficulties in implementation and a few available tools. Archetypes may be implemented using other languages such as XML or OWL, increasing integration with Semantic Web tools. Exchanging and transforming data can be better implemented with semantics oriented models, for example using OWL which is a language to define and instantiate Web ontologies defined by W3C. OWL permits defining significant, detailed, precise and consistent distinctions among classes, properties and relations by the user, ensuring the consistency of knowledge than using ADL techniques. This paper presents a process of an openEHR ADL archetypes representation in OWL ontologies. This process consists of ADL archetypes conversion in OWL ontologies and validation of OWL resultant ontologies using the mutation test.

  14. Use of the CIM Ontology

    Energy Technology Data Exchange (ETDEWEB)

    Neumann, Scott; Britton, Jay; Devos, Arnold N.; Widergren, Steven E.

    2006-02-08

    There are many uses for the Common Information Model (CIM), an ontology that is being standardized through Technical Committee 57 of the International Electrotechnical Commission (IEC TC57). The most common uses to date have included application modeling, information exchanges, information management and systems integration. As one should expect, there are many issues that become apparent when the CIM ontology is applied to any one use. Some of these issues are shortcomings within the current draft of the CIM, and others are a consequence of the different ways in which the CIM can be applied using different technologies. As the CIM ontology will and should evolve, there are several dangers that need to be recognized. One is overall consistency and impact upon applications when extending the CIM for a specific need. Another is that a tight coupling of the CIM to specific technologies could limit the value of the CIM in the longer term as an ontology, which becomes a larger issue over time as new technologies emerge. The integration of systems is one specific area of interest for application of the CIM ontology. This is an area dominated by the use of XML for the definition of messages. While this is certainly true when using Enterprise Application Integration (EAI) products, it is even more true with the movement towards the use of Web Services (WS), Service-Oriented Architectures (SOA) and Enterprise Service Buses (ESB) for integration. This general IT industry trend is consistent with trends seen within the IEC TC57 scope of power system management and associated information exchange. The challenge for TC57 is how to best leverage the CIM ontology using the various XML technologies and standards for integration. This paper will provide examples of how the CIM ontology is used and describe some specific issues that should be addressed within the CIM in order to increase its usefulness as an ontology. It will also describe some of the issues and challenges that will

  15. Ontology Assisted Formal Specification Extraction from Text

    Directory of Open Access Journals (Sweden)

    Andreea Mihis

    2010-12-01

    Full Text Available In the field of knowledge processing, the ontologies are the most important mean. They make possible for the computer to understand better the natural language and to make judgments. In this paper, a method which use ontologies in the semi-automatic extraction of formal specifications from a natural language text is proposed.

  16. A methodology for creating ontologies for engineering design

    DEFF Research Database (Denmark)

    Ahmed, Saeema; Kim, S.; Wallace, K.M.

    2007-01-01

    This paper describes a six-stage methodology for developing ontologies for engineering design, together with the research methods and evaluation of each stage. The methodology focuses upon understanding a user's domain models through empirical research. A case study of an ontology for searching......, indexing, and retrieving engineering knowledge is described. The root concepts of the ontology were elicited from engineering designers. Relationships between concepts are extracted as the ontology is populated. The contribution of this research is a methodology to allow researchers. and industry to create...... ontologies for their particular purpose and a thesaurus for the terms within the ontology....

  17. An integrative approach to knowledge transfer and integration: Spanning boundaries through objects, people and processes

    NARCIS (Netherlands)

    Duijn, M.; Rijnveld, M.

    2008-01-01

    Knowledge transfer and integration is the main challenge in many knowledge management projects. This challenge follows from the observation that it is difficult to determine how and what knowledge may transfer from one person to another, from one team to another and from one network or organization

  18. Semantic Health Knowledge Graph: Semantic Integration of Heterogeneous Medical Knowledge and Services

    Directory of Open Access Journals (Sweden)

    Longxiang Shi

    2017-01-01

    Full Text Available With the explosion of healthcare information, there has been a tremendous amount of heterogeneous textual medical knowledge (TMK, which plays an essential role in healthcare information systems. Existing works for integrating and utilizing the TMK mainly focus on straightforward connections establishment and pay less attention to make computers interpret and retrieve knowledge correctly and quickly. In this paper, we explore a novel model to organize and integrate the TMK into conceptual graphs. We then employ a framework to automatically retrieve knowledge in knowledge graphs with a high precision. In order to perform reasonable inference on knowledge graphs, we propose a contextual inference pruning algorithm to achieve efficient chain inference. Our algorithm achieves a better inference result with precision and recall of 92% and 96%, respectively, which can avoid most of the meaningless inferences. In addition, we implement two prototypes and provide services, and the results show our approach is practical and effective.

  19. Aber-OWL: a framework for ontology-based data access in biology

    KAUST Repository

    Hoehndorf, Robert

    2015-01-28

    Background: Many ontologies have been developed in biology and these ontologies increasingly contain large volumes of formalized knowledge commonly expressed in the Web Ontology Language (OWL). Computational access to the knowledge contained within these ontologies relies on the use of automated reasoning. Results: We have developed the Aber-OWL infrastructure that provides reasoning services for bio-ontologies. Aber-OWL consists of an ontology repository, a set of web services and web interfaces that enable ontology-based semantic access to biological data and literature. Aber-OWL is freely available at http://aber-owl.net. Conclusions: Aber-OWL provides a framework for automatically accessing information that is annotated with ontologies or contains terms used to label classes in ontologies. When using Aber-OWL, access to ontologies and data annotated with them is not merely based on class names or identifiers but rather on the knowledge the ontologies contain and the inferences that can be drawn from it.

  20. Didactical Ontologies

    Directory of Open Access Journals (Sweden)

    Steffen Mencke, Reiner Dumke

    2008-03-01

    Full Text Available Ontologies are a fundamental concept of theSemantic Web envisioned by Tim Berners-Lee [1]. Togetherwith explicit representation of the semantics of data formachine-accessibility such domain theories are the basis forintelligent next generation applications for the web andother areas of interest [2]. Their application for specialaspects within the domain of e-learning is often proposed tosupport the increasing complexity ([3], [4], [5], [6]. So theycan provide a better support for course generation orlearning scenario description [7]. By the modeling ofdidactics-related expertise and their provision for thecreators of courses many improvements like reuse, rapiddevelopment and of course increased learning performancebecome possible due to the separation from other aspects ofe-learning platforms as already proposed in [8].

  1. Knowledge representation for integrated plant operation and maintenance

    DEFF Research Database (Denmark)

    Lind, Morten

    2010-01-01

    Integrated operation and maintenance of process plants has many advantages. One advantage is the improved economy obtained by reducing the number of plant shutdowns. Another is to increase reliability of operation by monitoring of risk levels during on-line maintenance. Integrated plant operation...... and maintenance require knowledge bases which can capture the interactions between the two plant activities. As an example, taking out a component or a subsystem for maintenance during operation will require a knowledge base representing the interactions between plant structure, functions, operating states...... and goals and incorporate knowledge about redundancy and reliability data. Multilevel Flow Modeling can be used build knowledge bases representing plant goals and functions and has been applied for fault diagnosis and supervisory control but currently it does not take into account structural information...

  2. The Role of Integrated Knowledge Translation in Intervention Research.

    Science.gov (United States)

    Wathen, C Nadine; MacMillan, Harriet L

    2018-04-01

    There is widespread recognition across the full range of applied research disciplines, including health and social services, about the challenges of integrating scientifically derived research evidence into policy and/or practice decisions. These "disconnects" or "knowledge-practice gaps" between research production and use have spawned a new research field, most commonly known as either "implementation science" or "knowledge translation." The present paper will review key concepts in this area, with a particular focus on "integrated knowledge translation" (IKT)-which focuses on researcher-knowledge user partnership-in the area of mental health and prevention of violence against women and children using case examples from completed and ongoing work. A key distinction is made between the practice of KT (disseminating, communicating, etc.), and the science of KT, i.e., research regarding effective KT approaches. We conclude with a discussion of the relevance of IKT for mental health intervention research with children and adolescents.

  3. The ontology-based answers (OBA) service: a connector for embedded usage of ontologies in applications.

    Science.gov (United States)

    Dönitz, Jürgen; Wingender, Edgar

    2012-01-01

    The semantic web depends on the use of ontologies to let electronic systems interpret contextual information. Optimally, the handling and access of ontologies should be completely transparent to the user. As a means to this end, we have developed a service that attempts to bridge the gap between experts in a certain knowledge domain, ontologists, and application developers. The ontology-based answers (OBA) service introduced here can be embedded into custom applications to grant access to the classes of ontologies and their relations as most important structural features as well as to information encoded in the relations between ontology classes. Thus computational biologists can benefit from ontologies without detailed knowledge about the respective ontology. The content of ontologies is mapped to a graph of connected objects which is compatible to the object-oriented programming style in Java. Semantic functions implement knowledge about the complex semantics of an ontology beyond the class hierarchy and "partOf" relations. By using these OBA functions an application can, for example, provide a semantic search function, or (in the examples outlined) map an anatomical structure to the organs it belongs to. The semantic functions relieve the application developer from the necessity of acquiring in-depth knowledge about the semantics and curation guidelines of the used ontologies by implementing the required knowledge. The architecture of the OBA service encapsulates the logic to process ontologies in order to achieve a separation from the application logic. A public server with the current plugins is available and can be used with the provided connector in a custom application in scenarios analogous to the presented use cases. The server and the client are freely available if a project requires the use of custom plugins or non-public ontologies. The OBA service and further documentation is available at http://www.bioinf.med.uni-goettingen.de/projects/oba.

  4. A Sociology of Knowledge Approach to European Integration

    DEFF Research Database (Denmark)

    Adler-Nissen, Rebecca; Kropp, Kristoffer

    2015-01-01

    Scholars are deeply involved in the process of European integration, but we lack systematic understanding of this involvement. On the one hand, scholars, academic ideas and ideologies shape European integration and policies (e.g. the Economic and Monetary Union and the free movement of people......). On the other hand, EU institutions, policies and practitioners produce particular forms of knowledge (e.g. the Eurobarometer and benchmarking of national performances) that inform social scientific choices of theories, methods and research topics. Drawing on the new sociology of knowledge as well as Science...

  5. NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation.

    Science.gov (United States)

    Martínez-Romero, Marcos; Jonquet, Clement; O'Connor, Martin J; Graybeal, John; Pazos, Alejandro; Musen, Mark A

    2017-06-07

    Ontologies and controlled terminologies have become increasingly important in biomedical research. Researchers use ontologies to annotate their data with ontology terms, enabling better data integration and interoperability across disparate datasets. However, the number, variety and complexity of current biomedical ontologies make it cumbersome for researchers to determine which ones to reuse for their specific needs. To overcome this problem, in 2010 the National Center for Biomedical Ontology (NCBO) released the Ontology Recommender, which is a service that receives a biomedical text corpus or a list of keywords and suggests ontologies appropriate for referencing the indicated terms. We developed a new version of the NCBO Ontology Recommender. Called Ontology Recommender 2.0, it uses a novel recommendation approach that evaluates the relevance of an ontology to biomedical text data according to four different criteria: (1) the extent to which the ontology covers the input data; (2) the acceptance of the ontology in the biomedical community; (3) the level of detail of the ontology classes that cover the input data; and (4) the specialization of the ontology to the domain of the input data. Our evaluation shows that the enhanced recommender provides higher quality suggestions than the original approach, providing better coverage of the input data, more detailed information about their concepts, increased specialization for the domain of the input data, and greater acceptance and use in the community. In addition, it provides users with more explanatory information, along with suggestions of not only individual ontologies but also groups of ontologies to use together. It also can be customized to fit the needs of different ontology recommendation scenarios. Ontology Recommender 2.0 suggests relevant ontologies for annotating biomedical text data. It combines the strengths of its predecessor with a range of adjustments and new features that improve its reliability

  6. An infrastructure for ontology-based information systems in biomedicine: RICORDO case study.

    Science.gov (United States)

    Wimalaratne, Sarala M; Grenon, Pierre; Hoehndorf, Robert; Gkoutos, Georgios V; de Bono, Bernard

    2012-02-01

    The article presents an infrastructure for supporting the semantic interoperability of biomedical resources based on the management (storing and inference-based querying) of their ontology-based annotations. This infrastructure consists of: (i) a repository to store and query ontology-based annotations; (ii) a knowledge base server with an inference engine to support the storage of and reasoning over ontologies used in the annotation of resources; (iii) a set of applications and services allowing interaction with the integrated repository and knowledge base. The infrastructure is being prototyped and developed and evaluated by the RICORDO project in support of the knowledge management of biomedical resources, including physiology and pharmacology models and associated clinical data. The RICORDO toolkit and its source code are freely available from http://ricordo.eu/relevant-resources. sarala@ebi.ac.uk.

  7. The Relationship between User Expertise and Structural Ontology Characteristics

    Science.gov (United States)

    Waldstein, Ilya Michael

    2014-01-01

    Ontologies are commonly used to support application tasks such as natural language processing, knowledge management, learning, browsing, and search. Literature recommends considering specific context during ontology design, and highlights that a different context is responsible for problems in ontology reuse. However, there is still no clear…

  8. Developing Learning Materials Using an Ontology of Mathematical Logic

    Science.gov (United States)

    Boyatt, Russell; Joy, Mike

    2012-01-01

    Ontologies describe a body of knowledge and give formal structure to a domain by describing concepts and their relationships. The construction of an ontology provides an opportunity to develop a shared understanding and a consistent vocabulary to be used for a given activity. This paper describes the construction of an ontology for an area of…

  9. Unsupervised Ontology Generation from Unstructured Text. CRESST Report 827

    Science.gov (United States)

    Mousavi, Hamid; Kerr, Deirdre; Iseli, Markus R.

    2013-01-01

    Ontologies are a vital component of most knowledge acquisition systems, and recently there has been a huge demand for generating ontologies automatically since manual or supervised techniques are not scalable. In this paper, we introduce "OntoMiner", a rule-based, iterative method to extract and populate ontologies from unstructured or…

  10. Ontology-Based Method for Fault Diagnosis of Loaders.

    Science.gov (United States)

    Xu, Feixiang; Liu, Xinhui; Chen, Wei; Zhou, Chen; Cao, Bingwei

    2018-02-28

    This paper proposes an ontology-based fault diagnosis method which overcomes the difficulty of understanding complex fault diagnosis knowledge of loaders and offers a universal approach for fault diagnosis of all loaders. This method contains the following components: (1) An ontology-based fault diagnosis model is proposed to achieve the integrating, sharing and reusing of fault diagnosis knowledge for loaders; (2) combined with ontology, CBR (case-based reasoning) is introduced to realize effective and accurate fault diagnoses following four steps (feature selection, case-retrieval, case-matching and case-updating); and (3) in order to cover the shortages of the CBR method due to the lack of concerned cases, ontology based RBR (rule-based reasoning) is put forward through building SWRL (Semantic Web Rule Language) rules. An application program is also developed to implement the above methods to assist in finding the fault causes, fault locations and maintenance measures of loaders. In addition, the program is validated through analyzing a case study.

  11. Metadata and Ontologies in Learning Resources Design

    Science.gov (United States)

    Vidal C., Christian; Segura Navarrete, Alejandra; Menéndez D., Víctor; Zapata Gonzalez, Alfredo; Prieto M., Manuel

    Resource design and development requires knowledge about educational goals, instructional context and information about learner's characteristics among other. An important information source about this knowledge are metadata. However, metadata by themselves do not foresee all necessary information related to resource design. Here we argue the need to use different data and knowledge models to improve understanding the complex processes related to e-learning resources and their management. This paper presents the use of semantic web technologies, as ontologies, supporting the search and selection of resources used in design. Classification is done, based on instructional criteria derived from a knowledge acquisition process, using information provided by IEEE-LOM metadata standard. The knowledge obtained is represented in an ontology using OWL and SWRL. In this work we give evidence of the implementation of a Learning Object Classifier based on ontology. We demonstrate that the use of ontologies can support the design activities in e-learning.

  12. Ontologies and Information Systems: A Literature Survey

    Science.gov (United States)

    2011-06-01

    Falcon-AO (LMO + GMO ) [146], and RiMOM [317]. Meta-matching systems include APFEL [76] and eTuner [286]. There also exist frameworks that provide a set...Jian, N., Qu, Y. and Wang, Q. 2005. GMO : A graph matching for ontologies. In Proceedings of the K-CAPWorkshop on Integrating Ontologies, Banff

  13. An integrative model of knowledge management and team work

    Directory of Open Access Journals (Sweden)

    Juan A. Marin-Garcia

    2008-10-01

    Full Text Available Human Resource Management relevance in Knowledge Management has been studied in academic literature mostly from the point of view of recruitment, selection, wages and salaries and career development processes. We have found few publications that are focused in the behaviour of the group of people who generate, share and transfer that knowledge while working in a team. The aim of this paper is to propose a framework that describes the relation between knowledge management and team work,, integrating Nonaka and Takeuchi, Leonard- Barton and Heisig framework proposals, as well as to outline some reflexions for further researches.

  14. Fish Ontology framework for taxonomy-based fish recognition

    Science.gov (United States)

    Ali, Najib M.; Khan, Haris A.; Then, Amy Y-Hui; Ving Ching, Chong; Gaur, Manas

    2017-01-01

    Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO), an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users. PMID:28929028

  15. Fish Ontology framework for taxonomy-based fish recognition

    Directory of Open Access Journals (Sweden)

    Najib M. Ali

    2017-09-01

    Full Text Available Life science ontologies play an important role in Semantic Web. Given the diversity in fish species and the associated wealth of information, it is imperative to develop an ontology capable of linking and integrating this information in an automated fashion. As such, we introduce the Fish Ontology (FO, an automated classification architecture of existing fish taxa which provides taxonomic information on unknown fish based on metadata restrictions. It is designed to support knowledge discovery, provide semantic annotation of fish and fisheries resources, data integration, and information retrieval. Automated classification for unknown specimens is a unique feature that currently does not appear to exist in other known ontologies. Examples of automated classification for major groups of fish are demonstrated, showing the inferred information by introducing several restrictions at the species or specimen level. The current version of FO has 1,830 classes, includes widely used fisheries terminology, and models major aspects of fish taxonomy, grouping, and character. With more than 30,000 known fish species globally, the FO will be an indispensable tool for fish scientists and other interested users.

  16. Self-adaptation of Ontologies to Folksonomies in Semantic Web

    OpenAIRE

    Francisco Echarte; José Javier Astrain; Alberto Córdoba; Jesús Villadangos

    2008-01-01

    Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at...

  17. An Integrated Model for Effective Knowledge Management in Chinese Organizations

    Science.gov (United States)

    An, Xiaomi; Deng, Hepu; Wang, Yiwen; Chao, Lemen

    2013-01-01

    Purpose: The purpose of this paper is to provide organizations in the Chinese cultural context with a conceptual model for an integrated adoption of existing knowledge management (KM) methods and to improve the effectiveness of their KM activities. Design/methodology/approaches: A comparative analysis is conducted between China and the western…

  18. Integrating ICT in Agriculture for Knowledge-Based Economy | Balraj ...

    African Journals Online (AJOL)

    ... demands the integration of ICT knowledge with agriculture. Already projects such as Agriculture Management Information System (AMIS), and e-Soko (which means electronic marketing) – which provides farmers with the price decision making tools enlightens the path to socio-economic development through agriculture.

  19. Methodology to build medical ontology from textual resources.

    Science.gov (United States)

    Baneyx, Audrey; Charlet, Jean; Jaulent, Marie-Christine

    2006-01-01

    In the medical field, it is now established that the maintenance of unambiguous thesauri goes through ontologies. Our research task is to help pneumologists code acts and diagnoses with a software that represents medical knowledge through a domain ontology. In this paper, we describe our general methodology aimed at knowledge engineers in order to build various types of medical ontologies based on terminology extraction from texts. The hypothesis is to apply natural language processing tools to textual patient discharge summaries to develop the resources needed to build an ontology in pneumology. Results indicate that the joint use of distributional analysis and lexico-syntactic patterns performed satisfactorily for building such ontologies.

  20. Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob; Hohimer, Ryan E.; White, Amanda M.

    2006-06-06

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  1. Automating Ontological Annotation with WordNet

    Energy Technology Data Exchange (ETDEWEB)

    Sanfilippo, Antonio P.; Tratz, Stephen C.; Gregory, Michelle L.; Chappell, Alan R.; Whitney, Paul D.; Posse, Christian; Paulson, Patrick R.; Baddeley, Bob L.; Hohimer, Ryan E.; White, Amanda M.

    2006-01-22

    Semantic Web applications require robust and accurate annotation tools that are capable of automating the assignment of ontological classes to words in naturally occurring text (ontological annotation). Most current ontologies do not include rich lexical databases and are therefore not easily integrated with word sense disambiguation algorithms that are needed to automate ontological annotation. WordNet provides a potentially ideal solution to this problem as it offers a highly structured lexical conceptual representation that has been extensively used to develop word sense disambiguation algorithms. However, WordNet has not been designed as an ontology, and while it can be easily turned into one, the result of doing this would present users with serious practical limitations due to the great number of concepts (synonym sets) it contains. Moreover, mapping WordNet to an existing ontology may be difficult and requires substantial labor. We propose to overcome these limitations by developing an analytical platform that (1) provides a WordNet-based ontology offering a manageable and yet comprehensive set of concept classes, (2) leverages the lexical richness of WordNet to give an extensive characterization of concept class in terms of lexical instances, and (3) integrates a class recognition algorithm that automates the assignment of concept classes to words in naturally occurring text. The ensuing framework makes available an ontological annotation platform that can be effectively integrated with intelligence analysis systems to facilitate evidence marshaling and sustain the creation and validation of inference models.

  2. Language and embodied consciousness: A Peircean ontological ...

    African Journals Online (AJOL)

    An ontology of language: its source and place in First Language ... knowledge they supposedly gain in school with their immediate environment and their lived .... looking stick in space looks bent at the point it enters the medium of water.

  3. Semantic similarity between ontologies at different scales

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Qingpeng; Haglin, David J.

    2016-04-01

    In the past decade, existing and new knowledge and datasets has been encoded in different ontologies for semantic web and biomedical research. The size of ontologies is often very large in terms of number of concepts and relationships, which makes the analysis of ontologies and the represented knowledge graph computational and time consuming. As the ontologies of various semantic web and biomedical applications usually show explicit hierarchical structures, it is interesting to explore the trade-offs between ontological scales and preservation/precision of results when we analyze ontologies. This paper presents the first effort of examining the capability of this idea via studying the relationship between scaling biomedical ontologies at different levels and the semantic similarity values. We evaluate the semantic similarity between three Gene Ontology slims (Plant, Yeast, and Candida, among which the latter two belong to the same kingdom—Fungi) using four popular measures commonly applied to biomedical ontologies (Resnik, Lin, Jiang-Conrath, and SimRel). The results of this study demonstrate that with proper selection of scaling levels and similarity measures, we can significantly reduce the size of ontologies without losing substantial detail. In particular, the performance of Jiang-Conrath and Lin are more reliable and stable than that of the other two in this experiment, as proven by (a) consistently showing that Yeast and Candida are more similar (as compared to Plant) at different scales, and (b) small deviations of the similarity values after excluding a majority of nodes from several lower scales. This study provides a deeper understanding of the application of semantic similarity to biomedical ontologies, and shed light on how to choose appropriate semantic similarity measures for biomedical engineering.

  4. A semantic web framework to integrate cancer omics data with biological knowledge.

    Science.gov (United States)

    Holford, Matthew E; McCusker, James P; Cheung, Kei-Hoi; Krauthammer, Michael

    2012-01-25

    The RDF triple provides a simple linguistic means of describing limitless types of information. Triples can be flexibly combined into a unified data source we call a semantic model. Semantic models open new possibilities for the integration of variegated biological data. We use Semantic Web technology to explicate high throughput clinical data in the context of fundamental biological knowledge. We have extended Corvus, a data warehouse which provides a uniform interface to various forms of Omics data, by providing a SPARQL endpoint. With the querying and reasoning tools made possible by the Semantic Web, we were able to explore quantitative semantic models retrieved from Corvus in the light of systematic biological knowledge. For this paper, we merged semantic models containing genomic, transcriptomic and epigenomic data from melanoma samples with two semantic models of functional data - one containing Gene Ontology (GO) data, the other, regulatory networks constructed from transcription factor binding information. These two semantic models were created in an ad hoc manner but support a common interface for integration with the quantitative semantic models. Such combined semantic models allow us to pose significant translational medicine questions. Here, we study the interplay between a cell's molecular state and its response to anti-cancer therapy by exploring the resistance of cancer cells to Decitabine, a demethylating agent. We were able to generate a testable hypothesis to explain how Decitabine fights cancer - namely, that it targets apoptosis-related gene promoters predominantly in Decitabine-sensitive cell lines, thus conveying its cytotoxic effect by activating the apoptosis pathway. Our research provides a framework whereby similar hypotheses can be developed easily.

  5. Applications of the ACGT Master Ontology on Cancer

    OpenAIRE

    Brochhausen, Mathias; Weiler, Gabriele; Martín Martín, Luis; Cocos, Cristian; Stenzhorn, Holger; Graf, Norbert; Dörr, Martin; Tsiknakis, Manolis; Smith, Barry

    2008-01-01

    In this paper we present applications of the ACGT Master Ontology (MO) which is a new terminology resource for a transnational network providing data exchange in oncology, emphasizing the integration of both clinical and molecular data. The development of a new ontology was necessary due to problems with existing biomedical ontologies in oncology. The ACGT MO is a test case for the application of best practices in ontology development. This paper provides an overview of the application of the...

  6. Laevo: A Temporal Desktop Interface for Integrated Knowledge Work

    DEFF Research Database (Denmark)

    Jeuris, Steven; Houben, Steven; Bardram, Jakob

    2014-01-01

    Prior studies show that knowledge work is characterized by highly interlinked practices, including task, file and window management. However, existing personal information management tools primarily focus on a limited subset of knowledge work, forcing users to perform additional manual...... states and transitions of an activity. The life cycle is used to inform the design of Laevo, a temporal activity-centric desktop interface for personal knowledge work. Laevo allows users to structure work within dedicated workspaces, managed on a timeline. Through a centralized notification system which...... configuration work to integrate the different tools they use. In order to understand tool usage, we review literature on how users' activities are created and evolve over time as part of knowledge worker practices. From this we derive the activity life cycle, a conceptual framework describing the different...

  7. Challenges and promises of integrating knowledge engineering and qualitative methods

    Science.gov (United States)

    Lundberg, C. Gustav; Holm, Gunilla

    Our goal is to expose some of the close ties that exist between knowledge engineering (KE) and qualitative methodology (QM). Many key concepts of qualitative research, for example meaning, commonsense, understanding, and everyday life, overlap with central research concerns in artificial intelligence. These shared interests constitute a largely unexplored avenue for interdisciplinary cooperation. We compare and take some steps toward integrating two historically diverse methodologies by exploring the commonalities of KE and QM both from a substantive and a methodological/technical perspective. In the second part of this essay, we address knowledge acquisition problems and procedures. Knowledge acquisition within KE has been based primarily on cognitive psychology/science foundations, whereas knowledge acquisition within QM has a broader foundation in phenomenology, symbolic interactionism, and ethnomethodology. Our discussion and examples are interdisciplinary in nature. We do not suggest that there is a clash between the KE and QM frameworks, but rather that the lack of communication potentially may limit each framework's future development.

  8. Computational neuroanatomy: ontology-based representation of neural components and connectivity.

    Science.gov (United States)

    Rubin, Daniel L; Talos, Ion-Florin; Halle, Michael; Musen, Mark A; Kikinis, Ron

    2009-02-05

    A critical challenge in neuroscience is organizing, managing, and accessing the explosion in neuroscientific knowledge, particularly anatomic knowledge. We believe that explicit knowledge-based approaches to make neuroscientific knowledge computationally accessible will be helpful in tackling this challenge and will enable a variety of applications exploiting this knowledge, such as surgical planning. We developed ontology-based models of neuroanatomy to enable symbolic lookup, logical inference and mathematical modeling of neural systems. We built a prototype model of the motor system that integrates descriptive anatomic and qualitative functional neuroanatomical knowledge. In addition to modeling normal neuroanatomy, our approach provides an explicit representation of abnormal neural connectivity in disease states, such as common movement disorders. The ontology-based representation encodes both structural and functional aspects of neuroanatomy. The ontology-based models can be evaluated computationally, enabling development of automated computer reasoning applications. Neuroanatomical knowledge can be represented in machine-accessible format using ontologies. Computational neuroanatomical approaches such as described in this work could become a key tool in translational informatics, leading to decision support applications that inform and guide surgical planning and personalized care for neurological disease in the future.

  9. Predicting protein-protein interactions in Arabidopsis thaliana through integration of orthology, gene ontology and co-expression

    Directory of Open Access Journals (Sweden)

    Vandepoele Klaas

    2009-06-01

    Full Text Available Abstract Background Large-scale identification of the interrelationships between different components of the cell, such as the interactions between proteins, has recently gained great interest. However, unraveling large-scale protein-protein interaction maps is laborious and expensive. Moreover, assessing the reliability of the interactions can be cumbersome. Results In this study, we have developed a computational method that exploits the existing knowledge on protein-protein interactions in diverse species through orthologous relations on the one hand, and functional association data on the other hand to predict and filter protein-protein interactions in Arabidopsis thaliana. A highly reliable set of protein-protein interactions is predicted through this integrative approach making use of existing protein-protein interaction data from yeast, human, C. elegans and D. melanogaster. Localization, biological process, and co-expression data are used as powerful indicators for protein-protein interactions. The functional repertoire of the identified interactome reveals interactions between proteins functioning in well-conserved as well as plant-specific biological processes. We observe that although common mechanisms (e.g. actin polymerization and components (e.g. ARPs, actin-related proteins exist between different lineages, they are active in specific processes such as growth, cancer metastasis and trichome development in yeast, human and Arabidopsis, respectively. Conclusion We conclude that the integration of orthology with functional association data is adequate to predict protein-protein interactions. Through this approach, a high number of novel protein-protein interactions with diverse biological roles is discovered. Overall, we have predicted a reliable set of protein-protein interactions suitable for further computational as well as experimental analyses.

  10. Community-based participatory research and integrated knowledge translation: advancing the co-creation of knowledge.

    Science.gov (United States)

    Jull, Janet; Giles, Audrey; Graham, Ian D

    2017-12-19

    Better use of research evidence (one form of "knowledge") in health systems requires partnerships between researchers and those who contend with the real-world needs and constraints of health systems. Community-based participatory research (CBPR) and integrated knowledge translation (IKT) are research approaches that emphasize the importance of creating partnerships between researchers and the people for whom the research is ultimately meant to be of use ("knowledge users"). There exist poor understandings of the ways in which these approaches converge and diverge. Better understanding of the similarities and differences between CBPR and IKT will enable researchers to use these approaches appropriately and to leverage best practices and knowledge from each. The co-creation of knowledge conveys promise of significant social impacts, and further understandings of how to engage and involve knowledge users in research are needed. We examine the histories and traditions of CBPR and IKT, as well as their points of convergence and divergence. We critically evaluate the ways in which both have the potential to contribute to the development and integration of knowledge in health systems. As distinct research traditions, the underlying drivers and rationale for CBPR and IKT have similarities and differences across the areas of motivation, social location, and ethics; nevertheless, the practices of CBPR and IKT converge upon a common aim: the co-creation of knowledge that is the result of knowledge user and researcher expertise. We argue that while CBPR and IKT both have the potential to contribute evidence to implementation science and practices for collaborative research, clarity for the purpose of the research-social change or application-is a critical feature in the selection of an appropriate collaborative approach to build knowledge. CBPR and IKT bring distinct strengths to a common aim: to foster democratic processes in the co-creation of knowledge. As research

  11. Integrated learning: Ways of fostering the applicability of teachers’ pedagogical and psychological knowledge

    Directory of Open Access Journals (Sweden)

    Nora eHarr

    2015-06-01

    Full Text Available In teacher education, general pedagogical and psychological knowledge is often taught separately from the teaching subject itself, potentially leading to inert knowledge. In an experimental study with 69 mathematics student teachers, we tested the benefits of fostering the integration of pedagogical content knowledge and general pedagogical and psychological knowledge with respect to knowledge application. Integration was fostered either by integrating the contents or by prompting the learners to integrate separately-taught knowledge. Fostering integration, as compared to a separate presentation without integration help, led to more applicable pedagogical and psychological knowledge and greater simultaneous application of pedagogical and psychological knowledge and pedagogical content knowledge. The advantages of fostering knowledge integration were not moderated by the student teachers’ prior knowledge or working memory capacity. A disadvantage of integrating different knowledge types referred to increased learning times.

  12. Science Teachers’ Pedagogical Content Knowledge and Integrated Approach

    Science.gov (United States)

    Adi Putra, M. J.; Widodo, A.; Sopandi, W.

    2017-09-01

    The integrated approach refers to the stages of pupils’ psychological development. Unfortunately, the competences which are designed into the curriculum is not appropriate with the child development. This Manuscript presents PCK (pedagogical content knowledge) of teachers who teach science content utilizing an integrated approach. The data has been collected by using CoRe, PaP-eR, and interviews from six elementary teachers who teach science. The paper informs that high and stable teacher PCKs have an impact on how teachers present integrated teaching. Because it is influenced by the selection of important content that must be submitted to the students, the depth of the content, the reasons for choosing the teaching procedures and some other things. So for teachers to be able to integrate teaching, they should have a balanced PCK.

  13. Integrated knowledge base tool for acquisition and verification of NPP alarm systems

    International Nuclear Information System (INIS)

    Park, Joo Hyun; Seong, Poong Hyun

    1998-01-01

    Knowledge acquisition and knowledge base verification are important activities in developing knowledge-based systems such as alarm processing systems. In this work, we developed the integrated tool, for knowledge acquisition and verification of NPP alarm processing systems, by using G2 tool. The tool integrates document analysis method and ECPN matrix analysis method, for knowledge acquisition and knowledge verification, respectively. This tool enables knowledge engineers to perform their tasks from knowledge acquisition to knowledge verification consistently

  14. LKIF Core: principled ontology development for the legal domain

    NARCIS (Netherlands)

    Hoekstra, R.; Breuker, J.; Di Bello, M.; Boer, A.; Breuker, J.; Casanovas, P.; Klein, M.C.A.; Francesconi, E.

    2009-01-01

    In this paper we describe a legal core ontology that is part of the Legal Knowledge Interchange Format: a knowledge representation formalism that enables the translation of legal knowledge bases written in different representation formats and formalisms. A legal (core) ontology can play an important

  15. A Hydrological Sensor Web Ontology Based on the SSN Ontology: A Case Study for a Flood

    Directory of Open Access Journals (Sweden)

    Chao Wang

    2017-12-01

    Full Text Available Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains.

  16. Complex Topographic Feature Ontology Patterns

    Science.gov (United States)

    Varanka, Dalia E.; Jerris, Thomas J.

    2015-01-01

    Semantic ontologies are examined as effective data models for the representation of complex topographic feature types. Complex feature types are viewed as integrated relations between basic features for a basic purpose. In the context of topographic science, such component assemblages are supported by resource systems and found on the local landscape. Ontologies are organized within six thematic modules of a domain ontology called Topography that includes within its sphere basic feature types, resource systems, and landscape types. Context is constructed not only as a spatial and temporal setting, but a setting also based on environmental processes. Types of spatial relations that exist between components include location, generative processes, and description. An example is offered in a complex feature type ‘mine.’ The identification and extraction of complex feature types are an area for future research.

  17. Spatial cyberinfrastructures, ontologies, and the humanities.

    Science.gov (United States)

    Sieber, Renee E; Wellen, Christopher C; Jin, Yuan

    2011-04-05

    We report on research into building a cyberinfrastructure for Chinese biographical and geographic data. Our cyberinfrastructure contains (i) the McGill-Harvard-Yenching Library Ming Qing Women's Writings database (MQWW), the only online database on historical Chinese women's writings, (ii) the China Biographical Database, the authority for Chinese historical people, and (iii) the China Historical Geographical Information System, one of the first historical geographic information systems. Key to this integration is that linked databases retain separate identities as bases of knowledge, while they possess sufficient semantic interoperability to allow for multidatabase concepts and to support cross-database queries on an ad hoc basis. Computational ontologies create underlying semantics for database access. This paper focuses on the spatial component in a humanities cyberinfrastructure, which includes issues of conflicting data, heterogeneous data models, disambiguation, and geographic scale. First, we describe the methodology for integrating the databases. Then we detail the system architecture, which includes a tier of ontologies and schema. We describe the user interface and applications that allow for cross-database queries. For instance, users should be able to analyze the data, examine hypotheses on spatial and temporal relationships, and generate historical maps with datasets from MQWW for research, teaching, and publication on Chinese women writers, their familial relations, publishing venues, and the literary and social communities. Last, we discuss the social side of cyberinfrastructure development, as people are considered to be as critical as the technical components for its success.

  18. Spatial cyberinfrastructures, ontologies, and the humanities

    Science.gov (United States)

    Sieber, Renee E.; Wellen, Christopher C.; Jin, Yuan

    2011-01-01

    We report on research into building a cyberinfrastructure for Chinese biographical and geographic data. Our cyberinfrastructure contains (i) the McGill-Harvard-Yenching Library Ming Qing Women's Writings database (MQWW), the only online database on historical Chinese women's writings, (ii) the China Biographical Database, the authority for Chinese historical people, and (iii) the China Historical Geographical Information System, one of the first historical geographic information systems. Key to this integration is that linked databases retain separate identities as bases of knowledge, while they possess sufficient semantic interoperability to allow for multidatabase concepts and to support cross-database queries on an ad hoc basis. Computational ontologies create underlying semantics for database access. This paper focuses on the spatial component in a humanities cyberinfrastructure, which includes issues of conflicting data, heterogeneous data models, disambiguation, and geographic scale. First, we describe the methodology for integrating the databases. Then we detail the system architecture, which includes a tier of ontologies and schema. We describe the user interface and applications that allow for cross-database queries. For instance, users should be able to analyze the data, examine hypotheses on spatial and temporal relationships, and generate historical maps with datasets from MQWW for research, teaching, and publication on Chinese women writers, their familial relations, publishing venues, and the literary and social communities. Last, we discuss the social side of cyberinfrastructure development, as people are considered to be as critical as the technical components for its success. PMID:21444819

  19. Combining Archetypes, Ontologies and Formalization Enables Automated Computation of Quality Indicators.

    Science.gov (United States)

    Legaz-García, María Del Carmen; Dentler, Kathrin; Fernández-Breis, Jesualdo Tomás; Cornet, Ronald

    2017-01-01

    ArchMS is a framework that represents clinical information and knowledge using ontologies in OWL, which facilitates semantic interoperability and thereby the exploitation and secondary use of clinical data. However, it does not yet support the automated assessment of quality of care. CLIF is a stepwise method to formalize quality indicators. The method has been implemented in the CLIF tool which supports its users in generating computable queries based on a patient data model which can be based on archetypes. To enable the automated computation of quality indicators using ontologies and archetypes, we tested whether ArchMS and the CLIF tool can be integrated. We successfully automated the process of generating SPARQL queries from quality indicators that have been formalized with CLIF and integrated them into ArchMS. Hence, ontologies and archetypes can be combined for the execution of formalized quality indicators.

  20. Enabling collaboration on semiformal mathematical knowledge by semantic web integration

    CERN Document Server

    Lange, C

    2011-01-01

    Mathematics is becoming increasingly collaborative, but software does not sufficiently support that: Social Web applications do not currently make mathematical knowledge accessible to automated agents that have a deeper understanding of mathematical structures. Such agents exist but focus on individual research tasks, such as authoring, publishing, peer-review, or verification, instead of complex collaboration workflows. This work effectively enables their integration by bridging the document-oriented perspective of mathematical authoring and publishing, and the network perspective of threaded

  1. Human Processing of Knowledge from Texts: Acquisition, Integration, and Reasoning

    Science.gov (United States)

    1979-06-01

    comprehension. Norwood, N.J.: Ablex, 1977. Craik , F.I.M., and Lockhart , R. S. Levels of processing : for memory research. Journal of Verbal Learning A...Table 5.9 presents summary data regarding the performance levels and memory and search processes of individual subjects. The first row in Table 5.9...R-2256-ARP A June 1979 ARPA Order No.: 189-1 9020 Cybernetics Technology Human Processing of Knowledge from Texts: Acquisition, Integration, and

  2. Knowledge Management tools integration within DLR's concurrent engineering facility

    Science.gov (United States)

    Lopez, R. P.; Soragavi, G.; Deshmukh, M.; Ludtke, D.

    The complexity of space endeavors has increased the need for Knowledge Management (KM) tools. The concept of KM involves not only the electronic storage of knowledge, but also the process of making this knowledge available, reusable and traceable. Establishing a KM concept within the Concurrent Engineering Facility (CEF) has been a research topic of the German Aerospace Centre (DLR). This paper presents the current KM tools of the CEF: the Software Platform for Organizing and Capturing Knowledge (S.P.O.C.K.), the data model Virtual Satellite (VirSat), and the Simulation Model Library (SimMoLib), and how their usage improved the Concurrent Engineering (CE) process. This paper also exposes the lessons learned from the introduction of KM practices into the CEF and elaborates a roadmap for the further development of KM in CE activities at DLR. The results of the application of the Knowledge Management tools have shown the potential of merging the three software platforms with their functionalities, as the next step towards the fully integration of KM practices into the CE process. VirSat will stay as the main software platform used within a CE study, and S.P.O.C.K. and SimMoLib will be integrated into VirSat. These tools will support the data model as a reference and documentation source, and as an access to simulation and calculation models. The use of KM tools in the CEF aims to become a basic practice during the CE process. The settlement of this practice will result in a much more extended knowledge and experience exchange within the Concurrent Engineering environment and, consequently, the outcome of the studies will comprise higher quality in the design of space systems.

  3. Geo-Ontologies Are Scale Dependent

    Science.gov (United States)

    Frank, A. U.

    2009-04-01

    Philosophers aim at a single ontology that describes "how the world is"; for information systems we aim only at ontologies that describe a conceptualization of reality (Guarino 1995; Gruber 2005). A conceptualization of the world implies a spatial and temporal scale: what are the phenomena, the objects and the speed of their change? Few articles (Reitsma et al. 2003) seem to address that an ontology is scale specific (but many articles indicate that ontologies are scale-free in another sense namely that they are scale free in the link densities between concepts). The scale in the conceptualization can be linked to the observation process. The extent of the support of the physical observation instrument and the sampling theorem indicate what level of detail we find in a dataset. These rules apply for remote sensing or sensor networks alike. An ontology of observations must include scale or level of detail, and concepts derived from observations should carry this relation forward. A simple example: in high resolution remote sensing image agricultural plots and roads between them are shown, at lower resolution, only the plots and not the roads are visible. This gives two ontologies, one with plots and roads, the other with plots only. Note that a neighborhood relation in the two different ontologies also yield different results. References Gruber, T. (2005). "TagOntology - a way to agree on the semantics of tagging data." Retrieved October 29, 2005., from http://tomgruber.org/writing/tagontology-tagcapm-talk.pdf. Guarino, N. (1995). "Formal Ontology, Conceptual Analysis and Knowledge Representation." International Journal of Human and Computer Studies. Special Issue on Formal Ontology, Conceptual Analysis and Knowledge Representation, edited by N. Guarino and R. Poli 43(5/6). Reitsma, F. and T. Bittner (2003). Process, Hierarchy, and Scale. Spatial Information Theory. Cognitive and Computational Foundations of Geographic Information ScienceInternational Conference

  4. Nuclear component design ontology building based on ASME codes

    International Nuclear Information System (INIS)

    Bao Shiyi; Zhou Yu; He Shuyan

    2005-01-01

    The adoption of ontology analysis in the study of concept knowledge acquisition and representation for the nuclear component design process based on computer-supported cooperative work (CSCW) makes it possible to share and reuse numerous concept knowledge of multi-disciplinary domains. A practical ontology building method is accordingly proposed based on Protege knowledge model in combination with both top-down and bottom-up approaches together with Formal Concept Analysis (FCA). FCA exhibits its advantages in the way it helps establish and improve taxonomic hierarchy of concepts and resolve concept conflict occurred in modeling multi-disciplinary domains. With Protege-3.0 as the ontology building tool, a nuclear component design ontology based ASME codes is developed by utilizing the ontology building method. The ontology serves as the basis to realize concept knowledge sharing and reusing of nuclear component design. (authors)

  5. Integrating Ecological and Social Knowledge: Learning from CHANS Research

    Directory of Open Access Journals (Sweden)

    Bruce Shindler

    2017-03-01

    Full Text Available Scientists are increasingly called upon to integrate across ecological and social disciplines to tackle complex coupled human and natural system (CHANS problems. Integration of these disciplines is challenging and many scientists do not have experience with large integrated research projects. However, much can be learned about the complicated process of integration from such efforts. We document some of these lessons from a National Science Foundation-funded CHANS project (Forests, People, Fire and present considerations for developing and engaging in coupled human and natural system projects. Certainly we are not the first to undertake this endeavor, and many of our findings complement those of other research teams. We focus here on the process of coming together, learning to work as an integrated science team, and describe the challenges and opportunities of engaging stakeholders (agency personnel and citizen communities of interests in our efforts. Throughout this project our intention was to foster dialogue among diverse interests and, thus, incorporate this knowledge into uncovering primary social and ecological drivers of change. A primary tool was an agent-based model, Envision, that used this information in landscape simulation, visualization models, and scenario development. Although integration can be an end in itself, the proof of value in the approach can be the degree to which it provides new insights or tools to CHANS, including closer interaction among multiple stakeholders, that could not have been reached without it.

  6. DMTO: a realistic ontology for standard diabetes mellitus treatment.

    Science.gov (United States)

    El-Sappagh, Shaker; Kwak, Daehan; Ali, Farman; Kwak, Kyung-Sup

    2018-02-06

    Treatment of type 2 diabetes mellitus (T2DM) is a complex problem. A clinical decision support system (CDSS) based on massive and distributed electronic health record data can facilitate the automation of this process and enhance its accuracy. The most important component of any CDSS is its knowledge base. This knowledge base can be formulated using ontologies. The formal description logic of ontology supports the inference of hidden knowledge. Building a complete, coherent, consistent, interoperable, and sharable ontology is a challenge. This paper introduces the first version of the newly constructed Diabetes Mellitus Treatment Ontology (DMTO) as a basis for shared-semantics, domain-specific, standard, machine-readable, and interoperable knowledge relevant to T2DM treatment. It is a comprehensive ontology and provides the highest coverage and the most complete picture of coded knowledge about T2DM patients' current conditions, previous profiles, and T2DM-related aspects, including complications, symptoms, lab tests, interactions, treatment plan (TP) frameworks, and glucose-related diseases and medications. It adheres to the design principles recommended by the Open Biomedical Ontologies Foundry and is based on ontological realism that follows the principles of the Basic Formal Ontology and the Ontology for General Medical Science. DMTO is implemented under Protégé 5.0 in Web Ontology Language (OWL) 2 format and is publicly available through the National Center for Biomedical Ontology's BioPortal at http://bioportal.bioontology.org/ontologies/DMTO . The current version of DMTO includes more than 10,700 classes, 277 relations, 39,425 annotations, 214 semantic rules, and 62,974 axioms. We provide proof of concept for this approach to modeling TPs. The ontology is able to collect and analyze most features of T2DM as well as customize chronic TPs with the most appropriate drugs, foods, and physical exercises. DMTO is ready to be used as a knowledge base for

  7. Assessment Applications of Ontologies.

    Science.gov (United States)

    Chung, Gregory K. W. K.; Niemi, David; Bewley, William L.

    This paper discusses the use of ontologies and their applications to assessment. An ontology provides a shared and common understanding of a domain that can be communicated among people and computational systems. The ontology captures one or more experts' conceptual representation of a domain expressed in terms of concepts and the relationships…

  8. Integrating ethnobiological knowledge into biodiversity conservation in the Eastern Himalayas.

    Science.gov (United States)

    O'Neill, Alexander R; Badola, Hemant K; Dhyani, Pitamber P; Rana, Santosh K

    2017-03-29

    Biocultural knowledge provides valuable insight into ecological processes, and can guide conservation practitioners in local contexts. In many regions, however, such knowledge is underutilized due to its often-fragmented record in disparate sources. In this article, we review and apply ethnobiological knowledge to biodiversity conservation in the Eastern Himalayas. Using Sikkim, India as a case study, we: (i) traced the history and trends of ethnobiological documentation; (ii) identified priority species and habitat types; and, (iii) analyzed within and among community differences pertaining to species use and management. Our results revealed that Sikkim is a biocultural hotspot, where six ethnic communities and 1128 species engage in biocultural relationships. Since the mid-1800s, the number of ethnobiological publications from Sikkim has exponentially increased; however, our results also indicate that much of this knowledge is both unwritten and partitioned within an aging, gendered, and caste or ethnic group-specific stratum of society. Reviewed species were primarily wild or wild cultivated, native to subtropical and temperate forests, and pend IUCN Red List of Threatened Species assessment. Our results demonstrate the value of engaging local knowledge holders as active participants in conservation, and suggest the need for further ethnobiological research in the Eastern Himalayas. Our interdisciplinary approach, which included rank indices and geospatial modelling, can help integrate diverse datasets into evidence-based policy.

  9. An Ontology for Musical Phonographic Records: Contributing with a Representation Model

    Science.gov (United States)

    de Oliveira Albuquerque, Marcelo; Siqueira, Sean Wolfgand M.; de Saldanha da G. Lanzelotte, Rosana; Braz, Maria Helena L. B.

    Music is a complex domain with some interesting specificities that makes it difficult to be modeled. If different types of music are considered, then the difficulties are even bigger. This paper presents some of the characteristics that makes music such a hard domain to model and proposes an ontology for representing musical phonographic records. This ontology will provide a global representation that can be used to support systems interoperability and data integration, which provides disseminating music worldwide, contributing to culture in the knowledge society.

  10. Ontology-based multi-agent systems

    Energy Technology Data Exchange (ETDEWEB)

    Hadzic, Maja; Wongthongtham, Pornpit; Dillon, Tharam; Chang, Elizabeth [Digital Ecosystems and Business Intelligence Institute, Perth, WA (Australia)

    2009-07-01

    The Semantic web has given a great deal of impetus to the development of ontologies and multi-agent systems. Several books have appeared which discuss the development of ontologies or of multi-agent systems separately on their own. The growing interaction between agents and ontologies has highlighted the need for integrated development of these. This book is unique in being the first to provide an integrated treatment of the modeling, design and implementation of such combined ontology/multi-agent systems. It provides clear exposition of this integrated modeling and design methodology. It further illustrates this with two detailed case studies in (a) the biomedical area and (b) the software engineering area. The book is, therefore, of interest to researchers, graduate students and practitioners in the semantic web and web science area. (orig.)

  11. Informatics in radiology: radiology gamuts ontology: differential diagnosis for the Semantic Web.

    Science.gov (United States)

    Budovec, Joseph J; Lam, Cesar A; Kahn, Charles E

    2014-01-01

    The Semantic Web is an effort to add semantics, or "meaning," to empower automated searching and processing of Web-based information. The overarching goal of the Semantic Web is to enable users to more easily find, share, and combine information. Critical to this vision are knowledge models called ontologies, which define a set of concepts and formalize the relations between them. Ontologies have been developed to manage and exploit the large and rapidly growing volume of information in biomedical domains. In diagnostic radiology, lists of differential diagnoses of imaging observations, called gamuts, provide an important source of knowledge. The Radiology Gamuts Ontology (RGO) is a formal knowledge model of differential diagnoses in radiology that includes 1674 differential diagnoses, 19,017 terms, and 52,976 links between terms. Its knowledge is used to provide an interactive, freely available online reference of radiology gamuts ( www.gamuts.net ). A Web service allows its content to be discovered and consumed by other information systems. The RGO integrates radiologic knowledge with other biomedical ontologies as part of the Semantic Web. © RSNA, 2014.

  12. Ontologies vs. Classification Systems

    DEFF Research Database (Denmark)

    Madsen, Bodil Nistrup; Erdman Thomsen, Hanne

    2009-01-01

    What is an ontology compared to a classification system? Is a taxonomy a kind of classification system or a kind of ontology? These are questions that we meet when working with people from industry and public authorities, who need methods and tools for concept clarification, for developing meta...... data sets or for obtaining advanced search facilities. In this paper we will present an attempt at answering these questions. We will give a presentation of various types of ontologies and briefly introduce terminological ontologies. Furthermore we will argue that classification systems, e.g. product...... classification systems and meta data taxonomies, should be based on ontologies....

  13. Building a semi-automatic ontology learning and construction system for geosciences

    Science.gov (United States)

    Babaie, H. A.; Sunderraman, R.; Zhu, Y.

    2013-12-01

    We are developing an ontology learning and construction framework that allows continuous, semi-automatic knowledge extraction, verification, validation, and maintenance by potentially a very large group of collaborating domain experts in any geosciences field. The system brings geoscientists from the side-lines to the center stage of ontology building, allowing them to collaboratively construct and enrich new ontologies, and merge, align, and integrate existing ontologies and tools. These constantly evolving ontologies can more effectively address community's interests, purposes, tools, and change. The goal is to minimize the cost and time of building ontologies, and maximize the quality, usability, and adoption of ontologies by the community. Our system will be a domain-independent ontology learning framework that applies natural language processing, allowing users to enter their ontology in a semi-structured form, and a combined Semantic Web and Social Web approach that lets direct participation of geoscientists who have no skill in the design and development of their domain ontologies. A controlled natural language (CNL) interface and an integrated authoring and editing tool automatically convert syntactically correct CNL text into formal OWL constructs. The WebProtege-based system will allow a potentially large group of geoscientists, from multiple domains, to crowd source and participate in the structuring of their knowledge model by sharing their knowledge through critiquing, testing, verifying, adopting, and updating of the concept models (ontologies). We will use cloud storage for all data and knowledge base components of the system, such as users, domain ontologies, discussion forums, and semantic wikis that can be accessed and queried by geoscientists in each domain. We will use NoSQL databases such as MongoDB as a service in the cloud environment. MongoDB uses the lightweight JSON format, which makes it convenient and easy to build Web applications using

  14. Knowledge integration in One Health policy formulation, implementation and evaluation.

    Science.gov (United States)

    Hitziger, Martin; Esposito, Roberto; Canali, Massimo; Aragrande, Maurizio; Häsler, Barbara; Rüegg, Simon R

    2018-03-01

    The One Health concept covers the interrelationship between human, animal and environmental health and requires multistakeholder collaboration across many cultural, disciplinary, institutional and sectoral boundaries. Yet, the implementation of the One Health approach appears hampered by shortcomings in the global framework for health governance. Knowledge integration approaches, at all stages of policy development, could help to address these shortcomings. The identification of key objectives, the resolving of trade-offs and the creation of a common vision and a common direction can be supported by multicriteria analyses. Evidence-based decision-making and transformation of observations into narratives detailing how situations emerge and might unfold in the future can be achieved by systems thinking. Finally, transdisciplinary approaches can be used both to improve the effectiveness of existing systems and to develop novel networks for collective action. To strengthen One Health governance, we propose that knowledge integration becomes a key feature of all stages in the development of related policies. We suggest several ways in which such integration could be promoted.

  15. NeOn Methodology for Building Ontology Networks: Specification, Scheduling and Reuse

    OpenAIRE

    Suárez-Figueroa, Mari Carmen

    2010-01-01

    A new ontology development paradigm has started; its emphasis lies on the reuse and possible subsequent reengineering of knowledge resources, on the collaborative and argumentative ontology development, and on the building of ontology networks; this new trend is the opposite of building new ontologies from scratch. To help ontology developers in this new paradigm, it is important to provide strong methodological support. This thesis presents some contributions to the methodological area of...

  16. Knowledge Integration and Inter-Disciplinary Communication in Action Research

    Directory of Open Access Journals (Sweden)

    Hahn Heidi Ann

    2014-08-01

    Full Text Available In a plenary talk at WMSCI 2012 entitled "Planning for Action Research: Looking at Practice through a Different Lens," this author asserted that behavioral science practitioners, often "back into" action research – they start out doing a process improvement or intervention and discover something along the way, i.e., generalizable knowledge, that seems worthwhile to share with their community of practice. It was further asserted that, had the efforts been conceived of as research from the outset, the contributions to the body of knowledge would be more robust and the utility of the projects would improve as well. This paper continues on that theme. Action research and process improvement methods are briefly described and compared. A comparison of two Los Alamos National Laboratory engineering ethics training projects – one developed using a process improvement framework, the other using an action research framework – is put forth to provide evidence that use of a research "lens" can enhance behavioral science interventions and the knowledge that may result from them. The linkage between the Specifying Learning and Diagnosing stages of the Action Research Cycle provides one mechanism for integrating the knowledge gained into the product or process being studied and should provide a reinforcing loop that leads to continual improvement. The collaborative relationships among researchers and the individual, group, or organization that is the subject of the imp rovement op p ortunity (the "client", who are likely from very different backgrounds, and the interpretive epistemology that are among the hallmarks of action research also contribute to the quality of the knowledge gained. This paper closes with a discussion of how Inter-Disciplinary Communication is embedded within the action research paradigm and how this likely also enriches the knowledge gained.

  17. Developing integrated crop knowledge networks to advance candidate gene discovery.

    Science.gov (United States)

    Hassani-Pak, Keywan; Castellote, Martin; Esch, Maria; Hindle, Matthew; Lysenko, Artem; Taubert, Jan; Rawlings, Christopher

    2016-12-01

    The chances of raising crop productivity to enhance global food security would be greatly improved if we had a complete understanding of all the biological mechanisms that underpinned traits such as crop yield, disease resistance or nutrient and water use efficiency. With more crop genomes emerging all the time, we are nearer having the basic information, at the gene-level, to begin assembling crop gene catalogues and using data from other plant species to understand how the genes function and how their interactions govern crop development and physiology. Unfortunately, the task of creating such a complete knowledge base of gene functions, interaction networks and trait biology is technically challenging because the relevant data are dispersed in myriad databases in a variety of data formats with variable quality and coverage. In this paper we present a general approach for building genome-scale knowledge networks that provide a unified representation of heterogeneous but interconnected datasets to enable effective knowledge mining and gene discovery. We describe the datasets and outline the methods, workflows and tools that we have developed for creating and visualising these networks for the major crop species, wheat and barley. We present the global characteristics of such knowledge networks and with an example linking a seed size phenotype to a barley WRKY transcription factor orthologous to TTG2 from Arabidopsis, we illustrate the value of integrated data in biological knowledge discovery. The software we have developed (www.ondex.org) and the knowledge resources (http://knetminer.rothamsted.ac.uk) we have created are all open-source and provide a first step towards systematic and evidence-based gene discovery in order to facilitate crop improvement.

  18. Toxicology ontology perspectives.

    Science.gov (United States)

    Hardy, Barry; Apic, Gordana; Carthew, Philip; Clark, Dominic; Cook, David; Dix, Ian; Escher, Sylvia; Hastings, Janna; Heard, David J; Jeliazkova, Nina; Judson, Philip; Matis-Mitchell, Sherri; Mitic, Dragana; Myatt, Glenn; Shah, Imran; Spjuth, Ola; Tcheremenskaia, Olga; Toldo, Luca; Watson, David; White, Andrew; Yang, Chihae

    2012-01-01

    The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.

  19. New ways of integrating material knowledge into the design process

    DEFF Research Database (Denmark)

    Højris, Anders; Nielsen, Louise Møller

    2013-01-01

    – based on technical performance, no longer apply. Accordingly the approach in this paper is to view information and knowledge about materials through the perspective of organizational memory and technology brokering. This paper is build upon two cases from the German based design studio: designaffairs...... libraries and thereby access to information on new material possibilities has also changed the way designers integrate knowledge about materials into the design process. This means that the traditional design process model, where the selection of materials takes place after the design of form and function...... in order to help clients to find the right material among hundreds of samples. Furthermore a number of material libraries have also been developed into online database, which provides detailed information about new material and makes the information accessible from almost everywhere. The access to material...

  20. Cognition and Knowledge Sharing in Post-acquisition Integration

    DEFF Research Database (Denmark)

    Jaura, Manya; Michailova, Snejina

    2014-01-01

    conducted with ten respondents in four Indian IT companies that have acquired firms abroad. Findings: The authors find evidence for supporting the negative effect of in- and out-groups differentiation and the positive effect of interpersonal interaction on knowledge sharing among employees of the acquired...... of organisational objectives in a post-acquisition context. Managers should understand that the knowledge their employees possess is a strategic asset, and therefore how they use it is influential in attaining organisational goals in general, and acquisition integration objectives in particular. The creation...... of task- and project-related communities or groups can help in establishing a shared organisational identity, especially after the turbulent event of one company acquiring another one. The creation of communities or groups where socialisation is encouraged can lead to employees interacting with one...

  1. An Ontology for Learning Services on the Shop Floor

    Science.gov (United States)

    Ullrich, Carsten

    2016-01-01

    An ontology expresses a common understanding of a domain that serves as a basis of communication between people or systems, and enables knowledge sharing, reuse of domain knowledge, reasoning and thus problem solving. In Technology-Enhanced Learning, especially in Intelligent Tutoring Systems and Adaptive Learning Environments, ontologies serve as…

  2. The Volcanism Ontology (VO): a model of the volcanic system

    Science.gov (United States)

    Myer, J.; Babaie, H. A.

    2017-12-01

    We have modeled a part of the complex material and process entities and properties of the volcanic system in the Volcanism Ontology (VO) applying several top-level ontologies such as Basic Formal Ontology (BFO), SWEET, and Ontology of Physics for Biology (OPB) within a single framework. The continuant concepts in BFO describe features with instances that persist as wholes through time and have qualities (attributes) that may change (e.g., state, composition, and location). In VO, the continuants include lava, volcanic rock, and volcano. The occurrent concepts in BFO include processes, their temporal boundaries, and the spatio-temporal regions within which they occur. In VO, these include eruption (process), the onset of pyroclastic flow (temporal boundary), and the space and time span of the crystallization of lava in a lava tube (spatio-temporal region). These processes can be of physical (e.g., debris flow, crystallization, injection), atmospheric (e.g., vapor emission, ash particles blocking solar radiation), hydrological (e.g., diffusion of water vapor, hot spring), thermal (e.g., cooling of lava) and other types. The properties (predicates) relate continuants to other continuants, occurrents to continuants, and occurrents to occurrents. The ontology also models other concepts such as laboratory and field procedures by volcanologists, sampling by sensors, and the type of instruments applied in monitoring volcanic activity. When deployed on the web, VO will be used to explicitly and formally annotate data and information collected by volcanologists based on domain knowledge. This will enable the integration of global volcanic data and improve the interoperability of software that deal with such data.

  3. Match & Manage : The use of knowledge matching and project management to integrate knowledge in collaborative inbound open innovation

    OpenAIRE

    Lakemond, Nicolette; Bengtsson, Lars; Laursen, Keld; Tell, Fredrik

    2016-01-01

    Despite mounting evidence on the potential benefits of inbound open innovation, little is known about how firms purposefully manage inflows of knowledge. We investigate the use of two knowledge governance procedures—project management and knowledge matching—in collaborative inbound open innovation. Our findings suggest that, in addition to “knowledge-precursors,” which the literature on open innovation and absorptive capacity has shown to be important for the integration of external knowledge...

  4. Integrating data to acquire new knowledge: Three modes of integration in plant science.

    Science.gov (United States)

    Leonelli, Sabina

    2013-12-01

    This paper discusses what it means and what it takes to integrate data in order to acquire new knowledge about biological entities and processes. Maureen O'Malley and Orkun Soyer have pointed to the scientific work involved in data integration as important and distinct from the work required by other forms of integration, such as methodological and explanatory integration, which have been more successful in captivating the attention of philosophers of science. Here I explore what data integration involves in more detail and with a focus on the role of data-sharing tools, like online databases, in facilitating this process; and I point to the philosophical implications of focusing on data as a unit of analysis. I then analyse three cases of data integration in the field of plant science, each of which highlights a different mode of integration: (1) inter-level integration, which involves data documenting different features of the same species, aims to acquire an interdisciplinary understanding of organisms as complex wholes and is exemplified by research on Arabidopsis thaliana; (2) cross-species integration, which involves data acquired on different species, aims to understand plant biology in all its different manifestations and is exemplified by research on Miscanthus giganteus; and (3) translational integration, which involves data acquired from sources within as well as outside academia, aims at the provision of interventions to improve human health (e.g. by sustaining the environment in which humans thrive) and is exemplified by research on Phytophtora ramorum. Recognising the differences between these efforts sheds light on the dynamics and diverse outcomes of data dissemination and integrative research; and the relations between the social and institutional roles of science, the development of data-sharing infrastructures and the production of scientific knowledge. Copyright © 2013 Elsevier Ltd. All rights reserved.

  5. Design and Evaluation of a Bacterial Clinical Infectious Diseases Ontology

    Science.gov (United States)

    Gordon, Claire L.; Pouch, Stephanie; Cowell, Lindsay G.; Boland, Mary Regina; Platt, Heather L.; Goldfain, Albert; Weng, Chunhua

    2013-01-01

    With antimicrobial resistance increasing worldwide, there is a great need to use automated antimicrobial decision support systems (ADSSs) to lower antimicrobial resistance rates by promoting appropriate antimicrobial use. However, they are infrequently used mostly because of their poor interoperability with different health information technologies. Ontologies can augment portable ADSSs by providing an explicit knowledge representation for biomedical entities and their relationships, helping to standardize and integrate heterogeneous data resources. We developed a bacterial clinical infectious diseases ontology (BCIDO) using Protégé-OWL. BCIDO defines a controlled terminology for clinical infectious diseases along with domain knowledge commonly used in hospital settings for clinical infectious disease treatment decision-making. BCIDO has 599 classes and 2355 object properties. Terms were imported from or mapped to Systematized Nomenclature of Medicine, Unified Medical Language System, RxNorm and National Center for Bitechnology Information Organismal Classification where possible. Domain expert evaluation using the “laddering” technique, ontology visualization, and clinical notes and scenarios, confirmed the correctness and potential usefulness of BCIDO. PMID:24551353

  6. Supporting students' knowledge integration with technology-enhanced inquiry curricula

    Science.gov (United States)

    Chiu, Jennifer Lopseen

    Dynamic visualizations of scientific phenomena have the potential to transform how students learn and understand science. Dynamic visualizations enable interaction and experimentation with unobservable atomic-level phenomena. A series of studies clarify the conditions under which embedding dynamic visualizations in technology-enhanced inquiry instruction can help students develop robust and durable chemistry knowledge. Using the knowledge integration perspective, I designed Chemical Reactions, a technology-enhanced curriculum unit, with a partnership of teachers, educational researchers, and chemists. This unit guides students in an exploration of how energy and chemical reactions relate to climate change. It uses powerful dynamic visualizations to connect atomic level interactions to the accumulation of greenhouse gases. The series of studies were conducted in typical classrooms in eleven high schools across the country. This dissertation describes four studies that contribute to understanding of how visualizations can be used to transform chemistry learning. The efficacy study investigated the impact of the Chemical Reactions unit compared to traditional instruction using pre-, post- and delayed posttest assessments. The self-monitoring study used self-ratings in combination with embedded assessments to explore how explanation prompts help students learn from dynamic visualizations. The self-regulation study used log files of students' interactions with the learning environment to investigate how external feedback and explanation prompts influence students' exploration of dynamic visualizations. The explanation study compared specific and general explanation prompts to explore the processes by which explanations benefit learning with dynamic visualizations. These studies delineate the conditions under which dynamic visualizations embedded in inquiry instruction can enhance student outcomes. The studies reveal that visualizations can be deceptively clear

  7. Assembly and integration of geo-scientific knowledge and arguments

    International Nuclear Information System (INIS)

    Gierszewki, P.; Gautschi, A.; Nguyen, T.S.; Laaksohaju, M.; Rohlig, K.J.; Peake, T.; Peltier, R.; Pitkanen, P.; Skagius Elert, K.; Sykes, J.F.

    2007-01-01

    The purpose of this working group was to consider the assembly and integration of geo-scientific knowledge and arguments. In an introductory presentation, K. Skagius Elert presented 'Assessment of Uncertainty and Confidence in Site Descriptive Models Experience from the On-going Site Investigation Programme in Sweden'. The detailed description of concepts and procedures established at SKB for the development of a Site Descriptive Model (SDM) provided a starting point for the discussion of the working group. The SDM components and the procedures to achieve them were used as 'references' for the discussion of comparable elements in other national programmes. The observations have been placed into two broad themes: 1. How to manage the integration? 2. How to handle uncertainties? No specific prescription was identified for either of these questions; rather a range of suggestions were noted based on experience. The appropriate solution will depend on the organisation, the site, the state of the programme, and other factors. A final observation from the working group was on the handling of evolution of the site with time. This topic incorporates aspects of both site integration and uncertainty management. Specifically, the integrated site description model (SDM) noted above represents a description of the site as it presently exists. This description takes into account the site history, but does not describe its evolution. The latter involves a number of uncertainties. This time evolution of the site can be described through Scenarios. The definition of scenarios, similar to the definition of the SDM, is an integrated and multidisciplinary process in order to ensure a self-consistent description. It will involve use of common assumptions. Since it involves the future and the associated uncertainties, it can be useful to draw on expert panels to help define the key assumptions and outlines for scenarios. (authors)

  8. Elements for an Ontology of Care in the Field of Artificial Intelligence.

    Science.gov (United States)

    González Aguña, Alexandra; Fernández Batalla, Marta; Cercas Duque, Adriana; Herrero Jaén, Sara; Monsalvo San Macario, Enrique; Jiménez Rodríguez, Ma Lourdes; Santamaría García, José Ma; Ramírez Sánchez, Sylvia Claudine; Vialart Vidal, Niurka; Condor Camara, Daniel Flavio

    2018-01-01

    An ontology of care is a formal, explicit specification of a shared conceptualization. Constructing an ontology is a process that requires four elements: knowledge object, subject that knows, knowledge operation and result. These elements configure theframework to generate ontologies that can be used in Artificial Intelligence systems for care.

  9. Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

    Science.gov (United States)

    Agapito, Giuseppe; Milano, Marianna; Guzzi, Pietro Hiram; Cannataro, Mario

    2016-01-01

    Gene Ontology (GO) is a structured repository of concepts (GO Terms) that are associated to one or more gene products through a process referred to as annotation. The analysis of annotated data is an important opportunity for bioinformatics. There are different approaches of analysis, among those, the use of association rules (AR) which provides useful knowledge, discovering biologically relevant associations between terms of GO, not previously known. In a previous work, we introduced GO-WAR (Gene Ontology-based Weighted Association Rules), a methodology for extracting weighted association rules from ontology-based annotated datasets. We here adapt the GO-WAR algorithm to mine cross-ontology association rules, i.e., rules that involve GO terms present in the three sub-ontologies of GO. We conduct a deep performance evaluation of GO-WAR by mining publicly available GO annotated datasets, showing how GO-WAR outperforms current state of the art approaches.

  10. OpenTox predictive toxicology framework: toxicological ontology and semantic media wiki-based OpenToxipedia.

    Science.gov (United States)

    Tcheremenskaia, Olga; Benigni, Romualdo; Nikolova, Ivelina; Jeliazkova, Nina; Escher, Sylvia E; Batke, Monika; Baier, Thomas; Poroikov, Vladimir; Lagunin, Alexey; Rautenberg, Micha; Hardy, Barry

    2012-04-24

    The OpenTox Framework, developed by the partners in the OpenTox project (http://www.opentox.org), aims at providing a unified access to toxicity data, predictive models and validation procedures. Interoperability of resources is achieved using a common information model, based on the OpenTox ontologies, describing predictive algorithms, models and toxicity data. As toxicological data may come from different, heterogeneous sources, a deployed ontology, unifying the terminology and the resources, is critical for the rational and reliable organization of the data, and its automatic processing. The following related ontologies have been developed for OpenTox: a) Toxicological ontology - listing the toxicological endpoints; b) Organs system and Effects ontology - addressing organs, targets/examinations and effects observed in in vivo studies; c) ToxML ontology - representing semi-automatic conversion of the ToxML schema; d) OpenTox ontology- representation of OpenTox framework components: chemical compounds, datasets, types of algorithms, models and validation web services; e) ToxLink-ToxCast assays ontology and f) OpenToxipedia community knowledge resource on toxicology terminology.OpenTox components are made available through standardized REST web services, where every compound, data set, and predictive method has a unique resolvable address (URI), used to retrieve its Resource Description Framework (RDF) representation, or to initiate the associated calculations and generate new RDF-based resources.The services support the integration of toxicity and chemical data from various sources, the generation and validation of computer models for toxic effects, seamless integration of new algorithms and scientifically sound validation routines and provide a flexible framework, which allows building arbitrary number of applications, tailored to solving different problems by end users (e.g. toxicologists). The OpenTox toxicological ontology projects may be accessed via the Open

  11. An integrated system for interactive continuous learning of categorical knowledge

    Science.gov (United States)

    Skočaj, Danijel; Vrečko, Alen; Mahnič, Marko; Janíček, Miroslav; Kruijff, Geert-Jan M.; Hanheide, Marc; Hawes, Nick; Wyatt, Jeremy L.; Keller, Thomas; Zhou, Kai; Zillich, Michael; Kristan, Matej

    2016-09-01

    This article presents an integrated robot system capable of interactive learning in dialogue with a human. Such a system needs to have several competencies and must be able to process different types of representations. In this article, we describe a collection of mechanisms that enable integration of heterogeneous competencies in a principled way. Central to our design is the creation of beliefs from visual and linguistic information, and the use of these beliefs for planning system behaviour to satisfy internal drives. The system is able to detect gaps in its knowledge and to plan and execute actions that provide information needed to fill these gaps. We propose a hierarchy of mechanisms which are capable of engaging in different kinds of learning interactions, e.g. those initiated by a tutor or by the system itself. We present the theory these mechanisms are build upon and an instantiation of this theory in the form of an integrated robot system. We demonstrate the operation of the system in the case of learning conceptual models of objects and their visual properties.

  12. Use artificial neural network to align biological ontologies.

    Science.gov (United States)

    Huang, Jingshan; Dang, Jiangbo; Huhns, Michael N; Zheng, W Jim

    2008-09-16

    Being formal, declarative knowledge representation models, ontologies help to address the problem of imprecise terminologies in biological and biomedical research. However, ontologies constructed under the auspices of the Open Biomedical Ontologies (OBO) group have exhibited a great deal of variety, because different parties can design ontologies according to their own conceptual views of the world. It is therefore becoming critical to align ontologies from different parties. During automated/semi-automated alignment across biological ontologies, different semantic aspects, i.e., concept name, concept properties, and concept relationships, contribute in different degrees to alignment results. Therefore, a vector of weights must be assigned to these semantic aspects. It is not trivial to determine what those weights should be, and current methodologies depend a lot on human heuristics. In this paper, we take an artificial neural network approach to learn and adjust these weights, and thereby support a new ontology alignment algorithm, customized for biological ontologies, with the purpose of avoiding some disadvantages in both rule-based and learning-based aligning algorithms. This approach has been evaluated by aligning two real-world biological ontologies, whose features include huge file size, very few instances, concept names in numerical strings, and others. The promising experiment results verify our proposed hypothesis, i.e., three weights for semantic aspects learned from a subset of concepts are representative of all concepts in the same ontology. Therefore, our method represents a large leap forward towards automating biological ontology alignment.

  13. An ontology for Autism Spectrum Disorder (ASD) to infer ASD phenotypes from Autism Diagnostic Interview-Revised data.

    Science.gov (United States)

    Mugzach, Omri; Peleg, Mor; Bagley, Steven C; Guter, Stephen J; Cook, Edwin H; Altman, Russ B

    2015-08-01

    Our goal is to create an ontology that will allow data integration and reasoning with subject data to classify subjects, and based on this classification, to infer new knowledge on Autism Spectrum Disorder (ASD) and related neurodevelopmental disorders (NDD). We take a first step toward this goal by extending an existing autism ontology to allow automatic inference of ASD phenotypes and Diagnostic & Statistical Manual of Mental Disorders (DSM) criteria based on subjects' Autism Diagnostic Interview-Revised (ADI-R) assessment data. Knowledge regarding diagnostic instruments, ASD phenotypes and risk factors was added to augment an existing autism ontology via Ontology Web Language class definitions and semantic web rules. We developed a custom Protégé plugin for enumerating combinatorial OWL axioms to support the many-to-many relations of ADI-R items to diagnostic categories in the DSM. We utilized a reasoner to infer whether 2642 subjects, whose data was obtained from the Simons Foundation Autism Research Initiative, meet DSM-IV-TR (DSM-IV) and DSM-5 diagnostic criteria based on their ADI-R data. We extended the ontology by adding 443 classes and 632 rules that represent phenotypes, along with their synonyms, environmental risk factors, and frequency of comorbidities. Applying the rules on the data set showed that the method produced accurate results: the true positive and true negative rates for inferring autistic disorder diagnosis according to DSM-IV criteria were 1 and 0.065, respectively; the true positive rate for inferring ASD based on DSM-5 criteria was 0.94. The ontology allows automatic inference of subjects' disease phenotypes and diagnosis with high accuracy. The ontology may benefit future studies by serving as a knowledge base for ASD. In addition, by adding knowledge of related NDDs, commonalities and differences in manifestations and risk factors could be automatically inferred, contributing to the understanding of ASD pathophysiology. Copyright

  14. Ontology Enabled Generation of Embedded Web Services

    DEFF Research Database (Denmark)

    Hansen, Klaus Marius; Zhang, Weishan; Soares, Goncalo Teofilo Afonso Pinheiro

    2008-01-01

    Web services are increasingly adopted as a service provision mechanism in pervasive computing environments. Implementing web services on networked, embedded devices raises a number of challenges, for example efficiency of web services, handling of variability and dependencies of hardware...... and software platforms, and of devices state and context changes. To address these challenges, we developed a Web service compiler, Limbo, in which Web Ontology Language (OWL) ontologies are used to make the Limbo compiler aware of its compilation context, such as targeted hardware and software. At the same...... time, knowledge on device details, platform dependencies, and resource/power consumption is built into the supporting ontologies, which are used to configure Limbo for generating resource efficient web service code. A state machine ontology is used to generate stub code to facilitate handling of state...

  15. Ontologies and Epistemologies to Achieve Knowledge in Sor Juana Ines de la Cruz’s Poem «Primero Sueño»

    Directory of Open Access Journals (Sweden)

    Lydia Deni Gamboa López

    2017-11-01

    Full Text Available In this article, I propose reading one section of sor Juana Inés de la Cruz’s poem «Primero Sueño» as a philosophical reflexion about the discussion between realists and nominalists, on the one hand, and as a reflexion about the preferable based realist/nominalist methodology on the other hand. The realist perspective presented in this poem has a Platonic-Augustinian character. The nominalist perspective —an ontology which sor Juana seems to have preferred— has an Ockhamist vein.

  16. AN ONTOLOGY-BASED COMPETENCE MANAGEMENT SYSTEM FOR IT COMPANIES

    OpenAIRE

    Cristina NICULESCU; Stefan TRAUSAN-MATU

    2009-01-01

    The paper presents a generic framework of an intelligent information system for competence management based on ontologies for information technology companies. The advantage of using an ontology-based system is the possibility of the identification of new relations among concepts based on inferences starting from the existing knowledge. The inferences may be performed in our approach by a reasoning engine, using classifiers in the Descriptions Logics tab associated with the Protégé ontology e...

  17. A MAUT APPROACH FOR REUSING DOMAIN ONTOLOGIES ON THE BASIS OF THE NeOn METHODOLOGY

    OpenAIRE

    A. JIMÉNEZ; M. C. SUÁREZ-FIGUEROA; A. MATEOS; A. GÓMEZ-PÉREZ; M. FERNÁNDEZ-LÓPEZ

    2013-01-01

    Knowledge resource reuse is becoming a widespread approach in the ontology engineering field because it can speed up the ontology development process. In this context, the NeOn Methodology specifies some guidelines for reusing different types of knowledge resources (ontologies, nonontological resources, and ontology design patterns). These guidelines prescribe how to perform the different activities involved in any of the diverse types of reuse processes. One such activity is to select the be...

  18. Semantic web for integrated network analysis in biomedicine.

    Science.gov (United States)

    Chen, Huajun; Ding, Li; Wu, Zhaohui; Yu, Tong; Dhanapalan, Lavanya; Chen, Jake Y

    2009-03-01

    The Semantic Web technology enables integration of heterogeneous data on the World Wide Web by making the semantics of data explicit through formal ontologies. In this article, we survey the feasibility and state of the art of utilizing the Semantic Web technology to represent, integrate and analyze the knowledge in various biomedical networks. We introduce a new conceptual framework, semantic graph mining, to enable researchers to integrate graph mining with ontology reasoning in network data analysis. Through four case studies, we demonstrate how semantic graph mining can be applied to the analysis of disease-causal genes, Gene Ontology category cross-talks, drug efficacy analysis and herb-drug interactions analysis.

  19. Ontology modeling for generation of clinical pathways

    Directory of Open Access Journals (Sweden)

    Jasmine Tehrani

    2012-12-01

    Full Text Available Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the

  20. Desiderata for ontologies to be used in semantic annotation of biomedical documents.

    Science.gov (United States)

    Bada, Michael; Hunter, Lawrence

    2011-02-01

    A wealth of knowledge valuable to the translational research scientist is contained within the vast biomedical literature, but this knowledge is typically in the form of natural language. Sophisticated natural-language-processing systems are needed to translate text into unambiguous formal representations grounded in high-quality consensus ontologies, and these systems in turn rely on gold-standard corpora of annotated documents for training and testing. To this end, we are constructing the Colorado Richly Annotated Full-Text (CRAFT) Corpus, a collection of 97 full-text biomedical journal articles that are being manually annotated with the entire sets of terms from select vocabularies, predominantly from the Open Biomedical Ontologies (OBO) library. Our efforts in building this corpus has illuminated infelicities of these ontologies with respect to the semantic annotation of biomedical documents, and we propose desiderata whose implementation could substantially improve their utility in this task; these include the integration of overlapping terms across OBOs, the resolution of OBO-specific ambiguities, the integration of the BFO with the OBOs and the use of mid-level ontologies, the inclusion of noncanonical instances, and the expansion of relations and realizable entities. Copyright © 2010 Elsevier Inc. All rights reserved.

  1. Modularising ontology and designing inference patterns to personalise health condition assessment: the case of obesity.

    Science.gov (United States)

    Sojic, Aleksandra; Terkaj, Walter; Contini, Giorgia; Sacco, Marco

    2016-05-04

    The public health initiatives for obesity prevention are increasingly exploiting the advantages of smart technologies that can register various kinds of data related to physical, physiological, and behavioural conditions. Since individual features and habits vary among people, the design of appropriate intervention strategies for motivating changes in behavioural patterns towards a healthy lifestyle requires the interpretation and integration of collected information, while considering individual profiles in a personalised manner. The ontology-based modelling is recognised as a promising approach in facing the interoperability and integration of heterogeneous information related to characterisation of personal profiles. The presented ontology captures individual profiles across several obesity-related knowledge-domains structured into dedicated modules in order to support inference about health condition, physical features, behavioural habits associated with a person, and relevant changes over time. The modularisation strategy is designed to facilitate ontology development, maintenance, and reuse. The domain-specific modules formalised in the Web Ontology Language (OWL) integrate the domain-specific sets of rules formalised in the Semantic Web Rule Language (SWRL). The inference rules follow a modelling pattern designed to support personalised assessment of health condition as age- and gender-specific. The test cases exemplify a personalised assessment of the obesity-related health conditions for the population of teenagers. The paper addresses several issues concerning the modelling of normative concepts related to obesity and depicts how the public health concern impacts classification of teenagers according to their phenotypes. The modelling choices regarding the ontology-structure are explained in the context of the modelling goal to integrate multiple knowledge-domains and support reasoning about the individual changes over time. The presented modularisation

  2. Systematic integration of biomedical knowledge prioritizes drugs for repurposing.

    Science.gov (United States)

    Himmelstein, Daniel Scott; Lizee, Antoine; Hessler, Christine; Brueggeman, Leo; Chen, Sabrina L; Hadley, Dexter; Green, Ari; Khankhanian, Pouya; Baranzini, Sergio E

    2017-09-22

    The ability to computationally predict whether a compound treats a disease would improve the economy and success rate of drug approval. This study describes Project Rephetio to systematically model drug efficacy based on 755 existing treatments. First, we constructed Hetionet (neo4j.het.io), an integrative network encoding knowledge from millions of biomedical studies. Hetionet v1.0 consists of 47,031 nodes of 11 types and 2,250,197 relationships of 24 types. Data were integrated from 29 public resources to connect compounds, diseases, genes, anatomies, pathways, biological processes, molecular functions, cellular components, pharmacologic classes, side effects, and symptoms. Next, we identified network patterns that distinguish treatments from non-treatments. Then, we predicted the probability of treatment for 209,168 compound-disease pairs (het.io/repurpose). Our predictions validated on two external sets of treatment and provided pharmacological insights on epilepsy, suggesting they will help prioritize drug repurposing candidates. This study was entirely open and received realtime feedback from 40 community members.

  3. Toward a general ontology for digital forensic disciplines.

    Science.gov (United States)

    Karie, Nickson M; Venter, Hein S

    2014-09-01

    Ontologies are widely used in different disciplines as a technique for representing and reasoning about domain knowledge. However, despite the widespread ontology-related research activities and applications in different disciplines, the development of ontologies and ontology research activities is still wanting in digital forensics. This paper therefore presents the case for establishing an ontology for digital forensic disciplines. Such an ontology would enable better categorization of the digital forensic disciplines, as well as assist in the development of methodologies and specifications that can offer direction in different areas of digital forensics. This includes such areas as professional specialization, certifications, development of digital forensic tools, curricula, and educational materials. In addition, the ontology presented in this paper can be used, for example, to better organize the digital forensic domain knowledge and explicitly describe the discipline's semantics in a common way. Finally, this paper is meant to spark discussions and further research on an internationally agreed ontological distinction of the digital forensic disciplines. Digital forensic disciplines ontology is a novel approach toward organizing the digital forensic domain knowledge and constitutes the main contribution of this paper. © 2014 American Academy of Forensic Sciences.

  4. Knowledge representation and management: towards an integration of a semantic web in daily health practice.

    Science.gov (United States)

    Griffon, N; Charlet, J; Darmoni, Sj

    2013-01-01

    To summarize the best papers in the field of Knowledge Representation and Management (KRM). A synopsis of the four selected articles for the IMIA Yearbook 2013 KRM section is provided, as well as highlights of current KRM trends, in particular, of the semantic web in daily health practice. The manual selection was performed in three stages: first a set of 3,106 articles, then a second set of 86 articles followed by a third set of 15 articles, and finally the last set of four chosen articles. Among the four selected articles (see Table 1), one focuses on knowledge engineering to prevent adverse drug events; the objective of the second is to propose mappings between clinical archetypes and SNOMED CT in the context of clinical practice; the third presents an ontology to create a question-answering system; the fourth describes a biomonitoring network based on semantic web technologies. These four articles clearly indicate that the health semantic web has become a part of daily practice of health professionals since 2012. In the review of the second set of 86 articles, the same topics included in the previous IMIA yearbook remain active research fields: Knowledge extraction, automatic indexing, information retrieval, natural language processing, management of health terminologies and ontologies.

  5. Ontology-based representation and analysis of host-Brucella interactions.

    Science.gov (United States)

    Lin, Yu; Xiang, Zuoshuang; He, Yongqun

    2015-01-01

    Biomedical ontologies are representations of classes of entities in the biomedical domain and how these classes are related in computer- and human-interpretable formats. Ontologies support data standardization and exchange and provide a basis for computer-assisted automated reasoning. IDOBRU is an ontology in the domain of Brucella and brucellosis. Brucella is a Gram-negative intracellular bacterium that causes brucellosis, the most common zoonotic disease in the world. In this study, IDOBRU is used as a platform to model and analyze how the hosts, especially host macrophages, interact with virulent Brucella strains or live attenuated Brucella vaccine strains. Such a study allows us to better integrate and understand intricate Brucella pathogenesis and host immunity mechanisms. Different levels of host-Brucella interactions based on different host cell types and Brucella strains were first defined ontologically. Three important processes of virulent Brucella interacting with host macrophages were represented: Brucella entry into macrophage, intracellular trafficking, and intracellular replication. Two Brucella pathogenesis mechanisms were ontologically represented: Brucella Type IV secretion system that supports intracellular trafficking and replication, and Brucella erythritol metabolism that participates in Brucella intracellular survival and pathogenesis. The host cell death pathway is critical to the outcome of host-Brucella interactions. For better survival and replication, virulent Brucella prevents macrophage cell death. However, live attenuated B. abortus vaccine strain RB51 induces caspase-2-mediated proinflammatory cell death. Brucella-associated cell death processes are represented in IDOBRU. The gene and protein information of 432 manually annotated Brucella virulence factors were represented using the Ontology of Genes and Genomes (OGG) and Protein Ontology (PRO), respectively. Seven inference rules were defined to capture the knowledge of host

  6. The Impact of Organizational Knowledge Integrators on Cooperative R&D Projects

    DEFF Research Database (Denmark)

    Bulathsinhala, Nadika

    2014-01-01

    This paper addresses the fact that R&D projects that incorporate external knowledge sources not only depend on the number of sources, but also on integrating the right source. An organizational knowledge integrator has a natural interest due to its position in the value chain and the technology...... phase to pull the knowledge from earlier phases of development closer towards commercialization. The aim of the paper is to examine if organizational knowledge integrators in R&D projects have a positive impact on innovative performance compared to projects that do not involve a knowledge integrator...

  7. Using semantic distances for reasoning with inconsistent ontologies

    NARCIS (Netherlands)

    Huang, Zhisheng; van Harmelen, Frank

    2009-01-01

    Re-using and combining multiple ontologies on the Web is bound to lead to inconsistencies between the combined vocabularies. Even many of the ontologies that are in use today turn out to be inconsistent once some of their implicit knowledge is made explicit. However, robust and efficient methods to

  8. ExO: An Ontology for Exposure Science

    Science.gov (United States)

    An ontology is a formal representation of knowledge within a domain and typically consists of classes, the properties of those classes, and the relationships between them. Ontologies are critically important for specifying data of interest in a consistent manner, thereby enablin...

  9. Validating Domain Ontologies: A Methodology Exemplified for Concept Maps

    Science.gov (United States)

    Steiner, Christina M.; Albert, Dietrich

    2017-01-01

    Ontologies play an important role as knowledge domain representations in technology-enhanced learning and instruction. Represented in form of concept maps they are commonly used as teaching and learning material and have the potential to enhance positive educational outcomes. To ensure the effective use of an ontology representing a knowledge…

  10. The KNOMAD Methodology for Integration of Multi-Disciplinary Engineering Knowledge within Aerospace Production

    NARCIS (Netherlands)

    Curran, R.; Verhagen, W.J.C.; Van Tooren, M.J.L.

    2010-01-01

    The paper is associated with the integration of multi-disciplinary knowledge within a Knowledge Based Engineering (KBE)-enabled design framework. To support this integration effort, the KNOMAD methodology has been devised. KNOMAD stands for Knowledge Optimized Manufacture And Design and is a

  11. Models, methods and software for distributed knowledge acquisition for the automated construction of integrated expert systems knowledge bases

    International Nuclear Information System (INIS)

    Dejneko, A.O.

    2011-01-01

    Based on an analysis of existing models, methods and means of acquiring knowledge, a base method of automated knowledge acquisition has been chosen. On the base of this method, a new approach to integrate information acquired from knowledge sources of different typologies has been proposed, and the concept of a distributed knowledge acquisition with the aim of computerized formation of the most complete and consistent models of problem areas has been introduced. An original algorithm for distributed knowledge acquisition from databases, based on the construction of binary decision trees has been developed [ru

  12. Ontological foundations for evolutionary economics: A Darwinian social ontology

    NARCIS (Netherlands)

    Stoelhorst, J.W.

    2008-01-01

    The purpose of this paper is to further the project of generalized Darwinism by developing a social ontology on the basis of a combined commitment to ontological continuity and ontological commonality. Three issues that are central to the development of a social ontology are addressed: (1) the

  13. An ontology for major histocompatibility restriction.

    Science.gov (United States)

    Vita, Randi; Overton, James A; Seymour, Emily; Sidney, John; Kaufman, Jim; Tallmadge, Rebecca L; Ellis, Shirley; Hammond, John; Butcher, Geoff W; Sette, Alessandro; Peters, Bjoern

    2016-01-01

    MHC molecules are a highly diverse family of proteins that play a key role in cellular immune recognition. Over time, different techniques and terminologies have been developed to identify the specific type(s) of MHC molecule involved in a specific immune recognition context. No consistent nomenclature exists across different vertebrate species. To correctly represent MHC related data in The Immune Epitope Database (IEDB), we built upon a previously established MHC ontology and created an ontology to represent MHC molecules as they relate to immunological experiments. This ontology models MHC protein chains from 16 species, deals with different approaches used to identify MHC, such as direct sequencing verses serotyping, relates engineered MHC molecules to naturally occurring ones, connects genetic loci, alleles, protein chains and multi-chain proteins, and establishes evidence codes for MHC restriction. Where available, this work is based on existing ontologies from the OBO foundry. Overall, representing MHC molecules provides a challenging and practically important test case for ontology building, and could serve as an example of how to integrate other ontology building efforts into web resources.

  14. Using ontology network structure in text mining.

    Science.gov (United States)

    Berndt, Donald J; McCart, James A; Luther, Stephen L

    2010-11-13

    Statistical text mining treats documents as bags of words, with a focus on term frequencies within documents and across document collections. Unlike natural language processing (NLP) techniques that rely on an engineered vocabulary or a full-featured ontology, statistical approaches do not make use of domain-specific knowledge. The freedom from biases can be an advantage, but at the cost of ignoring potentially valuable knowledge. The approach proposed here investigates a hybrid strategy based on computing graph measures of term importance over an entire ontology and injecting the measures into the statistical text mining process. As a starting point, we adapt existing search engine algorithms such as PageRank and HITS to determine term importance within an ontology graph. The graph-theoretic approach is evaluated using a smoking data set from the i2b2 National Center for Biomedical Computing, cast as a simple binary classification task for categorizing smoking-related documents, demonstrating consistent improvements in accuracy.

  15. ``Force,'' ontology, and language

    Science.gov (United States)

    Brookes, David T.; Etkina, Eugenia

    2009-06-01

    We introduce a linguistic framework through which one can interpret systematically students’ understanding of and reasoning about force and motion. Some researchers have suggested that students have robust misconceptions or alternative frameworks grounded in everyday experience. Others have pointed out the inconsistency of students’ responses and presented a phenomenological explanation for what is observed, namely, knowledge in pieces. We wish to present a view that builds on and unifies aspects of this prior research. Our argument is that many students’ difficulties with force and motion are primarily due to a combination of linguistic and ontological difficulties. It is possible that students are primarily engaged in trying to define and categorize the meaning of the term “force” as spoken about by physicists. We found that this process of negotiation of meaning is remarkably similar to that engaged in by physicists in history. In this paper we will describe a study of the historical record that reveals an analogous process of meaning negotiation, spanning multiple centuries. Using methods from cognitive linguistics and systemic functional grammar, we will present an analysis of the force and motion literature, focusing on prior studies with interview data. We will then discuss the implications of our findings for physics instruction.

  16. Application of Ontologies for Big Earth Data

    Science.gov (United States)

    Huang, T.; Chang, G.; Armstrong, E. M.; Boening, C.

    2014-12-01

    Connected data is smarter data! Earth Science research infrastructure must do more than just being able to support temporal, geospatial discovery of satellite data. As the Earth Science data archives continue to expand across NASA data centers, the research communities are demanding smarter data services. A successful research infrastructure must be able to present researchers the complete picture, that is, datasets with linked citations, related interdisciplinary data, imageries, current events, social media discussions, and scientific data tools that are relevant to the particular dataset. The popular Semantic Web for Earth and Environmental Terminology (SWEET) ontologies is a collection of ontologies and concepts designed to improve discovery and application of Earth Science data. The SWEET ontologies collection was initially developed to capture the relationships between keywords in the NASA Global Change Master Directory (GCMD). Over the years this popular ontologies collection has expanded to cover over 200 ontologies and 6000 concepts to enable scalable classification of Earth system science concepts and Space science. This presentation discusses the semantic web technologies as the enabling technology for data-intensive science. We will discuss the application of the SWEET ontologies as a critical component in knowledge-driven research infrastructure for some of the recent projects, which include the DARPA Ontological System for Context Artifact and Resources (OSCAR), 2013 NASA ACCESS Virtual Quality Screening Service (VQSS), and the 2013 NASA Sea Level Change Portal (SLCP) projects. The presentation will also discuss the benefits in using semantic web technologies in developing research infrastructure for Big Earth Science Data in an attempt to "accommodate all domains and provide the necessary glue for information to be cross-linked, correlated, and discovered in a semantically rich manner." [1] [1] Savas Parastatidis: A platform for all that we know

  17. Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

    Science.gov (United States)

    Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

    2013-04-01

    In the last years, airborne Light Detection and Ranging (LiDAR) data proved to be a valuable information resource for a vast number of applications ranging from land cover mapping to individual surface feature extraction from complex urban environments. To extract information from LiDAR data, users apply prior knowledge. Unfortunately, there is no consistent initiative for structuring this knowledge into data models that can be shared and reused across different applications and domains. The absence of such models poses great challenges to data interpretation, data fusion and integration as well as information transferability. The intention of this work is to describe the design, development and deployment of an ontology-based system to classify buildings from airborne LiDAR data. The novelty of this approach consists of the development of a domain ontology that specifies explicitly the knowledge used to extract features from airborne LiDAR data. The overall goal of this approach is to investigate the possibility for classification of features of interest from LiDAR data by means of domain ontology. The proposed workflow is applied to the building extraction process for the region of "Biberach an der Riss" in South Germany. Strip-adjusted and georeferenced airborne LiDAR data is processed based on geometrical and radiometric signatures stored within the point cloud. Region-growing segmentation algorithms are applied and segmented regions are exported to the GeoJSON format. Subsequently, the data is imported into the ontology-based reasoning process used to automatically classify exported features of interest. Based on the ontology it becomes possible to define domain concepts, associated properties and relations. As a consequence, the resulting specific body of knowledge restricts possible interpretation variants. Moreover, ontologies are machinable and thus it is possible to run reasoning on top of them. Available reasoners (FACT++, JESS, Pellet) are used to check

  18. Pedagogically-Driven Ontology Network for Conceptualizing the e-Learning Assessment Domain

    Science.gov (United States)

    Romero, Lucila; North, Matthew; Gutiérrez, Milagros; Caliusco, Laura

    2015-01-01

    The use of ontologies as tools to guide the generation, organization and personalization of e-learning content, including e-assessment, has drawn attention of the researchers because ontologies can represent the knowledge of a given domain and researchers use the ontology to reason about it. Although the use of these semantic technologies tends to…

  19. LapOntoSPM: an ontology for laparoscopic surgeries and its application to surgical phase recognition.

    Science.gov (United States)

    Katić, Darko; Julliard, Chantal; Wekerle, Anna-Laura; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie; Jannin, Pierre; Gibaud, Bernard

    2015-09-01

    The rise of intraoperative information threatens to outpace our abilities to process it. Context-aware systems, filtering information to automatically adapt to the current needs of the surgeon, are necessary to fully profit from computerized surgery. To attain context awareness, representation of medical knowledge is crucial. However, most existing systems do not represent knowledge in a reusable way, hindering also reuse of data. Our purpose is therefore to make our computational models of medical knowledge sharable, extensible and interoperational with established knowledge representations in the form of the LapOntoSPM ontology. To show its usefulness, we apply it to situation interpretation, i.e., the recognition of surgical phases based on surgical activities. Considering best practices in ontology engineering and building on our ontology for laparoscopy, we formalized the workflow of laparoscopic adrenalectomies, cholecystectomies and pancreatic resections in the framework of OntoSPM, a new standard for surgical process models. Furthermore, we provide a rule-based situation interpretation algorithm based on SQWRL to recognize surgical phases using the ontology. The system was evaluated on ground-truth data from 19 manually annotated surgeries. The aim was to show that the phase recognition capabilities are equal to a specialized solution. The recognition rates of the new system were equal to the specialized one. However, the time needed to interpret a situation rose from 0.5 to 1.8 s on average which is still viable for practical application. We successfully integrated medical knowledge for laparoscopic surgeries into OntoSPM, facilitating knowledge and data sharing. This is especially important for reproducibility of results and unbiased comparison of recognition algorithms. The associated recognition algorithm was adapted to the new representation without any loss of classification power. The work is an important step to standardized knowledge and data

  20. Integration of asynchronous knowledge sources in a novel speech recognition framework

    OpenAIRE

    Van hamme, Hugo

    2008-01-01

    Van hamme H., ''Integration of asynchronous knowledge sources in a novel speech recognition framework'', Proceedings ITRW on speech analysis and processing for knowledge discovery, 4 pp., June 2008, Aalborg, Denmark.

  1. An integration architecture for knowledge management system and business process management system

    NARCIS (Netherlands)

    Jung, J.; Choi, I.; Song, M.S.

    2007-01-01

    Recently, interests in the notion of process-oriented knowledge management (PKM) from academia and industry have been significantly increased. Comprehensive research and development requirements along with a cogent framework, however, have not been proposed for integrating knowledge management (KM)

  2. Interestingness measures and strategies for mining multi-ontology multi-level association rules from gene ontology annotations for the discovery of new GO relationships.

    Science.gov (United States)

    Manda, Prashanti; McCarthy, Fiona; Bridges, Susan M

    2013-10-01

    The Gene Ontology (GO), a set of three sub-ontologies, is one of the most popular bio-ontologies used for describing gene product characteristics. GO annotation data containing terms from multiple sub-ontologies and at different levels in the ontologies is an important source of implicit relationships between terms from the three sub-ontologies. Data mining techniques such as association rule mining that are tailored to mine from multiple ontologies at multiple levels of abstraction are required for effective knowledge discovery from GO annotation data. We present a data mining approach, Multi-ontology data mining at All Levels (MOAL) that uses the structure and relationships of the GO to mine multi-ontology multi-level association rules. We introduce two interestingness measures: Multi-ontology Support (MOSupport) and Multi-ontology Confidence (MOConfidence) customized to evaluate multi-ontology multi-level association rules. We also describe a variety of post-processing strategies for pruning uninteresting rules. We use publicly available GO annotation data to demonstrate our methods with respect to two applications (1) the discovery of co-annotation suggestions and (2) the discovery of new cross-ontology relationships. Copyright © 2013 The Authors. Published by Elsevier Inc. All rights reserved.

  3. Integrating Relational Reasoning and Knowledge Revision during Reading

    Science.gov (United States)

    Kendeou, Panayiota; Butterfuss, Reese; Van Boekel, Martin; O'Brien, Edward J.

    2017-01-01

    Our goal in this theoretical contribution is to connect research on knowledge revision and relational reasoning. To achieve this goal, first, we review the "knowledge revision components framework" (KReC) that provides an account of knowledge revision processes, specifically as they unfold during reading of texts. Second, we review a…

  4. Development and Evaluation of an Ontology for Guiding Appropriate Antibiotic Prescribing

    Science.gov (United States)

    Furuya, E. Yoko; Kuperman, Gilad J.; Cimino, James J.; Bakken, Suzanne

    2011-01-01

    Objectives To develop and apply formal ontology creation methods to the domain of antimicrobial prescribing and to formally evaluate the resulting ontology through intrinsic and extrinsic evaluation studies. Methods We extended existing ontology development methods to create the ontology and implemented the ontology using Protégé-OWL. Correctness of the ontology was assessed using a set of ontology design principles and domain expert review via the laddering technique. We created three artifacts to support the extrinsic evaluation (set of prescribing rules, alerts and an ontology-driven alert module, and a patient database) and evaluated the usefulness of the ontology for performing knowledge management tasks to maintain the ontology and for generating alerts to guide antibiotic prescribing. Results The ontology includes 199 classes, 10 properties, and 1,636 description logic restrictions. Twenty-three Semantic Web Rule Language rules were written to generate three prescribing alerts: 1) antibiotic-microorganism mismatch alert; 2) medication-allergy alert; and 3) non-recommended empiric antibiotic therapy alert. The evaluation studies confirmed the correctness of the ontology, usefulness of the ontology for representing and maintaining antimicrobial treatment knowledge rules, and usefulness of the ontology for generating alerts to provide feedback to clinicians during antibiotic prescribing. Conclusions This study contributes to the understanding of ontology development and evaluation methods and addresses one knowledge gap related to using ontologies as a clinical decision support system component—a need for formal ontology evaluation methods to measure their quality from the perspective of their intrinsic characteristics and their usefulness for specific tasks. PMID:22019377

  5. Data mining for ontology development.

    Energy Technology Data Exchange (ETDEWEB)

    Davidson, George S.; Strasburg, Jana (Pacific Northwest National Laboratory, Richland, WA); Stampf, David (Brookhaven National Laboratory, Upton, NY); Neymotin,Lev (Brookhaven National Laboratory, Upton, NY); Czajkowski, Carl (Brookhaven National Laboratory, Upton, NY); Shine, Eugene (Savannah River National Laboratory, Aiken, SC); Bollinger, James (Savannah River National Laboratory, Aiken, SC); Ghosh, Vinita (Brookhaven National Laboratory, Upton, NY); Sorokine, Alexandre (Oak Ridge National Laboratory, Oak Ridge, TN); Ferrell, Regina (Oak Ridge National Laboratory, Oak Ridge, TN); Ward, Richard (Oak Ridge National Laboratory, Oak Ridge, TN); Schoenwald, David Alan

    2010-06-01

    A multi-laboratory ontology construction effort during the summer and fall of 2009 prototyped an ontology for counterfeit semiconductor manufacturing. This effort included an ontology development team and an ontology validation methods team. Here the third team of the Ontology Project, the Data Analysis (DA) team reports on their approaches, the tools they used, and results for mining literature for terminology pertinent to counterfeit semiconductor manufacturing. A discussion of the value of ontology-based analysis is presented, with insights drawn from other ontology-based methods regularly used in the analysis of genomic experiments. Finally, suggestions for future work are offered.

  6. War of ontology worlds: mathematics, computer code, or Esperanto?

    Science.gov (United States)

    Rzhetsky, Andrey; Evans, James A

    2011-09-01

    The use of structured knowledge representations-ontologies and terminologies-has become standard in biomedicine. Definitions of ontologies vary widely, as do the values and philosophies that underlie them. In seeking to make these views explicit, we conducted and summarized interviews with a dozen leading ontologists. Their views clustered into three broad perspectives that we summarize as mathematics, computer code, and Esperanto. Ontology as mathematics puts the ultimate premium on rigor and logic, symmetry and consistency of representation across scientific subfields, and the inclusion of only established, non-contradictory knowledge. Ontology as computer code focuses on utility and cultivates diversity, fitting ontologies to their purpose. Like computer languages C++, Prolog, and HTML, the code perspective holds that diverse applications warrant custom designed ontologies. Ontology as Esperanto focuses on facilitating cross-disciplinary communication, knowledge cross-referencing, and computation across datasets from diverse communities. We show how these views align with classical divides in science and suggest how a synthesis of their concerns could strengthen the next generation of biomedical ontologies.

  7. Role of Ontologies for CPS Implementation in Manufacturing

    Directory of Open Access Journals (Sweden)

    Garetti Marco

    2015-12-01

    Full Text Available Cyber Physical Systems are an evolution of embedded systems featuring a tight combination of collaborating computational elements that control physical entities. CPSs promise a great potential of innovation in many areas including manufacturing and production. This is because we obtain a very powerful, flexible, modular infrastructure allowing easy (re configurability and fast ramp-up of manufacturing applications by building a manufacturing system with modular mechatronic components (for machining, transportation and storage and embedded intelligence, by integrating them into a system, through a network connection. However, when building such kind of architectures, the way to supply the needed domain knowledge to real manufacturing applications arises as a problem to solve. In fact, a CPS based architecture for manufacturing is made of smart but independent manufacturing components without any knowledge of the role they have to play together in the real world of manufacturing applications. Ontologies can supply such kind of knowledge, playing a very important role in CPS for manufacturing. The paper deals with this intriguing theme, also presenting an implementation of this approach in a research project for the open automation of manufacturing systems, in which the power of CPS is complemented by the support of an ontology of the manufacturing domain.

  8. Knowledge Sharing, Communities of Practice, and Learning Asset Integration - DAU's Major Initiatives

    National Research Council Canada - National Science Library

    Hickok, John

    2005-01-01

    .... What follows is an overview of Knowledge Sharing through the eyes of the Defense Acquisition University, along with some new initiatives called Learning Asset Integration and Workflow Learning...

  9. OWLing Clinical Data Repositories With the Ontology Web Language.

    Science.gov (United States)

    Lozano-Rubí, Raimundo; Pastor, Xavier; Lozano, Esther

    2014-08-01

    The health sciences are based upon information. Clinical information is usually stored and managed by physicians with precarious tools, such as spreadsheets. The biomedical domain is more complex than other domains that have adopted information and communication technologies as pervasive business tools. Moreover, medicine continuously changes its corpus of knowledge because of new discoveries and the rearrangements in the relationships among concepts. This scenario makes it especially difficult to offer good tools to answer the professional needs of researchers and constitutes a barrier that needs innovation to discover useful solutions. The objective was to design and implement a framework for the development of clinical data repositories, capable of facing the continuous change in the biomedicine domain and minimizing the technical knowledge required from final users. We combined knowledge management tools and methodologies with relational technology. We present an ontology-based approach that is flexible and efficient for dealing with complexity and change, integrated with a solid relational storage and a Web graphical user interface. Onto Clinical Research Forms (OntoCRF) is a framework for the definition, modeling, and instantiation of data repositories. It does not need any database design or programming. All required information to define a new project is explicitly stated in ontologies. Moreover, the user interface is built automatically on the fly as Web pages, whereas data are stored in a generic repository. This allows for immediate deployment and population of the database as well as instant online availability of any modification. OntoCRF is a complete framework to build data repositories with a solid relational storage. Driven by ontologies, OntoCRF is more flexible and efficient to deal with complexity and change than traditional systems and does not require very skilled technical people facilitating the engineering of clinical software systems.

  10. Seamless Integration of Desktop and Mobile Learning Experience through an Ontology-Based Adaptation Engine: Report of a Pilot-Project

    Science.gov (United States)

    Mercurio, Marco; Torre, Ilaria; Torsani, Simone

    2014-01-01

    The paper describes a module within the distance language learning environment of the Language Centre at the Genoa University which adapts, through an ontology, learning activities to the device in use. Adaptation means not simply resizing a page but also the ability to transform the nature of a task so that it fits the device with the smallest…

  11. GFVO: the Genomic Feature and Variation Ontology

    KAUST Repository

    Baran, Joachim

    2015-05-05

    Falling costs in genomic laboratory experiments have led to a steady increase of genomic feature and variation data. Multiple genomic data formats exist for sharing these data, and whilst they are similar, they are addressing slightly different data viewpoints and are consequently not fully compatible with each other. The fragmentation of data format specifications makes it hard to integrate and interpret data for further analysis with information from multiple data providers. As a solution, a new ontology is presented here for annotating and representing genomic feature and variation dataset contents. The Genomic Feature and Variation Ontology (GFVO) specifically addresses genomic data as it is regularly shared using the GFF3 (incl. FASTA), GTF, GVF and VCF file formats. GFVO simplifies data integration and enables linking of genomic annotations across datasets through common semantics of genomic types and relations. Availability and implementation. The latest stable release of the ontology is available via its base URI; previous and development versions are available at the ontology’s GitHub repository: https://github.com/BioInterchange/Ontologies; versions of the ontology are indexed through BioPortal (without external class-/property-equivalences due to BioPortal release 4.10 limitations); examples and reference documentation is provided on a separate web-page: http://www.biointerchange.org/ontologies.html. GFVO version 1.0.2 is licensed under the CC0 1.0 Universal license (https://creativecommons.org/publicdomain/zero/1.0) and therefore de facto within the public domain; the ontology can be appropriated without attribution for commercial and non-commercial use.

  12. Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function.

    Science.gov (United States)

    Chasman, Daniel I; Fuchsberger, Christian; Pattaro, Cristian; Teumer, Alexander; Böger, Carsten A; Endlich, Karlhans; Olden, Matthias; Chen, Ming-Huei; Tin, Adrienne; Taliun, Daniel; Li, Man; Gao, Xiaoyi; Gorski, Mathias; Yang, Qiong; Hundertmark, Claudia; Foster, Meredith C; O'Seaghdha, Conall M; Glazer, Nicole; Isaacs, Aaron; Liu, Ching-Ti; Smith, Albert V; O'Connell, Jeffrey R; Struchalin, Maksim; Tanaka, Toshiko; Li, Guo; Johnson, Andrew D; Gierman, Hinco J; Feitosa, Mary F; Hwang, Shih-Jen; Atkinson, Elizabeth J; Lohman, Kurt; Cornelis, Marilyn C; Johansson, Asa; Tönjes, Anke; Dehghan, Abbas; Lambert, Jean-Charles; Holliday, Elizabeth G; Sorice, Rossella; Kutalik, Zoltan; Lehtimäki, Terho; Esko, Tõnu; Deshmukh, Harshal; Ulivi, Sheila; Chu, Audrey Y; Murgia, Federico; Trompet, Stella; Imboden, Medea; Coassin, Stefan; Pistis, Giorgio; Harris, Tamara B; Launer, Lenore J; Aspelund, Thor; Eiriksdottir, Gudny; Mitchell, Braxton D; Boerwinkle, Eric; Schmidt, Helena; Cavalieri, Margherita; Rao, Madhumathi; Hu, Frank; Demirkan, Ayse; Oostra, Ben A; de Andrade, Mariza; Turner, Stephen T; Ding, Jingzhong; Andrews, Jeanette S; Freedman, Barry I; Giulianini, Franco; Koenig, Wolfgang; Illig, Thomas; Meisinger, Christa; Gieger, Christian; Zgaga, Lina; Zemunik, Tatijana; Boban, Mladen; Minelli, Cosetta; Wheeler, Heather E; Igl, Wilmar; Zaboli, Ghazal; Wild, Sarah H; Wright, Alan F; Campbell, Harry; Ellinghaus, David; Nöthlings, Ute; Jacobs, Gunnar; Biffar, Reiner; Ernst, Florian; Homuth, Georg; Kroemer, Heyo K; Nauck, Matthias; Stracke, Sylvia; Völker, Uwe; Völzke, Henry; Kovacs, Peter; Stumvoll, Michael; Mägi, Reedik; Hofman, Albert; Uitterlinden, Andre G; Rivadeneira, Fernando; Aulchenko, Yurii S; Polasek, Ozren; Hastie, Nick; Vitart, Veronique; Helmer, Catherine; Wang, Jie Jin; Stengel, Bénédicte; Ruggiero, Daniela; Bergmann, Sven; Kähönen, Mika; Viikari, Jorma; Nikopensius, Tiit; Province, Michael; Ketkar, Shamika; Colhoun, Helen; Doney, Alex; Robino, Antonietta; Krämer, Bernhard K; Portas, Laura; Ford, Ian; Buckley, Brendan M; Adam, Martin; Thun, Gian-Andri; Paulweber, Bernhard; Haun, Margot; Sala, Cinzia; Mitchell, Paul; Ciullo, Marina; Kim, Stuart K; Vollenweider, Peter; Raitakari, Olli; Metspalu, Andres; Palmer, Colin; Gasparini, Paolo; Pirastu, Mario; Jukema, J Wouter; Probst-Hensch, Nicole M; Kronenberg, Florian; Toniolo, Daniela; Gudnason, Vilmundur; Shuldiner, Alan R; Coresh, Josef; Schmidt, Reinhold; Ferrucci, Luigi; Siscovick, David S; van Duijn, Cornelia M; Borecki, Ingrid B; Kardia, Sharon L R; Liu, Yongmei; Curhan, Gary C; Rudan, Igor; Gyllensten, Ulf; Wilson, James F; Franke, Andre; Pramstaller, Peter P; Rettig, Rainer; Prokopenko, Inga; Witteman, Jacqueline; Hayward, Caroline; Ridker, Paul M; Parsa, Afshin; Bochud, Murielle; Heid, Iris M; Kao, W H Linda; Fox, Caroline S; Köttgen, Anna

    2012-12-15

    In conducting genome-wide association studies (GWAS), analytical approaches leveraging biological information may further understanding of the pathophysiology of clinical traits. To discover novel associations with estimated glomerular filtration rate (eGFR), a measure of kidney function, we developed a strategy for integrating prior biological knowledge into the existing GWAS data for eGFR from the CKDGen Consortium. Our strategy focuses on single nucleotide polymorphism (SNPs) in genes that are connected by functional evidence, determined by literature mining and gene ontology (GO) hierarchies, to genes near previously validated eGFR associations. It then requires association thresholds consistent with multiple testing, and finally evaluates novel candidates by independent replication. Among the samples of European ancestry, we identified a genome-wide significant SNP in FBXL20 (P = 5.6 × 10(-9)) in meta-analysis of all available data, and additional SNPs at the INHBC, LRP2, PLEKHA1, SLC3A2 and SLC7A6 genes meeting multiple-testing corrected significance for replication and overall P-values of 4.5 × 10(-4)-2.2 × 10(-7). Neither the novel PLEKHA1 nor FBXL20 associations, both further supported by association with eGFR among African Americans and with transcript abundance, would have been implicated by eGFR candidate gene approaches. LRP2, encoding the megalin receptor, was identified through connection with the previously known eGFR gene DAB2 and extends understanding of the megalin system in kidney function. These findings highlight integration of existing genome-wide association data with independent biological knowledge to uncover novel candidate eGFR associations, including candidates lacking known connections to kidney-specific pathways. The strategy may also be applicable to other clinical phenotypes, although more testing will be needed to assess its potential for discovery in general.

  13. Knowledge-Intensive Gathering and Integration of Statistical Information on European Fisheries

    NARCIS (Netherlands)

    Klinkert, M.; Treur, J.; Verwaart, T.; Loganantharaj, R.; Palm, G.; Ali, M.

    2000-01-01

    Gathering, maintenance, integration and presentation of statistics are major activities of the Dutch Agricultural Economics Research Institute LEI. In this paper we explore how knowledge and agent technology can be exploited to support the information gathering and integration process. In

  14. Ontology of fractures

    Science.gov (United States)

    Zhong, Jian; Aydina, Atilla; McGuinness, Deborah L.

    2009-03-01

    Fractures are fundamental structures in the Earth's crust and they can impact many societal and industrial activities including oil and gas exploration and production, aquifer management, CO 2 sequestration, waste isolation, the stabilization of engineering structures, and assessing natural hazards (earthquakes, volcanoes, and landslides). Therefore, an ontology which organizes the concepts of fractures could help facilitate a sound education within, and communication among, the highly diverse professional and academic community interested in the problems cited above. We developed a process-based ontology that makes explicit specifications about fractures, their properties, and the deformation mechanisms which lead to their formation and evolution. Our ontology emphasizes the relationships among concepts such as the factors that influence the mechanism(s) responsible for the formation and evolution of specific fracture types. Our ontology is a valuable resource with a potential to applications in a number of fields utilizing recent advances in Information Technology, specifically for digital data and information in computers, grids, and Web services.

  15. A Method for Evaluating and Standardizing Ontologies

    Science.gov (United States)

    Seyed, Ali Patrice

    2012-01-01

    The Open Biomedical Ontology (OBO) Foundry initiative is a collaborative effort for developing interoperable, science-based ontologies. The Basic Formal Ontology (BFO) serves as the upper ontology for the domain-level ontologies of OBO. BFO is an upper ontology of types as conceived by defenders of realism. Among the ontologies developed for OBO…

  16. Manufacturing ontology through templates

    Directory of Open Access Journals (Sweden)

    Diciuc Vlad

    2017-01-01

    Full Text Available The manufacturing industry contains a high volume of knowhow and of high value, much of it being held by key persons in the company. The passing of this know-how is the basis of manufacturing ontology. Among other methods like advanced filtering and algorithm based decision making, one way of handling the manufacturing ontology is via templates. The current paper tackles this approach and highlights the advantages concluding with some recommendations.

  17. Ontological support for web courseware authoring

    NARCIS (Netherlands)

    Aroyo, L.M.; Dicheva, D.; Cristea, A.I.; Cerri, S.A.; Gouardères, G.; Paraguaçu, F.

    2002-01-01

    In this paper we present an ontology- oriented authoring support system for Web-based courseware. This is an elaboration of our approach to knowledge classification and indexing in the previously developed system AIMS (Agent-based Information Management System) aimed at supporting students while

  18. OntoWeaver S: supporting the design of knowledge portals

    OpenAIRE

    Lei, Yuangui; Motta, Enrico; Domingue, John

    2004-01-01

    This paper presents OntoWeaver-S, an ontology-based infrastructure for building knowledge portals. In particular, OntoWeaver-S is integrated with a comprehensive web service platform, IRS-II, for the publication, discovery, and execution of web services. In this way, OntoWeaver-S supports the access and provision of remote web services for knowledge portals. Moreover, it provides a set of comprehensive site ontologies to model and represent knowledge portals, and thus is able to offer high le...

  19. Topical Knowledge in L2 Speaking Assessment: Comparing Independent and Integrated Speaking Test Tasks

    Science.gov (United States)

    Huang, Heng-Tsung Danny; Hung, Shao-Ting Alan; Plakans, Lia

    2018-01-01

    Integrated speaking test tasks (integrated tasks) provide reading and/or listening input to serve as the basis for test-takers to formulate their oral responses. This study examined the influence of topical knowledge on integrated speaking test performance and compared independent speaking test performance and integrated speaking test performance…

  20. Improving the interoperability of biomedical ontologies with compound alignments.

    Science.gov (United States)

    Oliveira, Daniela; Pesquita, Catia

    2018-01-09

    Ontologies are commonly used to annotate and help process life sciences data. Although their original goal is to facilitate integration and interoperability among heterogeneous data sources, when these sources are annotated with distinct ontologies, bridging this gap can be challenging. In the last decade, ontology matching systems have been evolving and are now capable of producing high-quality mappings for life sciences ontologies, usually limited to the equivalence between two ontologies. However, life sciences research is becoming increasingly transdisciplinary and integrative, fostering the need to develop matching strategies that are able to handle multiple ontologies and more complex relations between their concepts. We have developed ontology matching algorithms that are able to find compound mappings between multiple biomedical ontologies, in the form of ternary mappings, finding for instance that "aortic valve stenosis"(HP:0001650) is equivalent to the intersection between "aortic valve"(FMA:7236) and "constricted" (PATO:0001847). The algorithms take advantage of search space filtering based on partial mappings between ontology pairs, to be able to handle the increased computational demands. The evaluation of the algorithms has shown that they are able to produce meaningful results, with precision in the range of 60-92% for new mappings. The algorithms were also applied to the potential extension of logical definitions of the OBO and the matching of several plant-related ontologies. This work is a first step towards finding more complex relations between multiple ontologies. The evaluation shows that the results produced are significant and that the algorithms could satisfy specific integration needs.

  1. Development of National Map ontologies for organization and orchestration of hydrologic observations

    Science.gov (United States)

    Lieberman, J. E.

    2014-12-01

    Feature layers in the National Map program (TNM) are a fundamental context for much of the data collection and analysis conducted by the USGS and other governmental and nongovernmental organizations. Their computational usefulness, though, has been constrained by the lack of formal relationships besides superposition between TNM layers, as well as limited means of representing how TNM datasets relate to additional attributes, datasets, and activities. In the field of Geospatial Information Science, there has been a growing recognition of the value of semantic representation and technology for addressing these limitations, particularly in the face of burgeoning information volume and heterogeneity. Fundamental to this approach is the development of formal ontologies for concepts related to that information that can be processed computationally to enhance creation and discovery of new geospatial knowledge. They offer a means of making much of the presently innate knowledge about relationships in and between TNM features accessible for machine processing and distributed computation.A full and comprehensive ontology of all knowledge represented by TNM features is still impractical. The work reported here involves elaboration and integration of a number of small ontology design patterns (ODP's) that represent limited, discrete, but commonly accepted and broadly applicable physical theories for the behavior of TNM features representing surface water bodies and landscape surfaces and the connections between them. These ontology components are validated through use in applications for discovery and aggregation of water science observational data associated with National Hydrography Data features, features from the National Elevation Dataset (NED) and Water Boundary Dataset (WBD) that constrain water occurrence in the continental US. These applications emphasize workflows which are difficult or impossible to automate using existing data structures. Evaluation of the

  2. Integrated Risk and Knowledge Management Program -- IRKM-P

    Science.gov (United States)

    Lengyel, David M.

    2009-01-01

    The NASA Exploration Systems Mission Directorate (ESMD) IRKM-P tightly couples risk management and knowledge management processes and tools to produce an effective "modern" work environment. IRKM-P objectives include: (1) to learn lessons from past and current programs (Apollo, Space Shuttle, and the International Space Station); (2) to generate and share new engineering design, operations, and management best practices through preexisting Continuous Risk Management (CRM) procedures and knowledge-management practices; and (3) to infuse those lessons and best practices into current activities. The conceptual framework of the IRKM-P is based on the assumption that risks highlight potential knowledge gaps that might be mitigated through one or more knowledge management practices or artifacts. These same risks also serve as cues for collection of knowledge particularly, knowledge of technical or programmatic challenges that might recur.

  3. An integrative model of knowledge management and team work

    OpenAIRE

    Juan A. Marin-Garcia; Mª Elena Zarate-Martinez

    2008-01-01

    Human Resource Management relevance in Knowledge Management has been studied in academic literature mostly from the point of view of recruitment, selection, wages and salaries and career development processes. We have found few publications that are focused in the behaviour of the group of people who generate, share and transfer that knowledge while working in a team. The aim of this paper is to propose a framework that describes the relation between knowledge management and team work,, integ...

  4. The use of web ontology languages and other semantic web tools in drug discovery.

    Science.gov (United States)

    Chen, Huajun; Xie, Guotong

    2010-05-01

    To optimize drug development processes, pharmaceutical companies require principled approaches to integrate disparate data on a unified infrastructure, such as the web. The semantic web, developed on the web technology, provides a common, open framework capable of harmonizing diversified resources to enable networked and collaborative drug discovery. We survey the state of art of utilizing web ontologies and other semantic web technologies to interlink both data and people to support integrated drug discovery across domains and multiple disciplines. Particularly, the survey covers three major application categories including: i) semantic integration and open data linking; ii) semantic web service and scientific collaboration and iii) semantic data mining and integrative network analysis. The reader will gain: i) basic knowledge of the semantic web technologies; ii) an overview of the web ontology landscape for drug discovery and iii) a basic understanding of the values and benefits of utilizing the web ontologies in drug discovery. i) The semantic web enables a network effect for linking open data for integrated drug discovery; ii) The semantic web service technology can support instant ad hoc collaboration to improve pipeline productivity and iii) The semantic web encourages publishing data in a semantic way such as resource description framework attributes and thus helps move away from a reliance on pure textual content analysis toward more efficient semantic data mining.

  5. Ontology-Based Model Of Firm Competitiveness

    Science.gov (United States)

    Deliyska, Boryana; Stoenchev, Nikolay

    2010-10-01

    Competitiveness is important characteristics of each business organization (firm, company, corporation etc). It is of great significance for the organization existence and defines evaluation criteria of business success at microeconomical level. Each criterium comprises set of indicators with specific weight coefficients. In the work an ontology-based model of firm competitiveness is presented as a set of several mutually connected ontologies. It would be useful for knowledge structuring, standardization and sharing among experts and software engineers who develop application in the domain. Then the assessment of the competitiveness of various business organizations could be generated more effectively.

  6. Ontology and Cloud Computing in Various Applications: The ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... to emphasize the importance of both ontology and cloud computing in various .... of knowledge management applications and retrieve information using .... above in terms of hard drive space, but any device ordinary computer ...

  7. PSOM2—partitioning-based scalable ontology matching using ...

    Indian Academy of Sciences (India)

    B Sathiya

    2017-11-16

    Nov 16, 2017 ... 1 Department of Computer Science and Engineering, College of Engineering, Guindy, Anna ... achieved by the ontology that is the new form of knowledge ... space, since only the matchable cluster pairs are considered.

  8. Application of Ontology Technology in Health Statistic Data Analysis.

    Science.gov (United States)

    Guo, Minjiang; Hu, Hongpu; Lei, Xingyun

    2017-01-01

    Research Purpose: establish health management ontology for analysis of health statistic data. Proposed Methods: this paper established health management ontology based on the analysis of the concepts in China Health Statistics Yearbook, and used protégé to define the syntactic and semantic structure of health statistical data. six classes of top-level ontology concepts and their subclasses had been extracted and the object properties and data properties were defined to establish the construction of these classes. By ontology instantiation, we can integrate multi-source heterogeneous data and enable administrators to have an overall understanding and analysis of the health statistic data. ontology technology provides a comprehensive and unified information integration structure of the health management domain and lays a foundation for the efficient analysis of multi-source and heterogeneous health system management data and enhancement of the management efficiency.

  9. Ordering Disorders. Linking organization design and knowledge integration

    NARCIS (Netherlands)

    Hendriks, P.H.J.; Fruytier, B.G.M.

    2014-01-01

    Studies addressing the connections between knowledge and organization structures can be divided into two classes. One class holds that a perspective on knowledge signals shortcomings of classical design principles and calls for flatter hierarchy and less specification of the production structure.

  10. The use of ontologies in the spatial planning domain

    CSIR Research Space (South Africa)

    Kaczmarek, I

    2011-07-01

    Full Text Available are based on RDF (Resource Description Framework) and RDFS (Resource Description Framework Schema) model. A CLOSER LOOK The description of datasets and the objects contained therein using ontologies is a way of representing knowledge about space. Having... of these data. The added value here is that knowledge can be derived. INTRODUCTION TO ONTOLOGIES Ontologies are considered to be a core element of the Semantic Web, which is defined as ?the extension of the World Wide Web that enables people to share content...

  11. A Formal Theory for Modular ERDF Ontologies

    Science.gov (United States)

    Analyti, Anastasia; Antoniou, Grigoris; Damásio, Carlos Viegas

    The success of the Semantic Web is impossible without any form of modularity, encapsulation, and access control. In an earlier paper, we extended RDF graphs with weak and strong negation, as well as derivation rules. The ERDF #n-stable model semantics of the extended RDF framework (ERDF) is defined, extending RDF(S) semantics. In this paper, we propose a framework for modular ERDF ontologies, called modular ERDF framework, which enables collaborative reasoning over a set of ERDF ontologies, while support for hidden knowledge is also provided. In particular, the modular ERDF stable model semantics of modular ERDF ontologies is defined, extending the ERDF #n-stable model semantics. Our proposed framework supports local semantics and different points of view, local closed-world and open-world assumptions, and scoped negation-as-failure. Several complexity results are provided.

  12. Functional Analysis of OMICs Data and Small Molecule Compounds in an Integrated "Knowledge-Based" Platform.

    Science.gov (United States)

    Dubovenko, Alexey; Nikolsky, Yuri; Rakhmatulin, Eugene; Nikolskaya, Tatiana

    2017-01-01

    Analysis of NGS and other sequencing data, gene variants, gene expression, proteomics, and other high-throughput (OMICs) data is challenging because of its biological complexity and high level of technical and biological noise. One way to deal with both problems is to perform analysis with a high fidelity annotated knowledgebase of protein interactions, pathways, and functional ontologies. This knowledgebase has to be structured in a computer-readable format and must include software tools for managing experimental data, analysis, and reporting. Here, we present MetaCore™ and Key Pathway Advisor (KPA), an integrated platform for functional data analysis. On the content side, MetaCore and KPA encompass a comprehensive database of molecular interactions of different types, pathways, network models, and ten functional ontologies covering human, mouse, and rat genes. The analytical toolkit includes tools for gene/protein list enrichment analysis, statistical "interactome" tool for the identification of over- and under-connected proteins in the dataset, and a biological network analysis module made up of network generation algorithms and filters. The suite also features Advanced Search, an application for combinatorial search of the database content, as well as a Java-based tool called Pathway Map Creator for drawing and editing custom pathway maps. Applications of MetaCore and KPA include molecular mode of action of disease research, identification of potential biomarkers and drug targets, pathway hypothesis generation, analysis of biological effects for novel small molecule compounds and clinical applications (analysis of large cohorts of patients, and translational and personalized medicine).

  13. An ontology for human-like interaction systems

    OpenAIRE

    Albacete García, Esperanza

    2016-01-01

    This report proposes and describes the development of a Ph.D. Thesis aimed at building an ontological knowledge model supporting Human-Like Interaction systems. The main function of such knowledge model in a human-like interaction system is to unify the representation of each concept, relating it to the appropriate terms, as well as to other concepts with which it shares semantic relations. When developing human-like interactive systems, the inclusion of an ontological module can be valuab...

  14. Enabling Integrated Decision Making for Electronic-Commerce by Modelling an Enterprise's Sharable Knowledge.

    Science.gov (United States)

    Kim, Henry M.

    2000-01-01

    An enterprise model, a computational model of knowledge about an enterprise, is a useful tool for integrated decision-making by e-commerce suppliers and customers. Sharable knowledge, once represented in an enterprise model, can be integrated by the modeled enterprise's e-commerce partners. Presents background on enterprise modeling, followed by…

  15. Community-based Ontology Development, Annotation and Discussion with MediaWiki extension Ontokiwi and Ontokiwi-based Ontobedia

    Science.gov (United States)

    Ong, Edison; He, Yongqun

    2016-01-01

    Hundreds of biological and biomedical ontologies have been developed to support data standardization, integration and analysis. Although ontologies are typically developed for community usage, community efforts in ontology development are limited. To support ontology visualization, distribution, and community-based annotation and development, we have developed Ontokiwi, an ontology extension to the MediaWiki software. Ontokiwi displays hierarchical classes and ontological axioms. Ontology classes and axioms can be edited and added using Ontokiwi form or MediaWiki source editor. Ontokiwi also inherits MediaWiki features such as Wikitext editing and version control. Based on the Ontokiwi/MediaWiki software package, we have developed Ontobedia, which targets to support community-based development and annotations of biological and biomedical ontologies. As demonstrations, we have loaded the Ontology of Adverse Events (OAE) and the Cell Line Ontology (CLO) into Ontobedia. Our studies showed that Ontobedia was able to achieve expected Ontokiwi features. PMID:27570653

  16. Information and organization in public health institutes: an ontology-based modeling of the entities in the reception-analysis-report phases.

    Science.gov (United States)

    Pozza, Giandomenico; Borgo, Stefano; Oltramari, Alessandro; Contalbrigo, Laura; Marangon, Stefano

    2016-09-08

    Ontologies are widely used both in the life sciences and in the management of public and private companies. Typically, the different offices in an organization develop their own models and related ontologies to capture specific tasks and goals. Although there might be an overall coordination, the use of distinct ontologies can jeopardize the integration of data across the organization since data sharing and reusability are sensitive to modeling choices. The paper provides a study of the entities that are typically found at the reception, analysis and report phases in public institutes in the life science domain. Ontological considerations and techniques are introduced and their implementation exemplified by studying the Istituto Zooprofilattico Sperimentale delle Venezie (IZSVe), a public veterinarian institute with different geographical locations and several laboratories. Different modeling issues are discussed like the identification and characterization of the main entities in these phases; the classification of the (types of) data; the clarification of the contexts and the roles of the involved entities. The study is based on a foundational ontology and shows how it can be extended to a comprehensive and coherent framework comprising the different institute's roles, processes and data. In particular, it shows how to use notions lying at the borderline between ontology and applications, like that of knowledge object. The paper aims to help the modeler to understand the core viewpoint of the organization and to improve data transparency. The study shows that the entities at play can be analyzed within a single ontological perspective allowing us to isolate a single ontological framework for the whole organization. This facilitates the development of coherent representations of the entities and related data, and fosters the use of integrated software for data management and reasoning across the company.

  17. Ontology-Based Retrieval of Spatially Related Objects for Location Based Services

    Science.gov (United States)

    Haav, Hele-Mai; Kaljuvee, Aivi; Luts, Martin; Vajakas, Toivo

    Advanced Location Based Service (LBS) applications have to integrate information stored in GIS, information about users' preferences (profile) as well as contextual information and information about application itself. Ontology engineering provides methods to semantically integrate several data sources. We propose an ontology-driven LBS development framework: the paper describes the architecture of ontologies and their usage for retrieval of spatially related objects relevant to the user. Our main contribution is to enable personalised ontology driven LBS by providing a novel approach for defining personalised semantic spatial relationships by means of ontologies. The approach is illustrated by an industrial case study.

  18. Application of Pareto optimization method for ontology matching in nuclear reactor domain

    International Nuclear Information System (INIS)

    Meenachi, N. Madurai; Baba, M. Sai

    2017-01-01

    This article describes the need for ontology matching and describes the methods to achieve the same. Efforts are put in the implementation of the semantic web based knowledge management system for nuclear domain which necessitated use of the methods for development of ontology matching. In order to exchange information in a distributed environment, ontology mapping has been used. The constraints in matching the ontology are also discussed. Pareto based ontology matching algorithm is used to find the similarity between two ontologies in the nuclear reactor domain. Algorithms like Jaro Winkler distance, Needleman Wunsch algorithm, Bigram, Kull Back and Cosine divergence are employed to demonstrate ontology matching. A case study was carried out to analysis the ontology matching in diversity in the nuclear reactor domain and same was illustrated.

  19. Application of Pareto optimization method for ontology matching in nuclear reactor domain

    Energy Technology Data Exchange (ETDEWEB)

    Meenachi, N. Madurai [Indira Gandhi Centre for Atomic Research, HBNI, Tamil Nadu (India). Planning and Human Resource Management Div.; Baba, M. Sai [Indira Gandhi Centre for Atomic Research, HBNI, Tamil Nadu (India). Resources Management Group

    2017-12-15

    This article describes the need for ontology matching and describes the methods to achieve the same. Efforts are put in the implementation of the semantic web based knowledge management system for nuclear domain which necessitated use of the methods for development of ontology matching. In order to exchange information in a distributed environment, ontology mapping has been used. The constraints in matching the ontology are also discussed. Pareto based ontology matching algorithm is used to find the similarity between two ontologies in the nuclear reactor domain. Algorithms like Jaro Winkler distance, Needleman Wunsch algorithm, Bigram, Kull Back and Cosine divergence are employed to demonstrate ontology matching. A case study was carried out to analysis the ontology matching in diversity in the nuclear reactor domain and same was illustrated.

  20. (KA)2: building ontologies for the internet: a mid-term report

    NARCIS (Netherlands)

    Benjamins, R.; Fensel, D.A.; Decker, S.; Gomez Perez, A.

    1999-01-01

    Ontologies are becoming increasingly more important in many different areas, including the knowledge management area. In knowledge management, ontologies can be used as an instrument to make knowledge assets intelligently accessible to people in organizations through an Intranet or the Internet.

  1. Integrating experiences from operations into engineering design: modelling knowledge transfer in the offshore oil industry

    DEFF Research Database (Denmark)

    Souza da Conceição, Carolina; Broberg, Ole; Paravizo, Esdras

    2017-01-01

    of knowledge registered in the systems without standards to categorise and store this knowledge, to being difficult to access and retrieve the knowledge in the systems. Discussion: Transferring knowledge and experiences from users brings human factors into play and modelling the knowledge transfer process...... and workwise distance between operations and engineering design teams, integrating human factors and transferring knowledge are key aspects when designing for better performance systems. Research Objective: Based on an in-depth empirical investigation in an offshore oil company, this study aims to provide......Summative Statement: Integrating human factors and users’ experiences in design projects is a well-known challenge. This study focus on the specific challenges for transferring these experiences and how using a knowledge transfer model can help this integration on the design of high-risk productive...

  2. An ontology-driven semantic mashup of gene and biological pathway information: application to the domain of nicotine dependence.

    Science.gov (United States)

    Sahoo, Satya S; Bodenreider, Olivier; Rutter, Joni L; Skinner, Karen J; Sheth, Amit P

    2008-10-01

    This paper illustrates how Semantic Web technologies (especially RDF, OWL, and SPARQL) can support information integration and make it easy to create semantic mashups (semantically integrated resources). In the context of understanding the genetic basis of nicotine dependence, we integrate gene and pathway information and show how three complex biological queries can be answered by the integrated knowledge base. We use an ontology-driven approach to integrate two gene resources (Entrez Gene and HomoloGene) and three pathway resources (KEGG, Reactome and BioCyc), for five organisms, including humans. We created the Entrez Knowledge Model (EKoM), an information model in OWL for the gene resources, and integrated it with the extant BioPAX ontology designed for pathway resources. The integrated schema is populated with data from the pathway resources, publicly available in BioPAX-compatible format, and gene resources for which a population procedure was created. The SPARQL query language is used to formulate queries over the integrated knowledge base to answer the three biological queries. Simple SPARQL queries could easily identify hub genes, i.e., those genes whose gene products participate in many pathways or interact with many other gene products. The identification of the genes expressed in the brain turned out to be more difficult, due to the lack of a common identification scheme for proteins. Semantic Web technologies provide a valid framework for information integration in the life sciences. Ontology-driven integration represents a flexible, sustainable and extensible solution to the integration of large volumes of information. Additional resources, which enable the creation of mappings between information sources, are required to compensate for heterogeneity across namespaces. RESOURCE PAGE: http://knoesis.wright.edu/research/lifesci/integration/structured_data/JBI-2008/

  3. Vernacular Knowledge and Water Management – Towards the Integration of Expert Science and Local Knowledge in Ontario, Canada

    Directory of Open Access Journals (Sweden)

    Hugh Simpson

    2015-10-01

    Full Text Available Complex environmental problems cannot be solved using expert science alone. Rather, these kinds of problems benefit from problem-solving processes that draw on 'vernacular' knowledge. Vernacular knowledge integrates expert science and local knowledge with community beliefs and values. Collaborative approaches to water problem-solving can provide forums for bringing together diverse, and often competing, interests to produce vernacular knowledge through deliberation and negotiation of solutions. Organised stakeholder groups are participating increasingly in such forums, often through involvement of networks, but it is unclear what roles these networks play in the creation and sharing of vernacular knowledge. A case-study approach was used to evaluate the involvement of a key stakeholder group, the agricultural community in Ontario, Canada, in creating vernacular knowledge during a prescribed multi-stakeholder problem-solving process for source water protection for municipal supplies. Data sources – including survey questionnaire responses, participant observation, and publicly available documents – illustrate how respondents supported and participated in the creation of vernacular knowledge. The results of the evaluation indicate that the respondents recognised and valued agricultural knowledge as an information source for resolving complex problems. The research also provided insight concerning the complementary roles and effectiveness of the agricultural community in sharing knowledge within a prescribed problem-solving process.

  4. Documenting the emergence of bio-ontologies: or, why researching bioinformatics requires HPSSB.

    Science.gov (United States)

    Leonelli, Sabina

    2010-01-01

    This paper reflects on the analytic challenges emerging from the study of bioinformatic tools recently created to store and disseminate biological data, such as databases, repositories, and bio-ontologies. I focus my discussion on the Gene Ontology, a term that defines three entities at once: a classification system facilitating the distribution and use of genomic data as evidence towards new insights; an expert community specialised in the curation of those data; and a scientific institution promoting the use of this tool among experimental biologists. These three dimensions of the Gene Ontology can be clearly distinguished analytically, but are tightly intertwined in practice. I suggest that this is true of all bioinformatic tools: they need to be understood simultaneously as epistemic, social, and institutional entities, since they shape the knowledge extracted from data and at the same time regulate the organisation, development, and communication of research. This viewpoint has one important implication for the methodologies used to study these tools; that is, the need to integrate historical, philosophical, and sociological approaches. I illustrate this claim through examples of misunderstandings that may result from a narrowly disciplinary study of the Gene Ontology, as I experienced them in my own research.

  5. An ontology based trust verification of software license agreement

    Science.gov (United States)

    Lu, Wenhuan; Li, Xiaoqing; Gan, Zengqin; Wei, Jianguo

    2017-08-01

    When we install software or download software, there will show up so big mass document to state the rights and obligations, for which lots of person are not patient to read it or understand it. That would may make users feel distrust for the software. In this paper, we propose an ontology based verification for Software License Agreement. First of all, this work proposed an ontology model for domain of Software License Agreement. The domain ontology is constructed by proposed methodology according to copyright laws and 30 software license agreements. The License Ontology can act as a part of generalized copyright law knowledge model, and also can work as visualization of software licenses. Based on this proposed ontology, a software license oriented text summarization approach is proposed which performances showing that it can improve the accuracy of software licenses summarizing. Based on the summarization, the underline purpose of the software license can be explicitly explored for trust verification.

  6. Research and Application of Knowledge Resources Network for Product Innovation

    Directory of Open Access Journals (Sweden)

    Chuan Li

    2015-01-01

    Full Text Available In order to enhance the capabilities of knowledge service in product innovation design service platform, a method of acquiring knowledge resources supporting for product innovation from the Internet and providing knowledge active push is proposed. Through knowledge modeling for product innovation based on ontology, the integrated architecture of knowledge resources network is put forward. The technology for the acquisition of network knowledge resources based on focused crawler and web services is studied. Knowledge active push is provided for users by user behavior analysis and knowledge evaluation in order to improve users’ enthusiasm for participation in platform. Finally, an application example is illustrated to prove the effectiveness of the method.

  7. Research and application of knowledge resources network for product innovation.

    Science.gov (United States)

    Li, Chuan; Li, Wen-qiang; Li, Yan; Na, Hui-zhen; Shi, Qian

    2015-01-01

    In order to enhance the capabilities of knowledge service in product innovation design service platform, a method of acquiring knowledge resources supporting for product innovation from the Internet and providing knowledge active push is proposed. Through knowledge modeling for product innovation based on ontology, the integrated architecture of knowledge resources network is put forward. The technology for the acquisition of network knowledge resources based on focused crawler and web services is studied. Knowledge active push is provided for users by user behavior analysis and knowledge evaluation in order to improve users' enthusiasm for participation in platform. Finally, an application example is illustrated to prove the effectiveness of the method.

  8. Integrated corridor management (ICM) knowledge and technology transfer (KTT).

    Science.gov (United States)

    2014-01-01

    The ICM approach involves aggressive, : proactive integration of infrastructure : along major corridors so that : transportation professionals can fully : leverage all existing modal choices : and assets. ICM helps transportation : leaders improve tr...

  9. Ontology: ambiguity and accuracy

    Directory of Open Access Journals (Sweden)

    Marcelo Schiessl

    2012-08-01

    Full Text Available Ambiguity is a major obstacle to information retrieval. It is source of several researches in Information Science. Ontologies have been studied in order to solve problems related to ambiguities. Paradoxically, “ontology” term is also ambiguous and it is understood according to the use by the community. Philosophy and Computer Science seems to have the most accentuated difference related to the term sense. The former holds undisputed tradition and authority. The latter, in despite of being quite recent, holds an informal sense, but pragmatic. Information Science acts ranging from philosophical to computational approaches so as to get organized collections based on balance between users’ necessities and available information. The semantic web requires informational cycle automation and demands studies related to ontologies. Consequently, revisiting relevant approaches for the study of ontologies plays a relevant role as a way to provide useful ideas to researchers maintaining philosophical rigor, and convenience provided by computers.

  10. A Method for Building Personalized Ontology Summaries

    OpenAIRE

    Queiroz-Sousa, Paulo Orlando; Salgado, Ana Carolina; Pires, Carlos Eduardo

    2013-01-01

    In the context of ontology engineering, the ontology understanding is the basis for its further developmentand reuse. One intuitive eective approach to support ontology understanding is the process of ontology summarizationwhich highlights the most important concepts of an ontology. Ontology summarization identies an excerpt from anontology that contains the most relevant concepts and produces an abridged ontology. In this article, we present amethod for summarizing ontologies that represent ...

  11. Core Semantics for Public Ontologies

    National Research Council Canada - National Science Library

    Suni, Niranjan

    2005-01-01

    ... (schemas or ontologies) with respect to objects. The DARPA Agent Markup Language (DAML) through the use of ontologies provides a very powerful way to describe objects and their relationships to other objects...

  12. Research on Ontology Modeling of Steel Manufacturing Process Based on Big Data Analysis

    Directory of Open Access Journals (Sweden)

    Bao Qing

    2016-01-01

    Full Text Available As an important method that steel industries ride the Indutrie 4.0 wave, knowledge management is expected to be versatile, effective and intelligent. Mechanism modeling difficulties, numerous influencing factors and complex industrial chains hinder the development of knowledge and information integration. Using data potentials, big data analysis can be an effective way to deal with knowledge acquisition as it solves the inaccuracy and imperfection mechanism modeling may lead to. This paper proposes a big data knowledge management system(BDAKMS adhering to data driven, intelligent analysis, service publication, dynamic update principle which can effectively extracts knowledge from mass data. Then, ontology modeling gives the knowledge unified descriptions as well as inference details combined with semantic web techniques.

  13. Knowledge Management Integration into Strategic Human Capital Management Systems

    International Nuclear Information System (INIS)

    Marco, Tony; Heler, David

    2014-01-01

    Leadership model philosophies: • Knowledge is fundamental – share it; • We are in the refueling outage business; • Cost effective does not necessarily mean cheap; • Working efficiently and event free; • Make conscious, informed decisions; • Excellence in Operational Focus; • Operations Leads the Station; • End of Licenses and Beyond 60; • Our Leadership Model - Our future

  14. Knowledge-enabled Customer Relationship Management: integrating customer relationship management and knowledge management concepts

    OpenAIRE

    Gebert, Henning; Geib, Malte; Kolbe, Lutz; Brenner, Walter

    2003-01-01

    The concepts of customer relationship management (CRM) and knowledge management (KM) both focus on allocating resources to supportive business activities in order to gain competitive advantages. CRM focuses on managing the relationship between a company and its current and prospective customer base as a key to success, while KM recognizes the knowledge available to a company as a major success factor.From a business process manager's perspective both the CRM and KM approaches promise a positi...

  15. An ontology design pattern for surface water features

    Science.gov (United States)

    Sinha, Gaurav; Mark, David; Kolas, Dave; Varanka, Dalia; Romero, Boleslo E.; Feng, Chen-Chieh; Usery, E. Lynn; Liebermann, Joshua; Sorokine, Alexandre

    2014-01-01

    Surface water is a primary concept of human experience but concepts are captured in cultures and languages in many different ways. Still, many commonalities exist due to the physical basis of many of the properties and categories. An abstract ontology of surface water features based only on those physical properties of landscape features has the best potential for serving as a foundational domain ontology for other more context-dependent ontologies. The Surface Water ontology design pattern was developed both for domain knowledge distillation and to serve as a conceptual building-block for more complex or specialized surface water ontologies. A fundamental distinction is made in this ontology between landscape features that act as containers (e.g., stream channels, basins) and the bodies of water (e.g., rivers, lakes) that occupy those containers. Concave (container) landforms semantics are specified in a Dry module and the semantics of contained bodies of water in a Wet module. The pattern is implemented in OWL, but Description Logic axioms and a detailed explanation is provided in this paper. The OWL ontology will be an important contribution to Semantic Web vocabulary for annotating surface water feature datasets. Also provided is a discussion of why there is a need to complement the pattern with other ontologies, especially the previously developed Surface Network pattern. Finally, the practical value of the pattern in semantic querying of surface water datasets is illustrated through an annotated geospatial dataset and sample queries using the classes of the Surface Water pattern.

  16. An Ontology for Description of Drug Discovery Investigations

    Directory of Open Access Journals (Sweden)

    Qi Da

    2010-12-01

    Full Text Available The paper presents an ontology for the description of Drug Discovery Investigation (DDI. This has been developed through the use of a Robot Scientist “Eve”, and in consultation with industry. DDI aims to define the principle entities and the relations in the research and development phase of the drug discovery pipeline. DDI is highly transferable and extendable due to its adherence to accepted standards, and compliance with existing ontology resources. This enables DDI to be integrated with such related ontologies as the Vaccine Ontology, the Advancing Clinico-Genomic Trials on Cancer Master Ontology, etc. DDI is available at http://purl.org/ddi/wikipedia or http://purl.org/ddi/home

  17. A Tailored Ontology Supporting Sensor Implementation for the Maintenance of Industrial Machines

    Directory of Open Access Journals (Sweden)

    Elaheh Maleki

    2017-09-01

    Full Text Available The longtime productivity of an industrial machine is improved by condition-based maintenance strategies. To do this, the integration of sensors and other cyber-physical devices is necessary in order to capture and analyze a machine’s condition through its lifespan. Thus, choosing the best sensor is a critical step to ensure the efficiency of the maintenance process. Indeed, considering the variety of sensors, and their features and performance, a formal classification of a sensor’s domain knowledge is crucial. This classification facilitates the search for and reuse of solutions during the design of a new maintenance service. Following a Knowledge Management methodology, the paper proposes and develops a new sensor ontology that structures the domain knowledge, covering both theoretical and experimental sensor attributes. An industrial case study is conducted to validate the proposed ontology and to demonstrate its utility as a guideline to ease the search of suitable sensors. Based on the ontology, the final solution will be implemented in a shared repository connected to legacy CAD (computer-aided design systems. The selection of the best sensor is, firstly, obtained by the matching of application requirements and sensor specifications (that are proposed by this sensor repository. Then, it is refined from the experimentation results. The achieved solution is recorded in the sensor repository for future reuse. As a result, the time and cost of the design process of new condition-based maintenance services is reduced.

  18. A Tailored Ontology Supporting Sensor Implementation for the Maintenance of Industrial Machines.

    Science.gov (United States)

    Maleki, Elaheh; Belkadi, Farouk; Ritou, Mathieu; Bernard, Alain

    2017-09-08

    The longtime productivity of an industrial machine is improved by condition-based maintenance strategies. To do this, the integration of sensors and other cyber-physical devices is necessary in order to capture and analyze a machine's condition through its lifespan. Thus, choosing the best sensor is a critical step to ensure the efficiency of the maintenance process. Indeed, considering the variety of sensors, and their features and performance, a formal classification of a sensor's domain knowledge is crucial. This classification facilitates the search for and reuse of solutions during the design of a new maintenance service. Following a Knowledge Management methodology, the paper proposes and develops a new sensor ontology that structures the domain knowledge, covering both theoretical and experimental sensor attributes. An industrial case study is conducted to validate the proposed ontology and to demonstrate its utility as a guideline to ease the search of suitable sensors. Based on the ontology, the final solution will be implemented in a shared repository connected to legacy CAD (computer-aided design) systems. The selection of the best sensor is, firstly, obtained by the matching of application requirements and sensor specifications (that are proposed by this sensor repository). Then, it is refined from the experimentation results. The achieved solution is recorded in the sensor repository for future reuse. As a result, the time and cost of the design process of new condition-based maintenance services is reduced.

  19. Indigenous Knowledge, Science, and Resilience: What Have We Learned from a Decade of International Literature on "Integration"?

    Directory of Open Access Journals (Sweden)

    Erin L. Bohensky

    2011-12-01

    Full Text Available Despite the increasing trend worldwide of integrating indigenous and scientific knowledge in natural resource management, there has been little stock-taking of literature on lessons learned from bringing indigenous knowledge and science together and the implications for maintaining and building social-ecological system resilience. In this paper we investigate: (1 themes, questions, or problems encountered for integration of indigenous knowledge and science; (2 the relationship between knowledge integration and social-ecological system resilience; and (3 critical features of knowledge integration practice needed to foster productive and mutually beneficial relationships between indigenous knowledge and science. We examine these questions through content analyses of three special journal issues and an edited book published in the past decade on indigenous, local, and traditional knowledge and its interface with science. We identified broad themes in the literature related to: (1 similarities and differences between knowledge systems; (2 methods and processes of integration; (3 social contexts of integration; and (4 evaluation of knowledge. A minority of papers discuss a relationship between knowledge integration and social-ecological system resilience, but there remains a lack of clarity and empirical evidence for such a relationship that can help distinguish how indigenous knowledge and knowledge integration contribute most to resilience. Four critical features of knowledge integration are likely to enable a more productive and mutually beneficial relationship between indigenous and scientific knowledge: new frames for integration, greater cognizance of the social contexts of integration, expanded modes of knowledge evaluation, and involvement of inter-cultural "knowledge bridgers."

  20. EO Model for Tacit Knowledge Externalization in Socio-Technical Enterprises

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    Shreyas Suresh Rao

    2017-03-01

    Full Text Available Aim/Purpose: A vital business activity within socio-technical enterprises is tacit knowledge externalization, which elicits and explicates tacit knowledge of enterprise employees as external knowledge. The aim of this paper is to integrate diverse aspects of externalization through the Enterprise Ontology model. Background: Across two decades, researchers have explored various aspects of tacit knowledge externalization. However, from the existing works, it is revealed that there is no uniform representation of the externalization process, which has resulted in divergent and contradictory interpretations across the literature. Methodology\t: The Enterprise Ontology model is constructed step-wise through the conceptual and measurement views. While the conceptual view encompasses three patterns that model the externalization process, the measurement view employs certainty-factor model to empirically measure the outcome of the externalization process. Contribution: The paper contributes towards knowledge management literature in two ways. The first contribution is the Enterprise Ontology model that integrates diverse aspects of externalization. The second contribution is a Web application that validates the model through a case study in banking. Findings: The findings show that the Enterprise Ontology model and the patterns are pragmatic in externalizing the tacit knowledge of experts in a problem-solving scenario within a banking enterprise. Recommendations for Practitioners\t: Consider the diverse aspects (what, where, when, why, and how during the tacit knowledge externalization process. Future Research:\tTo extend the Enterprise Ontology model to include externalization from partially automated enterprise systems.