Expert Judgement Assessment & SCENT Ontological Analysis

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NICHERSU Iulian

2018-05-01

Full Text Available This study aims to provide insights in the starting point of the Horizon 2020 ECfunded project SCENT (Smart Toolbox for Εngaging Citizens into a People-Centric Observation Web Citizen Observatory (CO in terms of existing infrastructure, existing monitoring systems and some discussion on the existing legal and administrative framework that relate to flood monitoring and management in the area of Danube Delta. The methodology used in this approach is based on expert judgement and ontological analysis, using the information collected from the identified end-users of the SCENT toolbox. In this type of analysis the stages of flood monitoring and management that the experts are involved in are detailed. This is done through an Expert Judgement Assessment analysis. The latter is complemented by a set of Key Performance Indicators that the stakeholders have assessed and/or proposed for the evaluation of the SCENT demonstrations, for the impact of the project and finally for SCENT toolbox performance and usefulness. The second part of the study presents an analysis that attempts to map the interactions between different organizations and components of the existing monitoring systems in the Danube Delta case study. Expert Judgement (EJ allows to gain information from specialists in a specific field through a consultation process with one or more experts that have experience in similar and complementary topics. Expert judgment, expert estimates, or expert opinion are all terms that refer to the contents of the problem; estimates, outcomes, predictions, uncertainties, and their corresponding assumptions and conditions are all examples of expert judgment. Expert Judgement is affected by the process used to gather it. On the other hand, the ontological analysis comes to complete this study, by organizing and presenting the connections behind the flood management and land use systems in the three phases of the flood event.

Gene Ontology-Based Analysis of Zebrafish Omics Data Using the Web Tool Comparative Gene Ontology.

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Ebrahimie, Esmaeil; Fruzangohar, Mario; Moussavi Nik, Seyyed Hani; Newman, Morgan

2017-10-01

Gene Ontology (GO) analysis is a powerful tool in systems biology, which uses a defined nomenclature to annotate genes/proteins within three categories: "Molecular Function," "Biological Process," and "Cellular Component." GO analysis can assist in revealing functional mechanisms underlying observed patterns in transcriptomic, genomic, and proteomic data. The already extensive and increasing use of zebrafish for modeling genetic and other diseases highlights the need to develop a GO analytical tool for this organism. The web tool Comparative GO was originally developed for GO analysis of bacterial data in 2013 ( www.comparativego.com ). We have now upgraded and elaborated this web tool for analysis of zebrafish genetic data using GOs and annotations from the Gene Ontology Consortium.

Ontology-based representation and analysis of host-Brucella interactions.

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Lin, Yu; Xiang, Zuoshuang; He, Yongqun

2015-01-01

-Brucella interactions and implemented in IDOBRU. Current IDOBRU includes 3611 ontology terms. SPARQL queries identified many results that are critical to the host-Brucella interactions. For example, out of 269 protein virulence factors related to macrophage-Brucella interactions, 81 are critical to Brucella intracellular replication inside macrophages. A SPARQL query also identified 11 biological processes important for Brucella virulence. To systematically represent and analyze fundamental host-pathogen interaction mechanisms, we provided for the first time comprehensive ontological modeling of host-pathogen interactions using Brucella as the pathogen model. The methods and ontology representations used in our study are generic and can be broadened to study the interactions between hosts and other pathogens.

Constructing Ontology for Knowledge Sharing of Materials Failure Analysis

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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.

Inferring ontology graph structures using OWL reasoning

KAUST Repository

Rodriguez-Garcia, Miguel Angel

2018-01-05

Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies\\' semantic content remains a challenge.We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies\\' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph .Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

Inferring ontology graph structures using OWL reasoning.

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Rodríguez-García, Miguel Ángel; Hoehndorf, Robert

2018-01-05

Ontologies are representations of a conceptualization of a domain. Traditionally, ontologies in biology were represented as directed acyclic graphs (DAG) which represent the backbone taxonomy and additional relations between classes. These graphs are widely exploited for data analysis in the form of ontology enrichment or computation of semantic similarity. More recently, ontologies are developed in a formal language such as the Web Ontology Language (OWL) and consist of a set of axioms through which classes are defined or constrained. While the taxonomy of an ontology can be inferred directly from the axioms of an ontology as one of the standard OWL reasoning tasks, creating general graph structures from OWL ontologies that exploit the ontologies' semantic content remains a challenge. We developed a method to transform ontologies into graphs using an automated reasoner while taking into account all relations between classes. Searching for (existential) patterns in the deductive closure of ontologies, we can identify relations between classes that are implied but not asserted and generate graph structures that encode for a large part of the ontologies' semantic content. We demonstrate the advantages of our method by applying it to inference of protein-protein interactions through semantic similarity over the Gene Ontology and demonstrate that performance is increased when graph structures are inferred using deductive inference according to our method. Our software and experiment results are available at http://github.com/bio-ontology-research-group/Onto2Graph . Onto2Graph is a method to generate graph structures from OWL ontologies using automated reasoning. The resulting graphs can be used for improved ontology visualization and ontology-based data analysis.

Interoperability between phenotype and anatomy ontologies.

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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.

Differential Adverse Event Profiles Associated with BCG as a Preventive Tuberculosis Vaccine or Therapeutic Bladder Cancer Vaccine Identified by Comparative Ontology-Based VAERS and Literature Meta-Analysis.

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Jiangan Xie

Full Text Available M. bovis strain Bacillus Calmette-Guérin (BCG has been the only licensed live attenuated vaccine against tuberculosis (TB for nearly one century and has also been approved as a therapeutic vaccine for bladder cancer treatment since 1990. During its long time usage, different adverse events (AEs have been reported. However, the AEs associated with the BCG preventive TB vaccine and therapeutic cancer vaccine have not been systematically compared. In this study, we systematically collected various BCG AE data mined from the US VAERS database and PubMed literature reports, identified statistically significant BCG-associated AEs, and ontologically classified and compared these AEs related to these two types of BCG vaccine. From 397 VAERS BCG AE case reports, we identified 64 AEs statistically significantly associated with the BCG TB vaccine and 14 AEs with the BCG cancer vaccine. Our meta-analysis of 41 peer-reviewed journal reports identified 48 AEs associated with the BCG TB vaccine and 43 AEs associated with the BCG cancer vaccine. Among all identified AEs from VAERS and literature reports, 25 AEs belong to serious AEs. The Ontology of Adverse Events (OAE-based ontological hierarchical analysis indicated that the AEs associated with the BCG TB vaccine were enriched in immune system (e.g., lymphadenopathy and lymphadenitis, skin (e.g., skin ulceration and cyanosis, and respiratory system (e.g., cough and pneumonia; in contrast, the AEs associated with the BCG cancer vaccine mainly occurred in the urinary system (e.g., dysuria, pollakiuria, and hematuria. With these distinct AE profiles detected, this study also discovered three AEs (i.e., chills, pneumonia, and C-reactive protein increased shared by the BCG TB vaccine and bladder cancer vaccine. Furthermore, our deep investigation of 24 BCG-associated death cases from VAERS identified the important effects of age, vaccine co-administration, and immunosuppressive status on the final BCG

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.

Alignment of ICNP? 2.0 Ontology and a proposed INCP? Brazilian Ontology1

OpenAIRE

Carvalho, Carina Maris Gaspar; Cubas, Marcia Regina; Malucelli, Andreia; da N?brega, Maria Miriam Lima

2014-01-01

OBJECTIVE: to align the International Classification for Nursing Practice (ICNP®) Version 2.0 ontology and a proposed INCP® Brazilian Ontology.METHOD: document-based, exploratory and descriptive study, the empirical basis of which was provided by the ICNP® 2.0 Ontology and the INCP® Brazilian Ontology. The ontology alignment was performed using a computer tool with algorithms to identify correspondences between concepts, which were organized and analyzed according to their presence or absence...

Benchmarking the Applicability of Ontology in Geographic Object-Based Image Analysis

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Sachit Rajbhandari

2017-11-01

Full Text Available In Geographic Object-based Image Analysis (GEOBIA, identification of image objects is normally achieved using rule-based classification techniques supported by appropriate domain knowledge. However, GEOBIA currently lacks a systematic method to formalise the domain knowledge required for image object identification. Ontology provides a representation vocabulary for characterising domain-specific classes. This study proposes an ontological framework that conceptualises domain knowledge in order to support the application of rule-based classifications. The proposed ontological framework is tested with a landslide case study. The Web Ontology Language (OWL is used to construct an ontology in the landslide domain. The segmented image objects with extracted features are incorporated into the ontology as instances. The classification rules are written in Semantic Web Rule Language (SWRL and executed using a semantic reasoner to assign instances to appropriate landslide classes. Machine learning techniques are used to predict new threshold values for feature attributes in the rules. Our framework is compared with published work on landslide detection where ontology was not used for the image classification. Our results demonstrate that a classification derived from the ontological framework accords with non-ontological methods. This study benchmarks the ontological method providing an alternative approach for image classification in the case study of landslides.

Ontological Analysis of the Project Risk Management Concept ‘Risk’

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Uzulāns Juris

2018-02-01

Full Text Available The aim of the current research series is to examine the definitions of the concept ‘risk’ and analyze the concepts used in the definitions of ‘risk’ in the sources of these definitions in order to perform the ontological analysis of the concept of ‘risk’. Ontological and epistemological analysis of the concepts in the definition of the concept ‘risk’ was used to answer the question what ‘risk’ means in project management. This investigation represents a part of the research series where the ontological, epistemological and methodological analysis of project risk is performed with the aim to improve risk registers and risk management as a whole. In the previous studies the author analyzed the concept of ‘event’ that defines the content of the concept ‘risk’. The use of ‘event’ was analyzed in different sources to find out how the concept should be used. The ontological, epistemological and methodological analysis of the definitions of the concept ‘risk’ is the theoretical foundation for risk register creation because it is possible to create complete and understandable register for the participants of the project risk management process. The author believes that the conducted research helps establish confidence that ontological analysis is the method that together with the epistemological and methodological analysis provides opportunity to perform analysis of risk management sources aimed at improving risk management. The results of the study cannot be considered sufficient for deriving valid conclusions about project risk management and developing recommendations for improving risk management with regard to the content of the risk register. For valid conclusions and recommendations, a deeper research is needed which, first of all, would analyze a larger number of sources.

Where to Publish and Find Ontologies? A Survey of Ontology Libraries

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d'Aquin, Mathieu; Noy, Natalya F.

2011-01-01

One of the key promises of the Semantic Web is its potential to enable and facilitate data interoperability. The ability of data providers and application developers to share and reuse ontologies is a critical component of this data interoperability: if different applications and data sources use the same set of well defined terms for describing their domain and data, it will be much easier for them to “talk” to one another. Ontology libraries are the systems that collect ontologies from different sources and facilitate the tasks of finding, exploring, and using these ontologies. Thus ontology libraries can serve as a link in enabling diverse users and applications to discover, evaluate, use, and publish ontologies. In this paper, we provide a survey of the growing—and surprisingly diverse—landscape of ontology libraries. We highlight how the varying scope and intended use of the libraries a ects their features, content, and potential exploitation in applications. From reviewing eleven ontology libraries, we identify a core set of questions that ontology practitioners and users should consider in choosing an ontology library for finding ontologies or publishing their own. We also discuss the research challenges that emerge from this survey, for the developers of ontology libraries to address. PMID:22408576

Construction of mammographic examination process ontology using bottom-up hierarchical task analysis.

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Yagahara, Ayako; Yokooka, Yuki; Jiang, Guoqian; Tsuji, Shintarou; Fukuda, Akihisa; Nishimoto, Naoki; Kurowarabi, Kunio; Ogasawara, Katsuhiko

2018-03-01

Describing complex mammography examination processes is important for improving the quality of mammograms. It is often difficult for experienced radiologic technologists to explain the process because their techniques depend on their experience and intuition. In our previous study, we analyzed the process using a new bottom-up hierarchical task analysis and identified key components of the process. Leveraging the results of the previous study, the purpose of this study was to construct a mammographic examination process ontology to formally describe the relationships between the process and image evaluation criteria to improve the quality of mammograms. First, we identified and created root classes: task, plan, and clinical image evaluation (CIE). Second, we described an "is-a" relation referring to the result of the previous study and the structure of the CIE. Third, the procedural steps in the ontology were described using the new properties: "isPerformedBefore," "isPerformedAfter," and "isPerformedAfterIfNecessary." Finally, the relationships between tasks and CIEs were described using the "isAffectedBy" property to represent the influence of the process on image quality. In total, there were 219 classes in the ontology. By introducing new properties related to the process flow, a sophisticated mammography examination process could be visualized. In relationships between tasks and CIEs, it became clear that the tasks affecting the evaluation criteria related to positioning were greater in number than those for image quality. We developed a mammographic examination process ontology that makes knowledge explicit for a comprehensive mammography process. Our research will support education and help promote knowledge sharing about mammography examination expertise.

Extracting Cross-Ontology Weighted Association Rules from Gene Ontology Annotations.

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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.

BiNChE: a web tool and library for chemical enrichment analysis based on the ChEBI ontology.

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Moreno, Pablo; Beisken, Stephan; Harsha, Bhavana; Muthukrishnan, Venkatesh; Tudose, Ilinca; Dekker, Adriano; Dornfeldt, Stefanie; Taruttis, Franziska; Grosse, Ivo; Hastings, Janna; Neumann, Steffen; Steinbeck, Christoph

2015-02-21

Ontology-based enrichment analysis aids in the interpretation and understanding of large-scale biological data. Ontologies are hierarchies of biologically relevant groupings. Using ontology annotations, which link ontology classes to biological entities, enrichment analysis methods assess whether there is a significant over or under representation of entities for ontology classes. While many tools exist that run enrichment analysis for protein sets annotated with the Gene Ontology, there are only a few that can be used for small molecules enrichment analysis. We describe BiNChE, an enrichment analysis tool for small molecules based on the ChEBI Ontology. BiNChE displays an interactive graph that can be exported as a high-resolution image or in network formats. The tool provides plain, weighted and fragment analysis based on either the ChEBI Role Ontology or the ChEBI Structural Ontology. BiNChE aids in the exploration of large sets of small molecules produced within Metabolomics or other Systems Biology research contexts. The open-source tool provides easy and highly interactive web access to enrichment analysis with the ChEBI ontology tool and is additionally available as a standalone library.

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 ...

Initial implementation of a comparative data analysis ontology.

Science.gov (United States)

Prosdocimi, Francisco; Chisham, Brandon; Pontelli, Enrico; Thompson, Julie D; Stoltzfus, Arlin

2009-07-03

Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species) are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: "Operational Taxonomic Units" (OTUs), representing the entities to be compared; "character-state data" representing the observations compared among OTUs; "phylogenetic tree", representing the historical path of evolution among the entities; and "transitions", the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL), we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO). CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc.) that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

The mouse-human anatomy ontology mapping project.

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Hayamizu, Terry F; de Coronado, Sherri; Fragoso, Gilberto; Sioutos, Nicholas; Kadin, James A; Ringwald, Martin

2012-01-01

The overall objective of the Mouse-Human Anatomy Project (MHAP) was to facilitate the mapping and harmonization of anatomical terms used for mouse and human models by Mouse Genome Informatics (MGI) and the National Cancer Institute (NCI). The anatomy resources designated for this study were the Adult Mouse Anatomy (MA) ontology and the set of anatomy concepts contained in the NCI Thesaurus (NCIt). Several methods and software tools were identified and evaluated, then used to conduct an in-depth comparative analysis of the anatomy ontologies. Matches between mouse and human anatomy terms were determined and validated, resulting in a highly curated set of mappings between the two ontologies that has been used by other resources. These mappings will enable linking of data from mouse and human. As the anatomy ontologies have been expanded and refined, the mappings have been updated accordingly. Insights are presented into the overall process of comparing and mapping between ontologies, which may prove useful for further comparative analyses and ontology mapping efforts, especially those involving anatomy ontologies. Finally, issues concerning further development of the ontologies, updates to the mapping files, and possible additional applications and significance were considered. DATABASE URL: http://obofoundry.org/cgi-bin/detail.cgi?id=ma2ncit.

Gene dosage, expression, and ontology analysis identifies driver genes in the carcinogenesis and chemoradioresistance of cervical cancer.

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Malin Lando

2009-11-01

Full Text Available Integrative analysis of gene dosage, expression, and ontology (GO data was performed to discover driver genes in the carcinogenesis and chemoradioresistance of cervical cancers. Gene dosage and expression profiles of 102 locally advanced cervical cancers were generated by microarray techniques. Fifty-two of these patients were also analyzed with the Illumina expression method to confirm the gene expression results. An independent cohort of 41 patients was used for validation of gene expressions associated with clinical outcome. Statistical analysis identified 29 recurrent gains and losses and 3 losses (on 3p, 13q, 21q associated with poor outcome after chemoradiotherapy. The intratumor heterogeneity, assessed from the gene dosage profiles, was low for these alterations, showing that they had emerged prior to many other alterations and probably were early events in carcinogenesis. Integration of the alterations with gene expression and GO data identified genes that were regulated by the alterations and revealed five biological processes that were significantly overrepresented among the affected genes: apoptosis, metabolism, macromolecule localization, translation, and transcription. Four genes on 3p (RYBP, GBE1 and 13q (FAM48A, MED4 correlated with outcome at both the gene dosage and expression level and were satisfactorily validated in the independent cohort. These integrated analyses yielded 57 candidate drivers of 24 genetic events, including novel loci responsible for chemoradioresistance. Further mapping of the connections among genetic events, drivers, and biological processes suggested that each individual event stimulates specific processes in carcinogenesis through the coordinated control of multiple genes. The present results may provide novel therapeutic opportunities of both early and advanced stage cervical cancers.

Fast gene ontology based clustering for microarray experiments.

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Ovaska, Kristian; Laakso, Marko; Hautaniemi, Sampsa

2008-11-21

Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

Ontology-Based Approach to Social Data Sentiment Analysis: Detection of Adolescent Depression Signals.

Science.gov (United States)

Jung, Hyesil; Park, Hyeoun-Ae; Song, Tae-Min

2017-07-24

Social networking services (SNSs) contain abundant information about the feelings, thoughts, interests, and patterns of behavior of adolescents that can be obtained by analyzing SNS postings. An ontology that expresses the shared concepts and their relationships in a specific field could be used as a semantic framework for social media data analytics. The aim of this study was to refine an adolescent depression ontology and terminology as a framework for analyzing social media data and to evaluate description logics between classes and the applicability of this ontology to sentiment analysis. The domain and scope of the ontology were defined using competency questions. The concepts constituting the ontology and terminology were collected from clinical practice guidelines, the literature, and social media postings on adolescent depression. Class concepts, their hierarchy, and the relationships among class concepts were defined. An internal structure of the ontology was designed using the entity-attribute-value (EAV) triplet data model, and superclasses of the ontology were aligned with the upper ontology. Description logics between classes were evaluated by mapping concepts extracted from the answers to frequently asked questions (FAQs) onto the ontology concepts derived from description logic queries. The applicability of the ontology was validated by examining the representability of 1358 sentiment phrases using the ontology EAV model and conducting sentiment analyses of social media data using ontology class concepts. We developed an adolescent depression ontology that comprised 443 classes and 60 relationships among the classes; the terminology comprised 1682 synonyms of the 443 classes. In the description logics test, no error in relationships between classes was found, and about 89% (55/62) of the concepts cited in the answers to FAQs mapped onto the ontology class. Regarding applicability, the EAV triplet models of the ontology class represented about 91

EDAM: an ontology of bioinformatics operations, types of data and identifiers, topics and formats

Science.gov (United States)

Ison, Jon; Kalaš, Matúš; Jonassen, Inge; Bolser, Dan; Uludag, Mahmut; McWilliam, Hamish; Malone, James; Lopez, Rodrigo; Pettifer, Steve; Rice, Peter

2013-01-01

Motivation: Advancing the search, publication and integration of bioinformatics tools and resources demands consistent machine-understandable descriptions. A comprehensive ontology allowing such descriptions is therefore required. Results: EDAM is an ontology of bioinformatics operations (tool or workflow functions), types of data and identifiers, application domains and data formats. EDAM supports semantic annotation of diverse entities such as Web services, databases, programmatic libraries, standalone tools, interactive applications, data schemas, datasets and publications within bioinformatics. EDAM applies to organizing and finding suitable tools and data and to automating their integration into complex applications or workflows. It includes over 2200 defined concepts and has successfully been used for annotations and implementations. Availability: The latest stable version of EDAM is available in OWL format from http://edamontology.org/EDAM.owl and in OBO format from http://edamontology.org/EDAM.obo. It can be viewed online at the NCBO BioPortal and the EBI Ontology Lookup Service. For documentation and license please refer to http://edamontology.org. This article describes version 1.2 available at http://edamontology.org/EDAM_1.2.owl. Contact: jison@ebi.ac.uk PMID:23479348

Initial Implementation of a comparative Data Analysis Ontology

Directory of Open Access Journals (Sweden)

Francisco Prosdocimi

2009-01-01

Full Text Available Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: “Operational Taxonomic Units” (OTUs, representing the entities to be compared; “character-state data” representing the observations compared among OTUs; “phylogenetic tree”, representing the historical path of evolution among the entities; and “transitions”, the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL, we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO. CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc. that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

Initial Implementation of a Comparative Data Analysis Ontology

Directory of Open Access Journals (Sweden)

Francisco Prosdocimi

2009-07-01

Full Text Available Comparative analysis is used throughout biology. When entities under comparison (e.g. proteins, genomes, species are related by descent, evolutionary theory provides a framework that, in principle, allows N-ary comparisons of entities, while controlling for non-independence due to relatedness. Powerful software tools exist for specialized applications of this approach, yet it remains under-utilized in the absence of a unifying informatics infrastructure. A key step in developing such an infrastructure is the definition of a formal ontology. The analysis of use cases and existing formalisms suggests that a significant component of evolutionary analysis involves a core problem of inferring a character history, relying on key concepts: “Operational Taxonomic Units” (OTUs, representing the entities to be compared; “character-state data” representing the observations compared among OTUs; “phylogenetic tree”, representing the historical path of evolution among the entities; and “transitions”, the inferred evolutionary changes in states of characters that account for observations. Using the Web Ontology Language (OWL, we have defined these and other fundamental concepts in a Comparative Data Analysis Ontology (CDAO. CDAO has been evaluated for its ability to represent token data sets and to support simple forms of reasoning. With further development, CDAO will provide a basis for tools (for semantic transformation, data retrieval, validation, integration, etc. that make it easier for software developers and biomedical researchers to apply evolutionary methods of inference to diverse types of data, so as to integrate this powerful framework for reasoning into their research.

OAE: The Ontology of Adverse Events.

Science.gov (United States)

He, Yongqun; Sarntivijai, Sirarat; Lin, Yu; Xiang, Zuoshuang; Guo, Abra; Zhang, Shelley; Jagannathan, Desikan; Toldo, Luca; Tao, Cui; Smith, Barry

2014-01-01

A medical intervention is a medical procedure or application intended to relieve or prevent illness or injury. Examples of medical interventions include vaccination and drug administration. After a medical intervention, adverse events (AEs) may occur which lie outside the intended consequences of the intervention. The representation and analysis of AEs are critical to the improvement of public health. The Ontology of Adverse Events (OAE), previously named Adverse Event Ontology (AEO), is a community-driven ontology developed to standardize and integrate data relating to AEs arising subsequent to medical interventions, as well as to support computer-assisted reasoning. OAE has over 3,000 terms with unique identifiers, including terms imported from existing ontologies and more than 1,800 OAE-specific terms. In OAE, the term 'adverse event' denotes a pathological bodily process in a patient that occurs after a medical intervention. Causal adverse events are defined by OAE as those events that are causal consequences of a medical intervention. OAE represents various adverse events based on patient anatomic regions and clinical outcomes, including symptoms, signs, and abnormal processes. OAE has been used in the analysis of several different sorts of vaccine and drug adverse event data. For example, using the data extracted from the Vaccine Adverse Event Reporting System (VAERS), OAE was used to analyse vaccine adverse events associated with the administrations of different types of influenza vaccines. OAE has also been used to represent and classify the vaccine adverse events cited in package inserts of FDA-licensed human vaccines in the USA. OAE is a biomedical ontology that logically defines and classifies various adverse events occurring after medical interventions. OAE has successfully been applied in several adverse event studies. The OAE ontological framework provides a platform for systematic representation and analysis of adverse events and of the factors (e

Semi-automated ontology generation and evolution

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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

An ontological approach to identifying cases of chronic kidney disease from routine primary care data: a cross-sectional study.

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Cole, Nicholas I; Liyanage, Harshana; Suckling, Rebecca J; Swift, Pauline A; Gallagher, Hugh; Byford, Rachel; Williams, John; Kumar, Shankar; de Lusignan, Simon

2018-04-10

Accurately identifying cases of chronic kidney disease (CKD) from primary care data facilitates the management of patients, and is vital for surveillance and research purposes. Ontologies provide a systematic and transparent basis for clinical case definition and can be used to identify clinical codes relevant to all aspects of CKD care and its diagnosis. We used routinely collected primary care data from the Royal College of General Practitioners Research and Surveillance Centre. A domain ontology was created and presented in Ontology Web Language (OWL). The identification and staging of CKD was then carried out using two parallel approaches: (1) clinical coding consistent with a diagnosis of CKD; (2) laboratory-confirmed CKD, based on estimated glomerular filtration rate (eGFR) or the presence of proteinuria. The study cohort comprised of 1.2 million individuals aged 18 years and over. 78,153 (6.4%) of the population had CKD on the basis of an eGFR of < 60 mL/min/1.73m 2 , and a further 7366 (0.6%) individuals were identified as having CKD due to proteinuria. 19,504 (1.6%) individuals without laboratory-confirmed CKD had a clinical code consistent with the diagnosis. In addition, a subset of codes allowed for 1348 (0.1%) individuals receiving renal replacement therapy to be identified. Finding cases of CKD from primary care data using an ontological approach may have greater sensitivity than less comprehensive methods, particularly for identifying those receiving renal replacement therapy or with CKD stages 1 or 2. However, the possibility of inaccurate coding may limit the specificity of this method.

Toxicology ontology perspectives.

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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.

Fast Gene Ontology based clustering for microarray experiments

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Ovaska Kristian

2008-11-01

Full Text Available Abstract Background Analysis of a microarray experiment often results in a list of hundreds of disease-associated genes. In order to suggest common biological processes and functions for these genes, Gene Ontology annotations with statistical testing are widely used. However, these analyses can produce a very large number of significantly altered biological processes. Thus, it is often challenging to interpret GO results and identify novel testable biological hypotheses. Results We present fast software for advanced gene annotation using semantic similarity for Gene Ontology terms combined with clustering and heat map visualisation. The methodology allows rapid identification of genes sharing the same Gene Ontology cluster. Conclusion Our R based semantic similarity open-source package has a speed advantage of over 2000-fold compared to existing implementations. From the resulting hierarchical clustering dendrogram genes sharing a GO term can be identified, and their differences in the gene expression patterns can be seen from the heat map. These methods facilitate advanced annotation of genes resulting from data analysis.

An Ontology for State Analysis: Formalizing the Mapping to SysML

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Wagner, David A.; Bennett, Matthew B.; Karban, Robert; Rouquette, Nicolas; Jenkins, Steven; Ingham, Michel

2012-01-01

State Analysis is a methodology developed over the last decade for architecting, designing and documenting complex control systems. Although it was originally conceived for designing robotic spacecraft, recent applications include the design of control systems for large ground-based telescopes. The European Southern Observatory (ESO) began a project to design the European Extremely Large Telescope (E-ELT), which will require coordinated control of over a thousand articulated mirror segments. The designers are using State Analysis as a methodology and the Systems Modeling Language (SysML) as a modeling and documentation language in this task. To effectively apply the State Analysis methodology in this context it became necessary to provide ontological definitions of the concepts and relations in State Analysis and greater flexibility through a mapping of State Analysis into a practical extension of SysML. The ontology provides the formal basis for verifying compliance with State Analysis semantics including architectural constraints. The SysML extension provides the practical basis for applying the State Analysis methodology with SysML tools. This paper will discuss the method used to develop these formalisms (the ontology), the formalisms themselves, the mapping to SysML and approach to using these formalisms to specify a control system and enforce architectural constraints in a SysML model.

Multicriteria analysis of ontologically represented information

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Wasielewska, K.; Ganzha, M.; Paprzycki, M.; Bǎdicǎ, C.; Ivanovic, M.; Lirkov, I.

2014-11-01

Our current work concerns the development of a decision support system for the software selection problem. The main idea is to utilize expert knowledge to help the user in selecting the best software / method / computational resource to solve a computational problem. Obviously, this involves multicriterial decision making and the key open question is: which method to choose. The context of the work is provided by the Agents in Grid (AiG) project, where the software selection (and thus multicriterial analysis) is to be realized when all information concerning the problem, the hardware and the software is ontologically represented. Initially, we have considered the Analytical Hierarchy Process (AHP), which is well suited for the hierarchical data structures (e.g., such that have been formulated in terms of ontologies). However, due to its well-known shortcomings, we have decided to extend our search for the multicriterial analysis method best suited for the problem in question. In this paper we report results of our search, which involved: (i) TOPSIS (Technique for Order Preference by Similarity to Ideal Solution), (ii) PROMETHEE, and (iii) GRIP (Generalized Regression with Intensities of Preference). We also briefly argue why other methods have not been considered as valuable candidates.

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

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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

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...

The Social Ontology of the Film "Avatar." Anthropological Analysis

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Marija Krstić

2016-02-01

Full Text Available Review of a book by Nina Kulenović. The Social Ontology of the Film "Avatar." Anthropological Analysis. 2011. Belgrade: University of Belgrade - Faculty of Philosophy, Department of Ethnology and Anthropology

Sentiment analysis and ontology engineering an environment of computational intelligence

CERN Document Server

Chen, Shyi-Ming

2016-01-01

This edited volume provides the reader with a fully updated, in-depth treatise on the emerging principles, conceptual underpinnings, algorithms and practice of Computational Intelligence in the realization of concepts and implementation of models of sentiment analysis and ontology –oriented engineering. The volume involves studies devoted to key issues of sentiment analysis, sentiment models, and ontology engineering. The book is structured into three main parts. The first part offers a comprehensive and prudently structured exposure to the fundamentals of sentiment analysis and natural language processing. The second part consists of studies devoted to the concepts, methodologies, and algorithmic developments elaborating on fuzzy linguistic aggregation to emotion analysis, carrying out interpretability of computational sentiment models, emotion classification, sentiment-oriented information retrieval, a methodology of adaptive dynamics in knowledge acquisition. The third part includes a plethora of applica...

Ontology Design of Influential People Identification Using Centrality

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Maulana Awangga, Rolly; Yusril, Muhammad; Setyawan, Helmi

2018-04-01

Identifying influential people as a node in a graph theory commonly calculated by social network analysis. The social network data has the user as node and edge as relation forming a friend relation graph. This research is conducting different meaning of every nodes relation in the social network. Ontology was perfect match science to describe the social network data as conceptual and domain. Ontology gives essential relationship in a social network more than a current graph. Ontology proposed as a standard for knowledge representation for the semantic web by World Wide Web Consortium. The formal data representation use Resource Description Framework (RDF) and Web Ontology Language (OWL) which is strategic for Open Knowledge-Based website data. Ontology used in the semantic description for a relationship in the social network, it is open to developing semantic based relationship ontology by adding and modifying various and different relationship to have influential people as a conclusion. This research proposes a model using OWL and RDF for influential people identification in the social network. The study use degree centrality, between ness centrality, and closeness centrality measurement for data validation. As a conclusion, influential people identification in Facebook can use proposed Ontology model in the Group, Photos, Photo Tag, Friends, Events and Works data.

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.

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

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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.

An ontology for major histocompatibility restriction.

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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.

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.

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

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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

An ontological analysis of the electrocardiogram - DOI: 10.3395/reciis.v3i1.242en

Directory of Open Access Journals (Sweden)

Bernardo Gonçalves

2009-04-01

Full Text Available Bioinformatics has been a fertile field for the application of the discipline of formal ontology. The principled representation of biomedical entities has increasingly supported biological research, with direct benefits ranging from the reformulation of medical terminologies to the introduction of new perspectives for enhanced models of Electronic Health Records (EHR. This paper introduces an application-independent ontological analysis of the electrocardiogram (ECG grounded in the Unified Foundational Ontology. With the objective of investigating the phenomena underlying this cardiological exam, we deal with the sub-domains of human heart electrophysiology and anatomy. We then outline an ECG Ontology built upon the OBO Relation Ontology. In addition, the domain ontology sketched here takes inspiration both in the Foundational Model of Anatomy and in the Ontology of Functions proposed under the auspices of the General Formal Ontology (GFO research program.

The role of ontologies in biological and biomedical research: a functional perspective

KAUST Repository

Hoehndorf, Robert

2015-04-10

Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications.

The role of ontologies in biological and biomedical research: a functional perspective

KAUST Repository

Hoehndorf, Robert; Schofield, P. N.; Gkoutos, G. V.

2015-01-01

Ontologies are widely used in biological and biomedical research. Their success lies in their combination of four main features present in almost all ontologies: provision of standard identifiers for classes and relations that represent the phenomena within a domain; provision of a vocabulary for a domain; provision of metadata that describes the intended meaning of the classes and relations in ontologies; and the provision of machine-readable axioms and definitions that enable computational access to some aspects of the meaning of classes and relations. While each of these features enables applications that facilitate data integration, data access and analysis, a great potential lies in the possibility of combining these four features to support integrative analysis and interpretation of multimodal data. Here, we provide a functional perspective on ontologies in biology and biomedicine, focusing on what ontologies can do and describing how they can be used in support of integrative research. We also outline perspectives for using ontologies in data-driven science, in particular their application in structured data mining and machine learning applications.

Biomedical ontologies: toward scientific debate.

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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.

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

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Viti Federica

2008-04-01

Full Text Available Abstract Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes.

How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects.

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Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A; Noy, Natalya F

2013-05-01

Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product . In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches.

How Ontologies are Made: Studying the Hidden Social Dynamics Behind Collaborative Ontology Engineering Projects

Science.gov (United States)

Strohmaier, Markus; Walk, Simon; Pöschko, Jan; Lamprecht, Daniel; Tudorache, Tania; Nyulas, Csongor; Musen, Mark A.; Noy, Natalya F.

2013-01-01

Traditionally, evaluation methods in the field of semantic technologies have focused on the end result of ontology engineering efforts, mainly, on evaluating ontologies and their corresponding qualities and characteristics. This focus has led to the development of a whole arsenal of ontology-evaluation techniques that investigate the quality of ontologies as a product. In this paper, we aim to shed light on the process of ontology engineering construction by introducing and applying a set of measures to analyze hidden social dynamics. We argue that especially for ontologies which are constructed collaboratively, understanding the social processes that have led to its construction is critical not only in understanding but consequently also in evaluating the ontology. With the work presented in this paper, we aim to expose the texture of collaborative ontology engineering processes that is otherwise left invisible. Using historical change-log data, we unveil qualitative differences and commonalities between different collaborative ontology engineering projects. Explaining and understanding these differences will help us to better comprehend the role and importance of social factors in collaborative ontology engineering projects. We hope that our analysis will spur a new line of evaluation techniques that view ontologies not as the static result of deliberations among domain experts, but as a dynamic, collaborative and iterative process that needs to be understood, evaluated and managed in itself. We believe that advances in this direction would help our community to expand the existing arsenal of ontology evaluation techniques towards more holistic approaches. PMID:24311994

Approaching the axiomatic enrichment of the Gene Ontology from a lexical perspective.

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Quesada-Martínez, Manuel; Mikroyannidi, Eleni; Fernández-Breis, Jesualdo Tomás; Stevens, Robert

2015-09-01

The main goal of this work is to measure how lexical regularities in biomedical ontology labels can be used for the automatic creation of formal relationships between classes, and to evaluate the results of applying our approach to the Gene Ontology (GO). In recent years, we have developed a method for the lexical analysis of regularities in biomedical ontology labels, and we showed that the labels can present a high degree of regularity. In this work, we extend our method with a cross-products extension (CPE) metric, which estimates the potential interest of a specific regularity for axiomatic enrichment in the lexical analysis, using information on exact matches in external ontologies. The GO consortium recently enriched the GO by using so-called cross-product extensions. Cross-products are generated by establishing axioms that relate a given GO class with classes from the GO or other biomedical ontologies. We apply our method to the GO and study how its lexical analysis can identify and reconstruct the cross-products that are defined by the GO consortium. The label of the classes of the GO are highly regular in lexical terms, and the exact matches with labels of external ontologies affect 80% of the GO classes. The CPE metric reveals that 31.48% of the classes that exhibit regularities have fragments that are classes into two external ontologies that are selected for our experiment, namely, the Cell Ontology and the Chemical Entities of Biological Interest ontology, and 18.90% of them are fully decomposable into smaller parts. Our results show that the CPE metric permits our method to detect GO cross-product extensions with a mean recall of 62% and a mean precision of 28%. The study is completed with an analysis of false positives to explain this precision value. We think that our results support the claim that our lexical approach can contribute to the axiomatic enrichment of biomedical ontologies and that it can provide new insights into the engineering of

Geo-Ontologies Are Scale Dependent

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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

Formal Ontologies and Uncertainty. In Geographical Knowledge

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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.

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

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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.

Ontology Update in the Cognitive Model of Ontology Learning

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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.

Invariance as a Tool for Ontology of Information

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Marcin J. Schroeder

2016-03-01

Full Text Available Attempts to answer questions regarding the ontological status of information are frequently based on the assumption that information should be placed within an already existing framework of concepts of established ontological statuses related to science, in particular to physics. However, many concepts of physics have undetermined or questionable ontological foundations. We can look for a solution in the recognition of the fundamental role of invariance with respect to a change of reference frame and to other transformations as a criterion for objective existence. The importance of invariance (symmetry as a criterion for a primary ontological status can be identified in the methodology of physics from its beginnings in the work of Galileo, to modern classifications of elementary particles. Thus, the study of the invariance of the theoretical description of information is proposed as the first step towards ontology of information. With the exception of only a few works among publications which set the paradigm of information studies, the issues of invariance were neglected. Orthodox analysis of information lacks conceptual framework for the study of invariance. The present paper shows how invariance can be formalized for the definition of information and, accompanying it, mathematical formalism proposed by the author in his earlier publications.

Validation test case generation based on safety analysis ontology

International Nuclear Information System (INIS)

Fan, Chin-Feng; Wang, Wen-Shing

2012-01-01

Highlights: ► Current practice in validation test case generation for nuclear system is mainly ad hoc. ► This study designs a systematic approach to generate validation test cases from a Safety Analysis Report. ► It is based on a domain-specific ontology. ► Test coverage criteria have been defined and satisfied. ► A computerized toolset has been implemented to assist the proposed approach. - Abstract: Validation tests in the current nuclear industry practice are typically performed in an ad hoc fashion. This study presents a systematic and objective method of generating validation test cases from a Safety Analysis Report (SAR). A domain-specific ontology was designed and used to mark up a SAR; relevant information was then extracted from the marked-up document for use in automatically generating validation test cases that satisfy the proposed test coverage criteria; namely, single parameter coverage, use case coverage, abnormal condition coverage, and scenario coverage. The novelty of this technique is its systematic rather than ad hoc test case generation from a SAR to achieve high test coverage.

Leave-two-out stability of ontology learning algorithm

International Nuclear Information System (INIS)

Wu, Jianzhang; Yu, Xiao; Zhu, Linli; Gao, Wei

2016-01-01

Ontology is a semantic analysis and calculation model, which has been applied to many subjects. Ontology similarity calculation and ontology mapping are employed as machine learning approaches. The purpose of this paper is to study the leave-two-out stability of ontology learning algorithm. Several leave-two-out stabilities are defined in ontology learning setting and the relationship among these stabilities are presented. Furthermore, the results manifested reveal that leave-two-out stability is a sufficient and necessary condition for ontology learning algorithm.

Ontological engineering versus metaphysics

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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.

DEPONTO: A Reusable Dependability Domain Ontology

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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.

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

Building a biomedical ontology recommender web service

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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.

One Song, Many Works: A Pluralist Ontology of Rock

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Dan Burkett

2016-01-01

Full Text Available A number of attempts have been made to construct a plausible ontology of rock music. Each of these ontologies identifies a single type of ontological entity as the “work” in rock music. Yet, all the suggestions advanced to date fail to capture some important considerations about how we engage with music of this tradition. This prompted Lee Brown to advocate a healthy skepticism of higher-order musical ontologies. I argue here that we should instead embrace a pluralist ontology of rock, an ontology that recognizes more than one kind of entity as “the work” in rock music. I contend that this approach has a number of advantages over other ontologies of rock, including that of allowing us to make some comparisons across ontological kinds.

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

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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.

The Human Phenotype Ontology in 2017

International Nuclear Information System (INIS)

Köhler, Sebastian; Vasilevsky, Nicole A.; Engelstad, Mark; Foster, Erin; McMurry, Julie

2016-01-01

Deep phenotyping has been defined as the precise and comprehensive analysis of phenotypic abnormalities in which the individual components of the phenotype are observed and described. The three components of the Human PhenotypeOntology (HPO; www.human-phenotype-ontology.org) project are the phenotype vocabulary, disease-phenotype annotations and the algorithms that operate on these. These components are being used for computational deep phenotyping and precision medicine as well as integration of clinical data into translational research. The HPO is being increasingly adopted as a standard for phenotypic abnormalities by diverse groups such as international rare disease organizations, registries, clinical labs, biomedical resources, and clinical software tools and will thereby contribute toward nascent efforts at global data exchange for identifying disease etiologies. This update article reviews the progress of the HPO project since the debut Nucleic Acids Research database article in 2014, including specific areas of expansion such as common (complex) disease, new algorithms for phenotype driven genomic discovery and diagnostics, integration of cross-species mapping efforts with the Mammalian Phenotype Ontology, an improved quality control pipeline, and the addition of patient-friendly terminology.

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

The MMI Device Ontology: Enabling Sensor Integration

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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

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.

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

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Skene JH Pate

2007-09-01

Full Text Available Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to rapidly search for and browse ontology terms. OntologyWidget can easily be embedded in other web-based applications. OntologyWidget is written using AJAX (Asynchronous JavaScript and XML and has two related elements. The first is a dynamic auto-complete ontology search feature. As a user enters characters into the search box, the appropriate ontology is queried remotely for terms that match the typed-in text, and the query results populate a drop-down list with all potential matches. Upon selection of a term from the list, the user can locate this term within a generic and dynamic ontology browser, which comprises the second element of the tool. The ontology browser shows the paths from a selected term to the root as well as parent/child tree hierarchies. We have implemented web services at the Stanford Microarray Database (SMD, which provide the OntologyWidget with access to over 40 ontologies from the Open Biological Ontology (OBO website 1. Each ontology is updated weekly. Adopters of the OntologyWidget can either use SMD's web services, or elect to rely on their own. Deploying the OntologyWidget can be accomplished in three simple steps: (1 install Apache Tomcat 2 on one's web server, (2 download and install the OntologyWidget servlet stub that provides access to the SMD ontology web services, and (3 create an html (HyperText Markup Language file that refers to the OntologyWidget using a simple, well-defined format. Conclusion We have developed Ontology

The Development of Ontology from Multiple Databases

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Kasim, Shahreen; Aswa Omar, Nurul; Fudzee, Mohd Farhan Md; Azhar Ramli, Azizul; Aizi Salamat, Mohamad; Mahdin, Hairulnizam

2017-08-01

The area of halal industry is the fastest growing global business across the world. The halal food industry is thus crucial for Muslims all over the world as it serves to ensure them that the food items they consume daily are syariah compliant. Currently, ontology has been widely used in computer sciences area such as web on the heterogeneous information processing, semantic web, and information retrieval. However, ontology has still not been used widely in the halal industry. Today, Muslim community still have problem to verify halal status for products in the market especially foods consisting of E number. This research tried to solve problem in validating the halal status from various halal sources. There are various chemical ontology from multilple databases found to help this ontology development. The E numbers in this chemical ontology are codes for chemicals that can be used as food additives. With this E numbers ontology, Muslim community could identify and verify the halal status effectively for halal products in the market.

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.

Discovering beaten paths in collaborative ontology-engineering projects using Markov chains.

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Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A; Noy, Natalya F

2014-10-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50,000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology

Discovering Beaten Paths in Collaborative Ontology-Engineering Projects using Markov Chains

Science.gov (United States)

Walk, Simon; Singer, Philipp; Strohmaier, Markus; Tudorache, Tania; Musen, Mark A.; Noy, Natalya F.

2014-01-01

Biomedical taxonomies, thesauri and ontologies in the form of the International Classification of Diseases as a taxonomy or the National Cancer Institute Thesaurus as an OWL-based ontology, play a critical role in acquiring, representing and processing information about human health. With increasing adoption and relevance, biomedical ontologies have also significantly increased in size. For example, the 11th revision of the International Classification of Diseases, which is currently under active development by the World Health Organization contains nearly 50, 000 classes representing a vast variety of different diseases and causes of death. This evolution in terms of size was accompanied by an evolution in the way ontologies are engineered. Because no single individual has the expertise to develop such large-scale ontologies, ontology-engineering projects have evolved from small-scale efforts involving just a few domain experts to large-scale projects that require effective collaboration between dozens or even hundreds of experts, practitioners and other stakeholders. Understanding the way these different stakeholders collaborate will enable us to improve editing environments that support such collaborations. In this paper, we uncover how large ontology-engineering projects, such as the International Classification of Diseases in its 11th revision, unfold by analyzing usage logs of five different biomedical ontology-engineering projects of varying sizes and scopes using Markov chains. We discover intriguing interaction patterns (e.g., which properties users frequently change after specific given ones) that suggest that large collaborative ontology-engineering projects are governed by a few general principles that determine and drive development. From our analysis, we identify commonalities and differences between different projects that have implications for project managers, ontology editors, developers and contributors working on collaborative ontology

Crowdsourcing the verification of relationships in biomedical ontologies.

Science.gov (United States)

Mortensen, Jonathan M; Musen, Mark A; Noy, Natalya F

2013-01-01

Biomedical ontologies are often large and complex, making ontology development and maintenance a challenge. To address this challenge, scientists use automated techniques to alleviate the difficulty of ontology development. However, for many ontology-engineering tasks, human judgment is still necessary. Microtask crowdsourcing, wherein human workers receive remuneration to complete simple, short tasks, is one method to obtain contributions by humans at a large scale. Previously, we developed and refined an effective method to verify ontology hierarchy using microtask crowdsourcing. In this work, we report on applying this method to find errors in the SNOMED CT CORE subset. By using crowdsourcing via Amazon Mechanical Turk with a Bayesian inference model, we correctly verified 86% of the relations from the CORE subset of SNOMED CT in which Rector and colleagues previously identified errors via manual inspection. Our results demonstrate that an ontology developer could deploy this method in order to audit large-scale ontologies quickly and relatively cheaply.

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

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

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.

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)

Feature-opinion pair identification of product reviews in Chinese: a domain ontology modeling method

Science.gov (United States)

Yin, Pei; Wang, Hongwei; Guo, Kaiqiang

2013-03-01

With the emergence of the new economy based on social media, a great amount of consumer feedback on particular products are conveyed through wide-spreading product online reviews, making opinion mining a growing interest for both academia and industry. According to the characteristic mode of expression in Chinese, this research proposes an ontology-based linguistic model to identify the basic appraisal expression in Chinese product reviews-"feature-opinion pair (FOP)." The product-oriented domain ontology is constructed automatically at first, then algorithms to identify FOP are designed by mapping product features and opinions to the conceptual space of the domain ontology, and finally comparative experiments are conducted to evaluate the model. Experimental results indicate that the performance of the proposed approach in this paper is efficient in obtaining a more accurate result compared to the state-of-art algorithms. Furthermore, through identifying and analyzing FOPs, the unstructured product reviews are converted into structured and machine-sensible expression, which provides valuable information for business application. This paper contributes to the related research in opinion mining by developing a solid foundation for further sentiment analysis at a fine-grained level and proposing a general way for automatic ontology construction.

There is no quantum ontology without classical ontology

Energy Technology Data Exchange (ETDEWEB)

Fink, Helmut [Institut fuer Theoretische Physik, Univ. Erlangen-Nuernberg (Germany)

2011-07-01

The relation between quantum physics and classical physics is still under debate. In his recent book ''Rational Reconstructions of Modern Physics'', Peter Mittelstaedt explores a route from classical to quantum mechanics by reduction and elimination of (some of) the ontological hypotheses underlying classical mechanics. While, according to Mittelstaedt, classical mechanics describes a fictitious world that does not exist in reality, he claims to achieve a universal quantum ontology that can be improved by incorporating unsharp properties and equipped with Planck's constant without any need to refer to classical concepts. In this talk, we argue that quantum ontology in Mittelstaedt's sense is not enough. Quantum ontology can never be universal as long as the difference between potential and real properties is not represented adequately. Quantum properties are potential, not (yet) real, be they sharp or unsharp. Hence, preparation and measurement presuppose classical concepts, even in quantum theory. We end up with a classical-quantum sandwich ontology, which is still less extravagant than Bohmian or many-worlds ontologies are.

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.

Prioritising lexical patterns to increase axiomatisation in biomedical ontologies. The role of localisation and modularity.

Science.gov (United States)

Quesada-Martínez, M; Fernández-Breis, J T; Stevens, R; Mikroyannidi, E

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". In previous work, we have defined methods for the extraction of lexical patterns from labels as an initial step towards semi-automatic ontology enrichment methods. Our previous findings revealed that many biomedical ontologies could benefit from enrichment methods using lexical patterns as a starting point.Here, we aim to identify which lexical patterns are appropriate for ontology enrichment, driving its analysis by metrics to prioritised the patterns. We propose metrics for suggesting which lexical regularities should be the starting point to enrich complex ontologies. Our method determines the relevance of a lexical pattern by measuring its locality in the ontology, that is, the distance between the classes associated with the pattern, and the distribution of the pattern in a certain module of the ontology. The methods have been applied to four significant biomedical ontologies including the Gene Ontology and SNOMED CT. The metrics provide information about the engineering of the ontologies and the relevance of the patterns. Our method enables the suggestion of links between classes that are not made explicit in the ontology. We propose a prioritisation of the lexical patterns found in the analysed ontologies. The locality and distribution of lexical patterns offer insights into the further engineering of the ontology. Developers can use this information to improve the axiomatisation of their ontologies.

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.

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.

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

Epistemology and ontology in core ontologies: FOLaw and LRI-Core, two core ontologies for law

NARCIS (Netherlands)

Breukers, J.A.P.J.; Hoekstra, R.J.

2004-01-01

For more than a decade constructing ontologies for legal domains, we, at the Leibniz Center for Law, felt really the need to develop a core ontology for law that would enable us to re-use the common denominator of the various legal domains. In this paper we present two core ontologies for law. The

Is the crowd better as an assistant or a replacement in ontology engineering? An exploration through the lens of the Gene Ontology.

Science.gov (United States)

Mortensen, Jonathan M; Telis, Natalie; Hughey, Jacob J; Fan-Minogue, Hua; Van Auken, Kimberly; Dumontier, Michel; Musen, Mark A

2016-04-01

Biomedical ontologies contain errors. Crowdsourcing, defined as taking a job traditionally performed by a designated agent and outsourcing it to an undefined large group of people, provides scalable access to humans. Therefore, the crowd has the potential to overcome the limited accuracy and scalability found in current ontology quality assurance approaches. Crowd-based methods have identified errors in SNOMED CT, a large, clinical ontology, with an accuracy similar to that of experts, suggesting that crowdsourcing is indeed a feasible approach for identifying ontology errors. This work uses that same crowd-based methodology, as well as a panel of experts, to verify a subset of the Gene Ontology (200 relationships). Experts identified 16 errors, generally in relationships referencing acids and metals. The crowd performed poorly in identifying those errors, with an area under the receiver operating characteristic curve ranging from 0.44 to 0.73, depending on the methods configuration. However, when the crowd verified what experts considered to be easy relationships with useful definitions, they performed reasonably well. Notably, there are significantly fewer Google search results for Gene Ontology concepts than SNOMED CT concepts. This disparity may account for the difference in performance - fewer search results indicate a more difficult task for the worker. The number of Internet search results could serve as a method to assess which tasks are appropriate for the crowd. These results suggest that the crowd fits better as an expert assistant, helping experts with their verification by completing the easy tasks and allowing experts to focus on the difficult tasks, rather than an expert replacement. Copyright © 2016 Elsevier Inc. All rights reserved.

SPONGY (SPam ONtoloGY): email classification using two-level dynamic ontology.

Science.gov (United States)

Youn, Seongwook

2014-01-01

Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

SPONGY (SPam ONtoloGY: Email Classification Using Two-Level Dynamic Ontology

Directory of Open Access Journals (Sweden)

Seongwook Youn

2014-01-01

Full Text Available Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user’s background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1 to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2 to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance.

SPONGY (SPam ONtoloGY): Email Classification Using Two-Level Dynamic Ontology

Science.gov (United States)

2014-01-01

Email is one of common communication methods between people on the Internet. However, the increase of email misuse/abuse has resulted in an increasing volume of spam emails over recent years. An experimental system has been designed and implemented with the hypothesis that this method would outperform existing techniques, and the experimental results showed that indeed the proposed ontology-based approach improves spam filtering accuracy significantly. In this paper, two levels of ontology spam filters were implemented: a first level global ontology filter and a second level user-customized ontology filter. The use of the global ontology filter showed about 91% of spam filtered, which is comparable with other methods. The user-customized ontology filter was created based on the specific user's background as well as the filtering mechanism used in the global ontology filter creation. The main contributions of the paper are (1) to introduce an ontology-based multilevel filtering technique that uses both a global ontology and an individual filter for each user to increase spam filtering accuracy and (2) to create a spam filter in the form of ontology, which is user-customized, scalable, and modularized, so that it can be embedded to many other systems for better performance. PMID:25254240

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.

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.

The Cell Ontology 2016: enhanced content, modularization, and ontology interoperability.

Science.gov (United States)

Diehl, Alexander D; Meehan, Terrence F; Bradford, Yvonne M; Brush, Matthew H; Dahdul, Wasila M; Dougall, David S; He, Yongqun; Osumi-Sutherland, David; Ruttenberg, Alan; Sarntivijai, Sirarat; Van Slyke, Ceri E; Vasilevsky, Nicole A; Haendel, Melissa A; Blake, Judith A; Mungall, Christopher J

2016-07-04

The Cell Ontology (CL) is an OBO Foundry candidate ontology covering the domain of canonical, natural biological cell types. Since its inception in 2005, the CL has undergone multiple rounds of revision and expansion, most notably in its representation of hematopoietic cells. For in vivo cells, the CL focuses on vertebrates but provides general classes that can be used for other metazoans, which can be subtyped in species-specific ontologies. Recent work on the CL has focused on extending the representation of various cell types, and developing new modules in the CL itself, and in related ontologies in coordination with the CL. For example, the Kidney and Urinary Pathway Ontology was used as a template to populate the CL with additional cell types. In addition, subtypes of the class 'cell in vitro' have received improved definitions and labels to provide for modularity with the representation of cells in the Cell Line Ontology and Reagent Ontology. Recent changes in the ontology development methodology for CL include a switch from OBO to OWL for the primary encoding of the ontology, and an increasing reliance on logical definitions for improved reasoning. The CL is now mandated as a metadata standard for large functional genomics and transcriptomics projects, and is used extensively for annotation, querying, and analyses of cell type specific data in sequencing consortia such as FANTOM5 and ENCODE, as well as for the NIAID ImmPort database and the Cell Image Library. The CL is also a vital component used in the modular construction of other biomedical ontologies-for example, the Gene Ontology and the cross-species anatomy ontology, Uberon, use CL to support the consistent representation of cell types across different levels of anatomical granularity, such as tissues and organs. The ongoing improvements to the CL make it a valuable resource to both the OBO Foundry community and the wider scientific community, and we continue to experience increased interest in the

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.

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.

Prospects and Possibilities for Ontology Evaluation: The View from NCOR

National Research Council Canada - National Science Library

Obrst, Leo; Hughes, Todd; Ray, Steve

2006-01-01

...) on ontology evaluation. NCOR's inauguration was recently held (October 2005), and at that time goals were identified and committees formed to pursue those goals, including the Ontology Evaluation Committee...

The Domain Shared by Computational and Digital Ontology: A Phenomenological Exploration and Analysis

Science.gov (United States)

Compton, Bradley Wendell

2009-01-01

The purpose of this dissertation is to explore and analyze a domain of research thought to be shared by two areas of philosophy: computational and digital ontology. Computational ontology is philosophy used to develop information systems also called computational ontologies. Digital ontology is philosophy dealing with our understanding of Being…

GOClonto: an ontological clustering approach for conceptualizing PubMed abstracts.

Science.gov (United States)

Zheng, Hai-Tao; Borchert, Charles; Kim, Hong-Gee

2010-02-01

Concurrent with progress in biomedical sciences, an overwhelming of textual knowledge is accumulating in the biomedical literature. PubMed is the most comprehensive database collecting and managing biomedical literature. To help researchers easily understand collections of PubMed abstracts, numerous clustering methods have been proposed to group similar abstracts based on their shared features. However, most of these methods do not explore the semantic relationships among groupings of documents, which could help better illuminate the groupings of PubMed abstracts. To address this issue, we proposed an ontological clustering method called GOClonto for conceptualizing PubMed abstracts. GOClonto uses latent semantic analysis (LSA) and gene ontology (GO) to identify key gene-related concepts and their relationships as well as allocate PubMed abstracts based on these key gene-related concepts. Based on two PubMed abstract collections, the experimental results show that GOClonto is able to identify key gene-related concepts and outperforms the STC (suffix tree clustering) algorithm, the Lingo algorithm, the Fuzzy Ants algorithm, and the clustering based TRS (tolerance rough set) algorithm. Moreover, the two ontologies generated by GOClonto show significant informative conceptual structures.

Development of Smart Sensors System Based on Formal Concept Analysis and Ontology Model

Directory of Open Access Journals (Sweden)

Hongsheng Xu

2013-06-01

Full Text Available The smart sensor is the product of the combination of one or more sensitive components, precision analog circuits, digital circuits, microprocessor, communication interface, intelligent software systems and hardware integration in a packaging component. Formal concept analysis is from the given data to automatically extract the classification relationship between the entire hidden concept and concept, formation of concept model. Ontology is a set of relations between concepts of the specific domain and concept, and it can effectively express the general knowledge of specific field. The paper proposes development of smart sensors system based on formal concept analysis and ontology model. Smart sensor is a micro processor, sensor with information detection, information processing, information memory, logical thinking and judging function. The methods can improve the effect of the smart sensors.

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.

Unintended consequences of existential quantifications in biomedical ontologies

Directory of Open Access Journals (Sweden)

Boeker Martin

2011-11-01

Full Text Available Abstract Background The Open Biomedical Ontologies (OBO Foundry is a collection of freely available ontologically structured controlled vocabularies in the biomedical domain. Most of them are disseminated via both the OBO Flatfile Format and the semantic web format Web Ontology Language (OWL, which draws upon formal logic. Based on the interpretations underlying OWL description logics (OWL-DL semantics, we scrutinize the OWL-DL releases of OBO ontologies to assess whether their logical axioms correspond to the meaning intended by their authors. Results We analyzed ontologies and ontology cross products available via the OBO Foundry site http://www.obofoundry.org for existential restrictions (someValuesFrom, from which we examined a random sample of 2,836 clauses. According to a rating done by four experts, 23% of all existential restrictions in OBO Foundry candidate ontologies are suspicious (Cohens' κ = 0.78. We found a smaller proportion of existential restrictions in OBO Foundry cross products are suspicious, but in this case an accurate quantitative judgment is not possible due to a low inter-rater agreement (κ = 0.07. We identified several typical modeling problems, for which satisfactory ontology design patterns based on OWL-DL were proposed. We further describe several usability issues with OBO ontologies, including the lack of ontological commitment for several common terms, and the proliferation of domain-specific relations. Conclusions The current OWL releases of OBO Foundry (and Foundry candidate ontologies contain numerous assertions which do not properly describe the underlying biological reality, or are ambiguous and difficult to interpret. The solution is a better anchoring in upper ontologies and a restriction to relatively few, well defined relation types with given domain and range constraints.

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.

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.

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

Ontologies and Formation Spaces for Conceptual ReDesign of Systems

Directory of Open Access Journals (Sweden)

J. Bíla

2005-01-01

Full Text Available This paper discusses ontologies, methods for developing them and languages for representing them. A special ontology for computational support of the Conceptual ReDesign Process (CRDP is introduced with a simple illustrative example of an application. The ontology denoted as Global context (GLB combines features of general semantic networks and features of UML language. The ontology is task-oriented and domain-oriented, and contains three basic strata – GLBExpl(stratum of Explanation, GLBFAct (stratum of Fields of Activities and GLBEnv (stratum of Environment, with their sub-strata. The ontology has been developed to represent functions of systems and their components in CRDP. The main difference between this ontology and ontologies which have been developed to identify functions (the semantic details in those ontologies must be as deep as possible is in the style of the description of the functions. In the proposed ontology, Formation Spaces were used as lower semantic categories the semantic deepness of which is variable and depends on the actual solution approach of a specialised Conceptual Designer.

Ontology-Based High-Level Context Inference for Human Behavior Identification

Science.gov (United States)

Villalonga, Claudia; Razzaq, Muhammad Asif; Khan, Wajahat Ali; Pomares, Hector; Rojas, Ignacio; Lee, Sungyoung; Banos, Oresti

2016-01-01

Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users. PMID:27690050

Ontology-Based High-Level Context Inference for Human Behavior Identification

Directory of Open Access Journals (Sweden)

Claudia Villalonga

2016-09-01

Full Text Available Recent years have witnessed a huge progress in the automatic identification of individual primitives of human behavior, such as activities or locations. However, the complex nature of human behavior demands more abstract contextual information for its analysis. This work presents an ontology-based method that combines low-level primitives of behavior, namely activity, locations and emotions, unprecedented to date, to intelligently derive more meaningful high-level context information. The paper contributes with a new open ontology describing both low-level and high-level context information, as well as their relationships. Furthermore, a framework building on the developed ontology and reasoning models is presented and evaluated. The proposed method proves to be robust while identifying high-level contexts even in the event of erroneously-detected low-level contexts. Despite reasonable inference times being obtained for a relevant set of users and instances, additional work is required to scale to long-term scenarios with a large number of users.

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.

Towards Process-Ontology: A Critical Study of Substance-Ontological Premises

DEFF Research Database (Denmark)

Seibt, Johanna

The thesis proposes therapeutic revision of fundamental assumptions in contemporary ontological thought. I show that non of the prevalent theories of objects, by virtue of certain implicit substance-ontological assumptions provides a viable account of the numerical, qualitative, and trans-tempora......-ontological presuppositions, I finally explore the result of rejecting all of them and sketch a scheme basic on dynamic masses which promises to yield coherent explanation of the ontological features of those complex processes that we commonly call objects....

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...

Formalized Conflicts Detection Based on the Analysis of Multiple Emails: An Approach Combining Statistics and Ontologies

Science.gov (United States)

Zakaria, Chahnez; Curé, Olivier; Salzano, Gabriella; Smaïli, Kamel

In Computer Supported Cooperative Work (CSCW), it is crucial for project leaders to detect conflicting situations as early as possible. Generally, this task is performed manually by studying a set of documents exchanged between team members. In this paper, we propose a full-fledged automatic solution that identifies documents, subjects and actors involved in relational conflicts. Our approach detects conflicts in emails, probably the most popular type of documents in CSCW, but the methods used can handle other text-based documents. These methods rely on the combination of statistical and ontological operations. The proposed solution is decomposed in several steps: (i) we enrich a simple negative emotion ontology with terms occuring in the corpus of emails, (ii) we categorize each conflicting email according to the concepts of this ontology and (iii) we identify emails, subjects and team members involved in conflicting emails using possibilistic description logic and a set of proposed measures. Each of these steps are evaluated and validated on concrete examples. Moreover, this approach's framework is generic and can be easily adapted to domains other than conflicts, e.g. security issues, and extended with operations making use of our proposed set of measures.

Towards a Consistent and Scientifically Accurate Drug Ontology.

Science.gov (United States)

Hogan, William R; Hanna, Josh; Joseph, Eric; Brochhausen, Mathias

2013-01-01

Our use case for comparative effectiveness research requires an ontology of drugs that enables querying National Drug Codes (NDCs) by active ingredient, mechanism of action, physiological effect, and therapeutic class of the drug products they represent. We conducted an ontological analysis of drugs from the realist perspective, and evaluated existing drug terminology, ontology, and database artifacts from (1) the technical perspective, (2) the perspective of pharmacology and medical science (3) the perspective of description logic semantics (if they were available in Web Ontology Language or OWL), and (4) the perspective of our realism-based analysis of the domain. No existing resource was sufficient. Therefore, we built the Drug Ontology (DrOn) in OWL, which we populated with NDCs and other classes from RxNorm using only content created by the National Library of Medicine. We also built an application that uses DrOn to query for NDCs as outlined above, available at: http://ingarden.uams.edu/ingredients. The application uses an OWL-based description logic reasoner to execute end-user queries. DrOn is available at http://code.google.com/p/dr-on.

InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk

OpenAIRE

Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

2018-01-01

Background Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each o...

Ontology-Based Vaccine Adverse Event Representation and Analysis.

Science.gov (United States)

Xie, Jiangan; He, Yongqun

2017-01-01

Vaccine is the one of the greatest inventions of modern medicine that has contributed most to the relief of human misery and the exciting increase in life expectancy. In 1796, an English country physician, Edward Jenner, discovered that inoculating mankind with cowpox can protect them from smallpox (Riedel S, Edward Jenner and the history of smallpox and vaccination. Proceedings (Baylor University. Medical Center) 18(1):21, 2005). Based on the vaccination worldwide, we finally succeeded in the eradication of smallpox in 1977 (Henderson, Vaccine 29:D7-D9, 2011). Other disabling and lethal diseases, like poliomyelitis and measles, are targeted for eradication (Bonanni, Vaccine 17:S120-S125, 1999).Although vaccine development and administration are tremendously successful and cost-effective practices to human health, no vaccine is 100% safe for everyone because each person reacts to vaccinations differently given different genetic background and health conditions. Although all licensed vaccines are generally safe for the majority of people, vaccinees may still suffer adverse events (AEs) in reaction to various vaccines, some of which can be serious or even fatal (Haber et al., Drug Saf 32(4):309-323, 2009). Hence, the double-edged sword of vaccination remains a concern.To support integrative AE data collection and analysis, it is critical to adopt an AE normalization strategy. In the past decades, different controlled terminologies, including the Medical Dictionary for Regulatory Activities (MedDRA) (Brown EG, Wood L, Wood S, et al., Drug Saf 20(2):109-117, 1999), the Common Terminology Criteria for Adverse Events (CTCAE) (NCI, The Common Terminology Criteria for Adverse Events (CTCAE). Available from: http://evs.nci.nih.gov/ftp1/CTCAE/About.html . Access on 7 Oct 2015), and the World Health Organization (WHO) Adverse Reactions Terminology (WHO-ART) (WHO, The WHO Adverse Reaction Terminology - WHO-ART. Available from: https://www.umc-products.com/graphics/28010.pdf

Annotating Evidence Based Clinical Guidelines : A Lightweight Ontology

NARCIS (Netherlands)

Hoekstra, R.; de Waard, A.; Vdovjak, R.; Paschke, A.; Burger, A.; Romano, P.; Marshall, M.S.; Splendiani, A.

2012-01-01

This paper describes a lightweight ontology for representing annotations of declarative evidence based clinical guidelines. We present the motivation and requirements for this representation, based on an analysis of several guidelines. The ontology provides the means to connect clinical questions

PAV ontology: provenance, authoring and versioning.

Science.gov (United States)

Ciccarese, Paolo; Soiland-Reyes, Stian; Belhajjame, Khalid; Gray, Alasdair Jg; Goble, Carole; Clark, Tim

2013-11-22

Provenance is a critical ingredient for establishing trust of published scientific content. This is true whether we are considering a data set, a computational workflow, a peer-reviewed publication or a simple scientific claim with supportive evidence. Existing vocabularies such as Dublin Core Terms (DC Terms) and the W3C Provenance Ontology (PROV-O) are domain-independent and general-purpose and they allow and encourage for extensions to cover more specific needs. In particular, to track authoring and versioning information of web resources, PROV-O provides a basic methodology but not any specific classes and properties for identifying or distinguishing between the various roles assumed by agents manipulating digital artifacts, such as author, contributor and curator. We present the Provenance, Authoring and Versioning ontology (PAV, namespace http://purl.org/pav/): a lightweight ontology for capturing "just enough" descriptions essential for tracking the provenance, authoring and versioning of web resources. We argue that such descriptions are essential for digital scientific content. PAV distinguishes between contributors, authors and curators of content and creators of representations in addition to the provenance of originating resources that have been accessed, transformed and consumed. We explore five projects (and communities) that have adopted PAV illustrating their usage through concrete examples. Moreover, we present mappings that show how PAV extends the W3C PROV-O ontology to support broader interoperability. The initial design of the PAV ontology was driven by requirements from the AlzSWAN project with further requirements incorporated later from other projects detailed in this paper. The authors strived to keep PAV lightweight and compact by including only those terms that have demonstrated to be pragmatically useful in existing applications, and by recommending terms from existing ontologies when plausible. We analyze and compare PAV with related

Ontology Alignment Repair through Modularization and Confidence-Based Heuristics.

Directory of Open Access Journals (Sweden)

Emanuel Santos

Full Text Available Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of repair techniques to improve the coherence of ontology alignments began to be explored. This paper presents a novel modularization technique for ontology alignment repair which extracts fragments of the input ontologies that only contain the necessary classes and relations to resolve all detectable incoherences. The paper presents also an alignment repair algorithm that uses a global repair strategy to minimize both the degree of incoherence and the number of mappings removed from the alignment, while overcoming the scalability problem by employing the proposed modularization technique. Our evaluation shows that our modularization technique produces significantly small fragments of the ontologies and that our repair algorithm produces more complete alignments than other current alignment repair systems, while obtaining an equivalent degree of incoherence. Additionally, we also present a variant of our repair algorithm that makes use of the confidence values of the mappings to improve alignment repair. Our repair algorithm was implemented as part of AgreementMakerLight, a free and open-source ontology matching system.

Ontology Alignment Repair through Modularization and Confidence-Based Heuristics.

Science.gov (United States)

Santos, Emanuel; Faria, Daniel; Pesquita, Catia; Couto, Francisco M

2015-01-01

Ontology Matching aims at identifying a set of semantic correspondences, called an alignment, between related ontologies. In recent years, there has been a growing interest in efficient and effective matching methods for large ontologies. However, alignments produced for large ontologies are often logically incoherent. It was only recently that the use of repair techniques to improve the coherence of ontology alignments began to be explored. This paper presents a novel modularization technique for ontology alignment repair which extracts fragments of the input ontologies that only contain the necessary classes and relations to resolve all detectable incoherences. The paper presents also an alignment repair algorithm that uses a global repair strategy to minimize both the degree of incoherence and the number of mappings removed from the alignment, while overcoming the scalability problem by employing the proposed modularization technique. Our evaluation shows that our modularization technique produces significantly small fragments of the ontologies and that our repair algorithm produces more complete alignments than other current alignment repair systems, while obtaining an equivalent degree of incoherence. Additionally, we also present a variant of our repair algorithm that makes use of the confidence values of the mappings to improve alignment repair. Our repair algorithm was implemented as part of AgreementMakerLight, a free and open-source ontology matching system.

An efficient, large-scale, non-lattice-detection algorithm for exhaustive structural auditing of biomedical ontologies.

Science.gov (United States)

Zhang, Guo-Qiang; Xing, Guangming; Cui, Licong

2018-04-01

One of the basic challenges in developing structural methods for systematic audition on the quality of biomedical ontologies is the computational cost usually involved in exhaustive sub-graph analysis. We introduce ANT-LCA, a new algorithm for computing all non-trivial lowest common ancestors (LCA) of each pair of concepts in the hierarchical order induced by an ontology. The computation of LCA is a fundamental step for non-lattice approach for ontology quality assurance. Distinct from existing approaches, ANT-LCA only computes LCAs for non-trivial pairs, those having at least one common ancestor. To skip all trivial pairs that may be of no practical interest, ANT-LCA employs a simple but innovative algorithmic strategy combining topological order and dynamic programming to keep track of non-trivial pairs. We provide correctness proofs and demonstrate a substantial reduction in computational time for two largest biomedical ontologies: SNOMED CT and Gene Ontology (GO). ANT-LCA achieved an average computation time of 30 and 3 sec per version for SNOMED CT and GO, respectively, about 2 orders of magnitude faster than the best known approaches. Our algorithm overcomes a fundamental computational barrier in sub-graph based structural analysis of large ontological systems. It enables the implementation of a new breed of structural auditing methods that not only identifies potential problematic areas, but also automatically suggests changes to fix the issues. Such structural auditing methods can lead to more effective tools supporting ontology quality assurance work. Copyright © 2018 Elsevier Inc. All rights reserved.

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.

Making methodology a matter of process ontology

DEFF Research Database (Denmark)

Revsbæk, Line

2016-01-01

This paper presents a practice of doing qualitative interview analysis from the insights of the process ontology in G. H. Mead’s Philosophy of the Present (1932). The paper presents two cases of analyzing in the present while listening to recorded interview material eliciting researcher’s case...... study and otherwise related experiences creating case narratives inclusive of researcher’s reflexive voice. The paper presents an auto-ethnographic approach to data analysis based on process theory ontology....

A broken symmetry ontology: Quantum mechanics as a broken symmetry

International Nuclear Information System (INIS)

Buschmann, J.E.

1988-01-01

The author proposes a new broken symmetry ontology to be used to analyze the quantum domain. This ontology is motivated and grounded in a critical epistemological analysis, and an analysis of the basic role of symmetry in physics. Concurrently, he is led to consider nonheterogeneous systems, whose logical state space contains equivalence relations not associated with the causal relation. This allows him to find a generalized principle of symmetry and a generalized symmetry-conservation formalisms. In particular, he clarifies the role of Noether's theorem in field theory. He shows how a broken symmetry ontology already operates in a description of the weak interactions. Finally, by showing how a broken symmetry ontology operates in the quantum domain, he accounts for the interpretational problem and the essential incompleteness of quantum mechanics. He proposes that the broken symmetry underlying this ontological domain is broken dilation invariance

Persistent identifiers for web service requests relying on a provenance ontology design pattern

Science.gov (United States)

Car, Nicholas; Wang, Jingbo; Wyborn, Lesley; Si, Wei

2016-04-01

Delivering provenance information for datasets produced from static inputs is relatively straightforward: we represent the processing actions and data flow using provenance ontologies and link to stored copies of the inputs stored in repositories. If appropriate detail is given, the provenance information can then describe what actions have occurred (transparency) and enable reproducibility. When web service-generated data is used by a process to create a dataset instead of a static inputs, we need to use sophisticated provenance representations of the web service request as we can no longer just link to data stored in a repository. A graph-based provenance representation, such as the W3C's PROV standard, can be used to model the web service request as a single conceptual dataset and also as a small workflow with a number of components within the same provenance report. This dual representation does more than just allow simplified or detailed views of a dataset's production to be used where appropriate. It also allow persistent identifiers to be assigned to instances of a web service requests, thus enabling one form of dynamic data citation, and for those identifiers to resolve to whatever level of detail implementers think appropriate in order for that web service request to be reproduced. In this presentation we detail our reasoning in representing web service requests as small workflows. In outline, this stems from the idea that web service requests are perdurant things and in order to most easily persist knowledge of them for provenance, we should represent them as a nexus of relationships between endurant things, such as datasets and knowledge of particular system types, as these endurant things are far easier to persist. We also describe the ontology design pattern that we use to represent workflows in general and how we apply it to different types of web service requests. We give examples of specific web service requests instances that were made by systems

Linking human diseases to animal models using ontology-based phenotype annotation.

Directory of Open Access Journals (Sweden)

Nicole L Washington

2009-11-01

Full Text Available Scientists and clinicians who study genetic alterations and disease have traditionally described phenotypes in natural language. The considerable variation in these free-text descriptions has posed a hindrance to the important task of identifying candidate genes and models for human diseases and indicates the need for a computationally tractable method to mine data resources for mutant phenotypes. In this study, we tested the hypothesis that ontological annotation of disease phenotypes will facilitate the discovery of new genotype-phenotype relationships within and across species. To describe phenotypes using ontologies, we used an Entity-Quality (EQ methodology, wherein the affected entity (E and how it is affected (Q are recorded using terms from a variety of ontologies. Using this EQ method, we annotated the phenotypes of 11 gene-linked human diseases described in Online Mendelian Inheritance in Man (OMIM. These human annotations were loaded into our Ontology-Based Database (OBD along with other ontology-based phenotype descriptions of mutants from various model organism databases. Phenotypes recorded with this EQ method can be computationally compared based on the hierarchy of terms in the ontologies and the frequency of annotation. We utilized four similarity metrics to compare phenotypes and developed an ontology of homologous and analogous anatomical structures to compare phenotypes between species. Using these tools, we demonstrate that we can identify, through the similarity of the recorded phenotypes, other alleles of the same gene, other members of a signaling pathway, and orthologous genes and pathway members across species. We conclude that EQ-based annotation of phenotypes, in conjunction with a cross-species ontology, and a variety of similarity metrics can identify biologically meaningful similarities between genes by comparing phenotypes alone. This annotation and search method provides a novel and efficient means to identify

Utilizing a structural meta-ontology for family-based quality assurance of the BioPortal ontologies.

Science.gov (United States)

Ochs, Christopher; He, Zhe; Zheng, Ling; Geller, James; Perl, Yehoshua; Hripcsak, George; Musen, Mark A

2016-06-01

An Abstraction Network is a compact summary of an ontology's structure and content. In previous research, we showed that Abstraction Networks support quality assurance (QA) of biomedical ontologies. The development of an Abstraction Network and its associated QA methodologies, however, is a labor-intensive process that previously was applicable only to one ontology at a time. To improve the efficiency of the Abstraction-Network-based QA methodology, we introduced a QA framework that uses uniform Abstraction Network derivation techniques and QA methodologies that are applicable to whole families of structurally similar ontologies. For the family-based framework to be successful, it is necessary to develop a method for classifying ontologies into structurally similar families. We now describe a structural meta-ontology that classifies ontologies according to certain structural features that are commonly used in the modeling of ontologies (e.g., object properties) and that are important for Abstraction Network derivation. Each class of the structural meta-ontology represents a family of ontologies with identical structural features, indicating which types of Abstraction Networks and QA methodologies are potentially applicable to all of the ontologies in the family. We derive a collection of 81 families, corresponding to classes of the structural meta-ontology, that enable a flexible, streamlined family-based QA methodology, offering multiple choices for classifying an ontology. The structure of 373 ontologies from the NCBO BioPortal is analyzed and each ontology is classified into multiple families modeled by the structural meta-ontology. Copyright © 2016 Elsevier Inc. All rights reserved.

Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

KAUST Repository

Alghamdi, Sarah M.

2018-01-01

To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

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...

The Software Ontology (SWO): a resource for reproducibility in biomedical data analysis, curation and digital preservation.

Science.gov (United States)

Malone, James; Brown, Andy; Lister, Allyson L; Ison, Jon; Hull, Duncan; Parkinson, Helen; Stevens, Robert

2014-01-01

Biomedical ontologists to date have concentrated on ontological descriptions of biomedical entities such as gene products and their attributes, phenotypes and so on. Recently, effort has diversified to descriptions of the laboratory investigations by which these entities were produced. However, much biological insight is gained from the analysis of the data produced from these investigations, and there is a lack of adequate descriptions of the wide range of software that are central to bioinformatics. We need to describe how data are analyzed for discovery, audit trails, provenance and reproducibility. The Software Ontology (SWO) is a description of software used to store, manage and analyze data. Input to the SWO has come from beyond the life sciences, but its main focus is the life sciences. We used agile techniques to gather input for the SWO and keep engagement with our users. The result is an ontology that meets the needs of a broad range of users by describing software, its information processing tasks, data inputs and outputs, data formats versions and so on. Recently, the SWO has incorporated EDAM, a vocabulary for describing data and related concepts in bioinformatics. The SWO is currently being used to describe software used in multiple biomedical applications. The SWO is another element of the biomedical ontology landscape that is necessary for the description of biomedical entities and how they were discovered. An ontology of software used to analyze data produced by investigations in the life sciences can be made in such a way that it covers the important features requested and prioritized by its users. The SWO thus fits into the landscape of biomedical ontologies and is produced using techniques designed to keep it in line with user's needs. The Software Ontology is available under an Apache 2.0 license at http://theswo.sourceforge.net/; the Software Ontology blog can be read at http://softwareontology.wordpress.com.

ER2OWL: Generating OWL Ontology from ER Diagram

Science.gov (United States)

Fahad, Muhammad

Ontology is the fundamental part of Semantic Web. The goal of W3C is to bring the web into (its full potential) a semantic web with reusing previous systems and artifacts. Most legacy systems have been documented in structural analysis and structured design (SASD), especially in simple or Extended ER Diagram (ERD). Such systems need up-gradation to become the part of semantic web. In this paper, we present ERD to OWL-DL ontology transformation rules at concrete level. These rules facilitate an easy and understandable transformation from ERD to OWL. The set of rules for transformation is tested on a structured analysis and design example. The framework provides OWL ontology for semantic web fundamental. This framework helps software engineers in upgrading the structured analysis and design artifact ERD, to components of semantic web. Moreover our transformation tool, ER2OWL, reduces the cost and time for building OWL ontologies with the reuse of existing entity relationship models.

Quality control for terms and definitions in ontologies and taxonomies

Directory of Open Access Journals (Sweden)

Rüegg Alexander

2006-04-01

Full Text Available Abstract Background Ontologies and taxonomies are among the most important computational resources for molecular biology and bioinformatics. A series of recent papers has shown that the Gene Ontology (GO, the most prominent taxonomic resource in these fields, is marked by flaws of certain characteristic types, which flow from a failure to address basic ontological principles. As yet, no methods have been proposed which would allow ontology curators to pinpoint flawed terms or definitions in ontologies in a systematic way. Results We present computational methods that automatically identify terms and definitions which are defined in a circular or unintelligible way. We further demonstrate the potential of these methods by applying them to isolate a subset of 6001 problematic GO terms. By automatically aligning GO with other ontologies and taxonomies we were able to propose alternative synonyms and definitions for some of these problematic terms. This allows us to demonstrate that these other resources do not contain definitions superior to those supplied by GO. Conclusion Our methods provide reliable indications of the quality of terms and definitions in ontologies and taxonomies. Further, they are well suited to assist ontology curators in drawing their attention to those terms that are ill-defined. We have further shown the limitations of ontology mapping and alignment in assisting ontology curators in rectifying problems, thus pointing to the need for manual curation.

Biomedical word sense disambiguation with ontologies and metadata: automation meets accuracy

Directory of Open Access Journals (Sweden)

Hakenberg Jörg

2009-01-01

Full Text Available Abstract Background Ontology term labels can be ambiguous and have multiple senses. While this is no problem for human annotators, it is a challenge to automated methods, which identify ontology terms in text. Classical approaches to word sense disambiguation use co-occurring words or terms. However, most treat ontologies as simple terminologies, without making use of the ontology structure or the semantic similarity between terms. Another useful source of information for disambiguation are metadata. Here, we systematically compare three approaches to word sense disambiguation, which use ontologies and metadata, respectively. Results The 'Closest Sense' method assumes that the ontology defines multiple senses of the term. It computes the shortest path of co-occurring terms in the document to one of these senses. The 'Term Cooc' method defines a log-odds ratio for co-occurring terms including co-occurrences inferred from the ontology structure. The 'MetaData' approach trains a classifier on metadata. It does not require any ontology, but requires training data, which the other methods do not. To evaluate these approaches we defined a manually curated training corpus of 2600 documents for seven ambiguous terms from the Gene Ontology and MeSH. All approaches over all conditions achieve 80% success rate on average. The 'MetaData' approach performed best with 96%, when trained on high-quality data. Its performance deteriorates as quality of the training data decreases. The 'Term Cooc' approach performs better on Gene Ontology (92% success than on MeSH (73% success as MeSH is not a strict is-a/part-of, but rather a loose is-related-to hierarchy. The 'Closest Sense' approach achieves on average 80% success rate. Conclusion Metadata is valuable for disambiguation, but requires high quality training data. Closest Sense requires no training, but a large, consistently modelled ontology, which are two opposing conditions. Term Cooc achieves greater 90

Operational Plan Ontology Model for Interconnection and Interoperability

Science.gov (United States)

Long, F.; Sun, Y. K.; Shi, H. Q.

2017-03-01

Aiming at the assistant decision-making system’s bottleneck of processing the operational plan data and information, this paper starts from the analysis of the problem of traditional expression and the technical advantage of ontology, and then it defines the elements of the operational plan ontology model and determines the basis of construction. Later, it builds up a semi-knowledge-level operational plan ontology model. Finally, it probes into the operational plan expression based on the operational plan ontology model and the usage of the application software. Thus, this paper has the theoretical significance and application value in the improvement of interconnection and interoperability of the operational plan among assistant decision-making systems.

Ontology Design Patterns for Combining Pathology and Anatomy: Application to Study Aging and Longevity in Inbred Mouse Strains

KAUST Repository

Alghamdi, Sarah M.

2018-05-13

In biomedical research, ontologies are widely used to represent knowledge as well as to annotate datasets. Many of the existing ontologies cover a single type of phenomena, such as a process, cell type, gene, pathological entity or anatomical structure. Consequently, there is a requirement to use multiple ontologies to fully characterize the observations in the datasets. Although this allows precise annotation of different aspects of a given dataset, it limits our ability to use the ontologies in data analysis, as the ontologies are usually disconnected and their combinations cannot be exploited. Motivated by this, here we present novel ontology design methods for combining pathology and anatomy concepts. To this end, we use a dataset of mouse models which has been characterized through two ontologies: one of them is the mouse pathology ontology (MPATH) covering pathological lesions while the other is the mouse anatomy ontology (MA) covering the anatomical site of the lesions. We propose four novel ontology design patterns for combining these ontologies, and use these patterns to generate four ontologies in a data-driven way. To evaluate the generated ontologies, we utilize these in ontology-based data analysis, including ontology enrichment analysis and computation of semantic similarity. We demonstrate that there are significant differences between the four ontologies in different analysis approaches. In addition, when using semantic similarity to confirm the hypothesis that genetically identical mice should develop more similar diseases, the generated combined ontologies lead to significantly better analysis results compared to using each ontology individually. Our results reveal that using ontology design patterns to combine different facets characterizing a dataset can improve established analysis methods.

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...

OntologyWidget – a reusable, embeddable widget for easily locating ontology terms

OpenAIRE

Beauheim, Catherine C; Wymore, Farrell; Nitzberg, Michael; Zachariah, Zachariah K; Jin, Heng; Skene, JH Pate; Ball, Catherine A; Sherlock, Gavin

2007-01-01

Abstract Background Biomedical ontologies are being widely used to annotate biological data in a computer-accessible, consistent and well-defined manner. However, due to their size and complexity, annotating data with appropriate terms from an ontology is often challenging for experts and non-experts alike, because there exist few tools that allow one to quickly find relevant ontology terms to easily populate a web form. Results We have produced a tool, OntologyWidget, which allows users to r...

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

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...

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.

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.

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

Ontorat: automatic generation of new ontology terms, annotations, and axioms based on ontology design patterns.

Science.gov (United States)

Xiang, Zuoshuang; Zheng, Jie; Lin, Yu; He, Yongqun

2015-01-01

It is time-consuming to build an ontology with many terms and axioms. Thus it is desired to automate the process of ontology development. Ontology Design Patterns (ODPs) provide a reusable solution to solve a recurrent modeling problem in the context of ontology engineering. Because ontology terms often follow specific ODPs, the Ontology for Biomedical Investigations (OBI) developers proposed a Quick Term Templates (QTTs) process targeted at generating new ontology classes following the same pattern, using term templates in a spreadsheet format. Inspired by the ODPs and QTTs, the Ontorat web application is developed to automatically generate new ontology terms, annotations of terms, and logical axioms based on a specific ODP(s). The inputs of an Ontorat execution include axiom expression settings, an input data file, ID generation settings, and a target ontology (optional). The axiom expression settings can be saved as a predesigned Ontorat setting format text file for reuse. The input data file is generated based on a template file created by a specific ODP (text or Excel format). Ontorat is an efficient tool for ontology expansion. Different use cases are described. For example, Ontorat was applied to automatically generate over 1,000 Japan RIKEN cell line cell terms with both logical axioms and rich annotation axioms in the Cell Line Ontology (CLO). Approximately 800 licensed animal vaccines were represented and annotated in the Vaccine Ontology (VO) by Ontorat. The OBI team used Ontorat to add assay and device terms required by ENCODE project. Ontorat was also used to add missing annotations to all existing Biobank specific terms in the Biobank Ontology. A collection of ODPs and templates with examples are provided on the Ontorat website and can be reused to facilitate ontology development. With ever increasing ontology development and applications, Ontorat provides a timely platform for generating and annotating a large number of ontology terms by following

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....

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

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...

GO-Bayes: Gene Ontology-based overrepresentation analysis using a Bayesian approach.

Science.gov (United States)

Zhang, Song; Cao, Jing; Kong, Y Megan; Scheuermann, Richard H

2010-04-01

A typical approach for the interpretation of high-throughput experiments, such as gene expression microarrays, is to produce groups of genes based on certain criteria (e.g. genes that are differentially expressed). To gain more mechanistic insights into the underlying biology, overrepresentation analysis (ORA) is often conducted to investigate whether gene sets associated with particular biological functions, for example, as represented by Gene Ontology (GO) annotations, are statistically overrepresented in the identified gene groups. However, the standard ORA, which is based on the hypergeometric test, analyzes each GO term in isolation and does not take into account the dependence structure of the GO-term hierarchy. We have developed a Bayesian approach (GO-Bayes) to measure overrepresentation of GO terms that incorporates the GO dependence structure by taking into account evidence not only from individual GO terms, but also from their related terms (i.e. parents, children, siblings, etc.). The Bayesian framework borrows information across related GO terms to strengthen the detection of overrepresentation signals. As a result, this method tends to identify sets of closely related GO terms rather than individual isolated GO terms. The advantage of the GO-Bayes approach is demonstrated with a simulation study and an application example.

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...

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.

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.

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.

Ontological interpretation of biomedical database content.

Science.gov (United States)

Santana da Silva, Filipe; Jansen, Ludger; Freitas, Fred; Schulz, Stefan

2017-06-26

addressed by a method that identifies implicit knowledge behind semantic annotations in biological databases and grounds it in an expressive upper-level ontology. The result is a seamless representation of database structure, content and annotations as OWL models.

Applying Conceptual Blending to Model Coordinated Use of Multiple Ontological Metaphors

Science.gov (United States)

Dreyfus, Benjamin W.; Gupta, Ayush; Redish, Edward F.

2015-04-01

Energy is an abstract science concept, so the ways that we think and talk about energy rely heavily on ontological metaphors: metaphors for what kind of thing energy is. Two commonly used ontological metaphors for energy are energy as a substance and energy as a vertical location. Our previous work has demonstrated that students and experts can productively use both the substance and location ontologies for energy. In this paper, we use Fauconnier and Turner's conceptual blending framework to demonstrate that experts and novices can successfully blend the substance and location ontologies into a coherent mental model in order to reason about energy. Our data come from classroom recordings of a physics professor teaching a physics course for the life sciences, and from an interview with an undergraduate student in that course. We analyze these data using predicate analysis and gesture analysis, looking at verbal utterances, gestures, and the interaction between them. This analysis yields evidence that the speakers are blending the substance and location ontologies into a single blended mental space.

The Russian Quest for Ontological Security

DEFF Research Database (Denmark)

Pedersen, Jonas Gejl

This paper argues that Russia’s decision to militarily intervene in the Kosovo crisis (1999) arose out of ontological, alongside material, insecurity. Whereas states’ material security essentially deals with national survival, ontological security concerns safety of the ‘national Self......’. By supplementing the existing theories of geopolitics and regime security with the conceptual lens of ontological security, my interpretivist case study demonstrates why Russia, despite great risk and material costs, decided to militarily intervene and traces how Russian senses of ‘national Self’ were...... fundamentally reconstructed during intervention. I find that the anxiety arising from a future scenario of an already weak post-Soviet ‘Russian Self’ gradually being engulfed by a confident ‘Western Self’ played a significant role in Russia’s decision to occupy Slatina airbase. My analysis paradoxically shows...

Ontology for customer centric digital services and analytics

Science.gov (United States)

Keat, Ng Wai; Shahrir, Mohammad Shazri

2017-11-01

In computer science research, ontologies are commonly utilised to create a unified abstract across many rich and different fields. In this paper, we apply the concept to the customer centric domain of digital services analytics and present an analytics solution ontology. The essence is based from traditional Entity Relationship Diagram (ERD), which then was abstracted out to cover wider areas on customer centric digital services. The ontology we developed covers both static aspects (customer identifiers) and dynamic aspects (customer's temporal interactions). The structure of the customer scape is modeled with classes that represent different types of customer touch points, ranging from digital and digital-stamps which represent physical analogies. The dynamic aspects of customer centric digital service are modeled with a set of classes, with the importance is represented in different associations involving establishment and termination of the target interaction. The realized ontology can be used in development of frameworks for customer centric applications, and for specification of common data format used by cooperating digital service applications.

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.

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.

Human microRNA target analysis and gene ontology clustering by GOmir, a novel stand-alone application.

Science.gov (United States)

Roubelakis, Maria G; Zotos, Pantelis; Papachristoudis, Georgios; Michalopoulos, Ioannis; Pappa, Kalliopi I; Anagnou, Nicholas P; Kossida, Sophia

2009-06-16

microRNAs (miRNAs) are single-stranded RNA molecules of about 20-23 nucleotides length found in a wide variety of organisms. miRNAs regulate gene expression, by interacting with target mRNAs at specific sites in order to induce cleavage of the message or inhibit translation. Predicting or verifying mRNA targets of specific miRNAs is a difficult process of great importance. GOmir is a novel stand-alone application consisting of two separate tools: JTarget and TAGGO. JTarget integrates miRNA target prediction and functional analysis by combining the predicted target genes from TargetScan, miRanda, RNAhybrid and PicTar computational tools as well as the experimentally supported targets from TarBase and also providing a full gene description and functional analysis for each target gene. On the other hand, TAGGO application is designed to automatically group gene ontology annotations, taking advantage of the Gene Ontology (GO), in order to extract the main attributes of sets of proteins. GOmir represents a new tool incorporating two separate Java applications integrated into one stand-alone Java application. GOmir (by using up to five different databases) introduces miRNA predicted targets accompanied by (a) full gene description, (b) functional analysis and (c) detailed gene ontology clustering. Additionally, a reverse search initiated by a potential target can also be conducted. GOmir can freely be downloaded BRFAA.

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.

OntoPop: An Ontology Population System for the Semantic Web

Science.gov (United States)

Thongkrau, Theerayut; Lalitrojwong, Pattarachai

The development of ontology at the instance level requires the extraction of the terms defining the instances from various data sources. These instances then are linked to the concepts of the ontology, and relationships are created between these instances for the next step. However, before establishing links among data, ontology engineers must classify terms or instances from a web document into an ontology concept. The tool for help ontology engineer in this task is called ontology population. The present research is not suitable for ontology development applications, such as long time processing or analyzing large or noisy data sets. OntoPop system introduces a methodology to solve these problems, which comprises two parts. First, we select meaningful features from syntactic relations, which can produce more significant features than any other method. Second, we differentiate feature meaning and reduce noise based on latent semantic analysis. Experimental evaluation demonstrates that the OntoPop works well, significantly out-performing the accuracy of 49.64%, a learning accuracy of 76.93%, and executes time of 5.46 second/instance.

Reconciliation of ontology and terminology to cope with linguistics.

Science.gov (United States)

Baud, Robert H; Ceusters, Werner; Ruch, Patrick; Rassinoux, Anne-Marie; Lovis, Christian; Geissbühler, Antoine

2007-01-01

To discuss the relationships between ontologies, terminologies and language in the context of Natural Language Processing (NLP) applications in order to show the negative consequences of confusing them. The viewpoints of the terminologist and (computational) linguist are developed separately, and then compared, leading to the presentation of reconciliation among these points of view, with consideration of the role of the ontologist. In order to encourage appropriate usage of terminologies, guidelines are presented advocating the simultaneous publication of pragmatic vocabularies supported by terminological material based on adequate ontological analysis. Ontologies, terminologies and natural languages each have their own purpose. Ontologies support machine understanding, natural languages support human communication, and terminologies should form the bridge between them. Therefore, future terminology standards should be based on sound ontology and do justice to the diversities in natural languages. Moreover, they should support local vocabularies, in order to be easily adaptable to local needs and practices.

From Patient Discharge Summaries to an Ontology for Psychiatry.

Science.gov (United States)

Richard, Marion; Aimé, Xavier; Jaulent, Marie-Christine; Krebs, Marie-Odile; Charlet, Jean

2017-01-01

Psychiatry aims at detecting symptoms, providing diagnoses and treating mental disorders. We developed ONTOPSYCHIA, an ontology for psychiatry in three modules: social and environmental factors of mental disorders, mental disorders, and treatments. The use of ONTOPSYCHIA, associated with dedicated tools, will facilitate semantic research in Patient Discharge Summaries (PDS). To develop the first module of the ontology we propose a PDS text analysis in order to explicit psychiatry concepts. We decided to set aside classifications during the construction of the modu le, to focus only on the information contained in PDS (bottom-up approach) and to return to domain classifications solely for the enrichment phase (top-down approach). Then, we focused our work on the development of the LOVMI methodology (Les Ontologies Validées par Méthode Interactive - Ontologies Validated by Interactive Method), which aims to provide a methodological framework to validate the structure and the semantic of an ontology.

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…

Toward a formal ontology for narrative

Directory of Open Access Journals (Sweden)

Ciotti, Fabio

2016-03-01

Full Text Available In this paper the rationale and the first draft of a formal ontology for modeling narrative texts are presented. Building on the semiotic and structuralist narratology, and on the work carried out in the late 1980s by Giuseppe Gigliozzi in Italy, the focus of my research are the concepts of character and of narrative world/space. This formal model is expressed in the OWL 2 ontology language. The main reason to adopt a formal modeling approach is that I consider the purely probabilistic-quantitative methods (now widespread in digital literary studies inadequate. An ontology, on one hand provides a tool for the analysis of strictly literary texts. On the other hand (though beyond the scope of the present work, its formalization can also represent a significant contribution towards grounding the application of storytelling methods outside of scholarly contexts.

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.

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…

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 ...

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.

Surreptitious, Evolving and Participative Ontology Development: An End-User Oriented Ontology Development Methodology

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Bachore, Zelalem

2012-01-01

Ontology not only is considered to be the backbone of the semantic web but also plays a significant role in distributed and heterogeneous information systems. However, ontology still faces limited application and adoption to date. One of the major problems is that prevailing engineering-oriented methodologies for building ontologies do not…

Adding a little reality to building ontologies for biology.

Directory of Open Access Journals (Sweden)

Phillip Lord

Full Text Available BACKGROUND: Many areas of biology are open to mathematical and computational modelling. The application of discrete, logical formalisms defines the field of biomedical ontologies. Ontologies have been put to many uses in bioinformatics. The most widespread is for description of entities about which data have been collected, allowing integration and analysis across multiple resources. There are now over 60 ontologies in active use, increasingly developed as large, international collaborations. There are, however, many opinions on how ontologies should be authored; that is, what is appropriate for representation. Recently, a common opinion has been the "realist" approach that places restrictions upon the style of modelling considered to be appropriate. METHODOLOGY/PRINCIPAL FINDINGS: Here, we use a number of case studies for describing the results of biological experiments. We investigate the ways in which these could be represented using both realist and non-realist approaches; we consider the limitations and advantages of each of these models. CONCLUSIONS/SIGNIFICANCE: From our analysis, we conclude that while realist principles may enable straight-forward modelling for some topics, there are crucial aspects of science and the phenomena it studies that do not fit into this approach; realism appears to be over-simplistic which, perversely, results in overly complex ontological models. We suggest that it is impossible to avoid compromise in modelling ontology; a clearer understanding of these compromises will better enable appropriate modelling, fulfilling the many needs for discrete mathematical models within computational biology.

Transcriptomic meta-analysis identifies gene expression characteristics in various samples of HIV-infected patients with nonprogressive disease.

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Zhang, Le-Le; Zhang, Zi-Ning; Wu, Xian; Jiang, Yong-Jun; Fu, Ya-Jing; Shang, Hong

2017-09-12

A small proportion of HIV-infected patients remain clinically and/or immunologically stable for years, including elite controllers (ECs) who have undetectable viremia (10 years). However, the mechanism of nonprogression needs to be further resolved. In this study, a transcriptome meta-analysis was performed on nonprogressor and progressor microarray data to identify differential transcriptome pathways and potential biomarkers. Using the INMEX (integrative meta-analysis of expression data) program, we performed the meta-analysis to identify consistently differentially expressed genes (DEGs) in nonprogressors and further performed functional interpretation (gene ontology analysis and pathway analysis) of the DEGs identified in the meta-analysis. Five microarray datasets (81 cases and 98 controls in total), including whole blood, CD4 + and CD8 + T cells, were collected for meta-analysis. We determined that nonprogressors have reduced expression of important interferon-stimulated genes (ISGs), CD38, lymphocyte activation gene 3 (LAG-3) in whole blood, CD4 + and CD8 + T cells. Gene ontology (GO) analysis showed a significant enrichment in DEGs that function in the type I interferon signaling pathway. Upregulated pathways, including the PI3K-Akt signaling pathway in whole blood, cytokine-cytokine receptor interaction in CD4 + T cells and the MAPK signaling pathway in CD8 + T cells, were identified in nonprogressors compared with progressors. In each metabolic functional category, the number of downregulated DEGs was more than the upregulated DEGs, and almost all genes were downregulated DEGs in the oxidative phosphorylation (OXPHOS) and tricarboxylic acid (TCA) cycle in the three types of samples. Our transcriptomic meta-analysis provides a comprehensive evaluation of the gene expression profiles in major blood types of nonprogressors, providing new insights in the understanding of HIV pathogenesis and developing strategies to delay HIV disease progression.

GeoSciGraph: An Ontological Framework for EarthCube Semantic Infrastructure

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Gupta, A.; Schachne, A.; Condit, C.; Valentine, D.; Richard, S.; Zaslavsky, I.

2015-12-01

The CINERGI (Community Inventory of EarthCube Resources for Geosciences Interoperability) project compiles an inventory of a wide variety of earth science resources including documents, catalogs, vocabularies, data models, data services, process models, information repositories, domain-specific ontologies etc. developed by research groups and data practitioners. We have developed a multidisciplinary semantic framework called GeoSciGraph semantic ingration of earth science resources. An integrated ontology is constructed with Basic Formal Ontology (BFO) as its upper ontology and currently ingests multiple component ontologies including the SWEET ontology, GeoSciML's lithology ontology, Tematres controlled vocabulary server, GeoNames, GCMD vocabularies on equipment, platforms and institutions, software ontology, CUAHSI hydrology vocabulary, the environmental ontology (ENVO) and several more. These ontologies are connected through bridging axioms; GeoSciGraph identifies lexically close terms and creates equivalence class or subclass relationships between them after human verification. GeoSciGraph allows a community to create community-specific customizations of the integrated ontology. GeoSciGraph uses the Neo4J,a graph database that can hold several billion concepts and relationships. GeoSciGraph provides a number of REST services that can be called by other software modules like the CINERGI information augmentation pipeline. 1) Vocabulary services are used to find exact and approximate terms, term categories (community-provided clusters of terms e.g., measurement-related terms or environmental material related terms), synonyms, term definitions and annotations. 2) Lexical services are used for text parsing to find entities, which can then be included into the ontology by a domain expert. 3) Graph services provide the ability to perform traversal centric operations e.g., finding paths and neighborhoods which can be used to perform ontological operations like

Ontology modularization to improve semantic medical image annotation.

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Wennerberg, Pinar; Schulz, Klaus; Buitelaar, Paul

2011-02-01

Searching for medical images and patient reports is a significant challenge in a clinical setting. The contents of such documents are often not described in sufficient detail thus making it difficult to utilize the inherent wealth of information contained within them. Semantic image annotation addresses this problem by describing the contents of images and reports using medical ontologies. Medical images and patient reports are then linked to each other through common annotations. Subsequently, search algorithms can more effectively find related sets of documents on the basis of these semantic descriptions. A prerequisite to realizing such a semantic search engine is that the data contained within should have been previously annotated with concepts from medical ontologies. One major challenge in this regard is the size and complexity of medical ontologies as annotation sources. Manual annotation is particularly time consuming labor intensive in a clinical environment. In this article we propose an approach to reducing the size of clinical ontologies for more efficient manual image and text annotation. More precisely, our goal is to identify smaller fragments of a large anatomy ontology that are relevant for annotating medical images from patients suffering from lymphoma. Our work is in the area of ontology modularization, which is a recent and active field of research. We describe our approach, methods and data set in detail and we discuss our results. Copyright © 2010 Elsevier Inc. All rights reserved.

An Ontology for Software Engineering Education

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Ling, Thong Chee; Jusoh, Yusmadi Yah; Adbullah, Rusli; Alwi, Nor Hayati

2013-01-01

Software agents communicate using ontology. It is important to build an ontology for specific domain such as Software Engineering Education. Building an ontology from scratch is not only hard, but also incur much time and cost. This study aims to propose an ontology through adaptation of the existing ontology which is originally built based on a…

A New role of ontologies and advanced scientific visualization in big data analytics

OpenAIRE

Chuprina, Svetlana

2016-01-01

Accessing and contextual semantic searching structured, semi-structured and unstructured information resources and their ontology based analysis in a uniform way across text-free Big Data query implementation is a main feature of approach under discussion. To increase the semantic power of query results’ analysis the ontology based implementation of multiplatform adaptive tools of scientific visualization are demonstrated. The ontologies are used not for integration of heterogeneous resources...

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

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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

A novel ontology approach to support design for reliability considering environmental effects.

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Sun, Bo; Li, Yu; Ye, Tianyuan; Ren, Yi

2015-01-01

Environmental effects are not considered sufficiently in product design. Reliability problems caused by environmental effects are very prominent. This paper proposes a method to apply ontology approach in product design. During product reliability design and analysis, environmental effects knowledge reusing is achieved. First, the relationship of environmental effects and product reliability is analyzed. Then environmental effects ontology to describe environmental effects domain knowledge is designed. Related concepts of environmental effects are formally defined by using the ontology approach. This model can be applied to arrange environmental effects knowledge in different environments. Finally, rubber seals used in the subhumid acid rain environment are taken as an example to illustrate ontological model application on reliability design and analysis.

OntoMaven: Maven-based Ontology Development and Management of Distributed Ontology Repositories

OpenAIRE

Paschke, Adrian

2013-01-01

In collaborative agile ontology development projects support for modular reuse of ontologies from large existing remote repositories, ontology project life cycle management, and transitive dependency management are important needs. The Apache Maven approach has proven its success in distributed collaborative Software Engineering by its widespread adoption. The contribution of this paper is a new design artifact called OntoMaven. OntoMaven adopts the Maven-based development methodology and ada...

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....

Supporting Multi-view User Ontology to Understand Company Value Chains

Science.gov (United States)

Zuo, Landong; Salvadores, Manuel; Imtiaz, Sm Hazzaz; Darlington, John; Gibbins, Nicholas; Shadbolt, Nigel R.; Dobree, James

The objective of the Market Blended Insight (MBI) project is to develop web based techniques to improve the performance of UK Business to Business (B2B) marketing activities. The analysis of company value chains is a fundamental task within MBI because it is an important model for understanding the market place and the company interactions within it. The project has aggregated rich data profiles of 3.7 million companies that form the active UK business community. The profiles are augmented by Web extractions from heterogeneous sources to provide unparalleled business insight. Advances by the Semantic Web in knowledge representation and logic reasoning allow flexible integration of data from heterogeneous sources, transformation between different representations and reasoning about their meaning. The MBI project has identified that the market insight and analysis interests of different types of users are difficult to maintain using a single domain ontology. Therefore, the project has developed a technique to undertake a plurality of analyses of value chains by deploying a distributed multi-view ontology to capture different user views over the classification of companies and their various relationships.

PIERO ontology for analysis of biochemical transformations: effective implementation of reaction information in the IUBMB enzyme list.

Science.gov (United States)

Kotera, Masaaki; Nishimura, Yosuke; Nakagawa, Zen-ichi; Muto, Ai; Moriya, Yuki; Okamoto, Shinobu; Kawashima, Shuichi; Katayama, Toshiaki; Tokimatsu, Toshiaki; Kanehisa, Minoru; Goto, Susumu

2014-12-01

Genomics is faced with the issue of many partially annotated putative enzyme-encoding genes for which activities have not yet been verified, while metabolomics is faced with the issue of many putative enzyme reactions for which full equations have not been verified. Knowledge of enzymes has been collected by IUBMB, and has been made public as the Enzyme List. To date, however, the terminology of the Enzyme List has not been assessed comprehensively by bioinformatics studies. Instead, most of the bioinformatics studies simply use the identifiers of the enzymes, i.e. the Enzyme Commission (EC) numbers. We investigated the actual usage of terminology throughout the Enzyme List, and demonstrated that the partial characteristics of reactions cannot be retrieved by simply using EC numbers. Thus, we developed a novel ontology, named PIERO, for annotating biochemical transformations as follows. First, the terminology describing enzymatic reactions was retrieved from the Enzyme List, and was grouped into those related to overall reactions and biochemical transformations. Consequently, these terms were mapped onto the actual transformations taken from enzymatic reaction equations. This ontology was linked to Gene Ontology (GO) and EC numbers, allowing the extraction of common partial reaction characteristics from given sets of orthologous genes and the elucidation of possible enzymes from the given transformations. Further future development of the PIERO ontology should enhance the Enzyme List to promote the integration of genomics and metabolomics.

Ontology of a scene based on Java 3D architecture.

Directory of Open Access Journals (Sweden)

Rubén González Crespo

2009-12-01

Full Text Available The present article seeks to make an approach to the class hierarchy of a scene built with the architecture Java 3D, to develop an ontology of a scene as from the semantic essential components for the semantic structuring of the Web3D. Java was selected because the language recommended by the W3C Consortium for the Development of the Web3D oriented applications as from X3D standard is Xj3D which compositionof their Schemas is based the architecture of Java3D In first instance identifies the domain and scope of the ontology, defining classes and subclasses that comprise from Java3D architecture and the essential elements of a scene, as its point of origin, the field of rotation, translation The limitation of the scene and the definition of shaders, then define the slots that are declared in RDF as a framework for describing the properties of the classes established from identifying thedomain and range of each class, then develops composition of the OWL ontology on SWOOP Finally, be perform instantiations of the ontology building for a Iconosphere object as from class expressions defined.

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.

Phenex: ontological annotation of phenotypic diversity.

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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.

Defining Resilience and Vulnerability Based on Ontology Engineering Approach

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Kumazawa, T.; Matsui, T.; Endo, A.

2014-12-01

It is necessary to reflect the concepts of resilience and vulnerability into the assessment framework of "Human-Environmental Security", but it is also in difficulty to identify the linkage between both concepts because of the difference of the academic community which has discussed each concept. The authors have been developing the ontology which deals with the sustainability of the social-ecological systems (SESs). Resilience and vulnerability are also the concepts in the target world which this ontology covers. Based on this point, this paper aims at explicating the semantic relationship between the concepts of resilience and vulnerability based on ontology engineering approach. For this purpose, we first examine the definitions of resilience and vulnerability which the existing literatures proposed. Second, we incorporate the definitions in the ontology dealing with sustainability of SESs. Finally, we focus on the "Water-Energy-Food Nexus Index" to assess Human-Environmental Security, and clarify how the concepts of resilience and vulnerability are linked semantically through the concepts included in these index items.

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

Applied Ontology Engineering in Cloud Services, Networks and Management Systems

CERN Document Server

Serrano Orozco, J Martín

2012-01-01

Metadata standards in today’s ICT sector are proliferating at unprecedented levels, while automated information management systems collect and process exponentially increasing quantities of data. With interoperability and knowledge exchange identified as a core challenge in the sector, this book examines the role ontology engineering can play in providing solutions to the problems of information interoperability and linked data. At the same time as introducing basic concepts of ontology engineering, the book discusses methodological approaches to formal representation of data and information models, thus facilitating information interoperability between heterogeneous, complex and distributed communication systems. In doing so, the text advocates the advantages of using ontology engineering in telecommunications systems. In addition, it offers a wealth of guidance and best-practice techniques for instances in which ontology engineering is applied in cloud services, computer networks and management systems. �...

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

Ontology-aided Data Fusion (Invited)

Science.gov (United States)

Raskin, R.

2009-12-01

An ontology provides semantic descriptions that are analogous to those in a dictionary, but are readable by both computers and humans. A data or service is semantically annotated when it is formally associated with elements of an ontology. The ESIP Federation Semantic Web Cluster has developed a set of ontologies to describe datatypes and data services that can be used to support automated data fusion. The service ontology includes descriptors of the service function, its inputs/outputs, and its invocation method. The datatype descriptors resemble typical metadata fields (data format, data model, data structure, originator, etc.) augmented with descriptions of the meaning of the data. These ontologies, in combination with the SWEET science ontology, enable a registered data fusion service to be chained together and implemented that is scientifically meaningful based on machine understanding of the associated data and services. This presentation describes initial results and experiences in automated data fusion.

An open annotation ontology for science on web 3.0.

Science.gov (United States)

Ciccarese, Paolo; Ocana, Marco; Garcia Castro, Leyla Jael; Das, Sudeshna; Clark, Tim

2011-05-17

There is currently a gap between the rich and expressive collection of published biomedical ontologies, and the natural language expression of biomedical papers consumed on a daily basis by scientific researchers. The purpose of this paper is to provide an open, shareable structure for dynamic integration of biomedical domain ontologies with the scientific document, in the form of an Annotation Ontology (AO), thus closing this gap and enabling application of formal biomedical ontologies directly to the literature as it emerges. Initial requirements for AO were elicited by analysis of integration needs between biomedical web communities, and of needs for representing and integrating results of biomedical text mining. Analysis of strengths and weaknesses of previous efforts in this area was also performed. A series of increasingly refined annotation tools were then developed along with a metadata model in OWL, and deployed for feedback and additional requirements the ontology to users at a major pharmaceutical company and a major academic center. Further requirements and critiques of the model were also elicited through discussions with many colleagues and incorporated into the work. This paper presents Annotation Ontology (AO), an open ontology in OWL-DL for annotating scientific documents on the web. AO supports both human and algorithmic content annotation. It enables "stand-off" or independent metadata anchored to specific positions in a web document by any one of several methods. In AO, the document may be annotated but is not required to be under update control of the annotator. AO contains a provenance model to support versioning, and a set model for specifying groups and containers of annotation. AO is freely available under open source license at http://purl.org/ao/, and extensive documentation including screencasts is available on AO's Google Code page: http://code.google.com/p/annotation-ontology/ . The Annotation Ontology meets critical requirements for

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.

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.

A Customizable Language Learning Support System Using Ontology-Driven Engine

Science.gov (United States)

Wang, Jingyun; Mendori, Takahiko; Xiong, Juan

2013-01-01

This paper proposes a framework for web-based language learning support systems designed to provide customizable pedagogical procedures based on the analysis of characteristics of both learner and course. This framework employs a course-centered ontology and a teaching method ontology as the foundation for the student model, which includes learner…

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…

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....

Ontology-based literature mining of E. coli vaccine-associated gene interaction networks.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; He, Yongqun

2017-03-14

Pathogenic Escherichia coli infections cause various diseases in humans and many animal species. However, with extensive E. coli vaccine research, we are still unable to fully protect ourselves against E. coli infections. To more rational development of effective and safe E. coli vaccine, it is important to better understand E. coli vaccine-associated gene interaction networks. In this study, we first extended the Vaccine Ontology (VO) to semantically represent various E. coli vaccines and genes used in the vaccine development. We also normalized E. coli gene names compiled from the annotations of various E. coli strains using a pan-genome-based annotation strategy. The Interaction Network Ontology (INO) includes a hierarchy of various interaction-related keywords useful for literature mining. Using VO, INO, and normalized E. coli gene names, we applied an ontology-based SciMiner literature mining strategy to mine all PubMed abstracts and retrieve E. coli vaccine-associated E. coli gene interactions. Four centrality metrics (i.e., degree, eigenvector, closeness, and betweenness) were calculated for identifying highly ranked genes and interaction types. Using vaccine-related PubMed abstracts, our study identified 11,350 sentences that contain 88 unique INO interactions types and 1,781 unique E. coli genes. Each sentence contained at least one interaction type and two unique E. coli genes. An E. coli gene interaction network of genes and INO interaction types was created. From this big network, a sub-network consisting of 5 E. coli vaccine genes, including carA, carB, fimH, fepA, and vat, and 62 other E. coli genes, and 25 INO interaction types was identified. While many interaction types represent direct interactions between two indicated genes, our study has also shown that many of these retrieved interaction types are indirect in that the two genes participated in the specified interaction process in a required but indirect process. Our centrality analysis of

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

Aplicación de visualización de una ontología para el dominio del análisis del semen humano Application to visualize an ontology for the human semen analysis domain

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Roberto Casañas

2007-06-01

Full Text Available En este trabajo se presenta el diseño e implementación de una ontología para el dominio del análisis del semen humano, cuyo objetivo es representar, organizar, formalizar y estandarizar el conocimiento del dominio, para que éste pueda ser compartido y reutilizado por distintos grupos de personas y aplicaciones de software. Para visualizar la ontología se desarrolló una aplicación basada en una arquitectura cliente/servidor para ambientes Web, la cual está constituida por un módulo de Administración y otro de Acceso Público. A través del primero se mantiene el sitio Web de la ontología, mientras que el segundo permite a los usuarios acceder al conocimiento almacenado y a un conjunto de recursos tales como imágenes, videos, artículos relativos al dominio, manuales y protocolos de laboratorio. La arquitectura propuesta facilita la observación y recuperación de las complejas estructuras de conocimiento, así como la navegación y administración de la información representada en la ontología. El enfoque utilizado en el diseño de los mecanismos de recuperación de información está dirigido tanto a usuarios poco familiarizados con el vocabulario del dominio, como a aquellos que ya lo conocen. Esta funcionalidad es de especial interés dado lo heterogénea que resulta la audiencia a la que está dirigida la ontología, como son profesionales y estudiantes de las ciencias de la salud, entre otros. La metodología Methontology fue seleccionada para desarrollar la ontología y se utilizó el editor Protégé para su implementación.The following work presents the design and implementation of an ontology for human semen analysis whose objective is to present, organize, formalize and standardize the domain knowledge, in order to be shared and reused by different groups of people and software applications. To visualize this ontology, a Web application based on a client/server architecture was developed, which is constituted by an

An ontology for component-based models of water resource systems

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Elag, Mostafa; Goodall, Jonathan L.

2013-08-01

Component-based modeling is an approach for simulating water resource systems where a model is composed of a set of components, each with a defined modeling objective, interlinked through data exchanges. Component-based modeling frameworks are used within the hydrologic, atmospheric, and earth surface dynamics modeling communities. While these efforts have been advancing, it has become clear that the water resources modeling community in particular, and arguably the larger earth science modeling community as well, faces a challenge of fully and precisely defining the metadata for model components. The lack of a unified framework for model component metadata limits interoperability between modeling communities and the reuse of models across modeling frameworks due to ambiguity about the model and its capabilities. To address this need, we propose an ontology for water resources model components that describes core concepts and relationships using the Web Ontology Language (OWL). The ontology that we present, which is termed the Water Resources Component (WRC) ontology, is meant to serve as a starting point that can be refined over time through engagement by the larger community until a robust knowledge framework for water resource model components is achieved. This paper presents the methodology used to arrive at the WRC ontology, the WRC ontology itself, and examples of how the ontology can aid in component-based water resources modeling by (i) assisting in identifying relevant models, (ii) encouraging proper model coupling, and (iii) facilitating interoperability across earth science modeling frameworks.

TermGenie - a web-application for pattern-based ontology class generation.

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Dietze, Heiko; Berardini, Tanya Z; Foulger, Rebecca E; Hill, David P; Lomax, Jane; Osumi-Sutherland, David; Roncaglia, Paola; Mungall, Christopher J

2014-01-01

Biological ontologies are continually growing and improving from requests for new classes (terms) by biocurators. These ontology requests can frequently create bottlenecks in the biocuration process, as ontology developers struggle to keep up, while manually processing these requests and create classes. TermGenie allows biocurators to generate new classes based on formally specified design patterns or templates. The system is web-based and can be accessed by any authorized curator through a web browser. Automated rules and reasoning engines are used to ensure validity, uniqueness and relationship to pre-existing classes. In the last 4 years the Gene Ontology TermGenie generated 4715 new classes, about 51.4% of all new classes created. The immediate generation of permanent identifiers proved not to be an issue with only 70 (1.4%) obsoleted classes. TermGenie is a web-based class-generation system that complements traditional ontology development tools. All classes added through pre-defined templates are guaranteed to have OWL equivalence axioms that are used for automatic classification and in some cases inter-ontology linkage. At the same time, the system is simple and intuitive and can be used by most biocurators without extensive training.

CREATION OF IT-ORIENTED ONTOLOGICAL FRAMEWORK FOR THE PURPOSE OF MAKING EDUCATIONAL PROGRAMS ON THE BASE OF COMPETENCIES

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G. M. Korotenko

2017-08-01

Full Text Available Purpose. Taking into account the expansion of computing application scopes there is a need to identify the links and features of the constantly emerging professional competencies of the new sections of computing knowledge to improve the process of forming new curricula. Methodology. Authors propose the new approach aimed to build specialized knowledge bases generated using artificial intelligence technology and focused on the use of multiple heterogeneous resources or data sources on specific educational topics is proposed. As a tool, ensuring the formation of the base ontology the Protégé 4.2 ontology editor is used. As one of the modules of the developed system of semantic analysis, which provides access to ontology and the possibility of its processing, the Apache Jena Java framework should be used, which forms the software environment for working with data in RDF, RDFS and OWL formats, and also supports the ability to form queries to Ontologies in the SPARQL language. The peculiarity of this approach is the binding of information resources of the three-platform presentation of the disciplinary structure in the context of identifying the links of professional competencies. Findings. The model and structure of the IT-oriented ontological framework designed to ensure the components convergence of the university three-platform information and communication environment are developed. The structure of the knowledge base ontology-basis, describing the main essence of the educational standards of the "Information Technologies" branch is formed. Originality. Within the framework of design and formation of the knowledge sector disciplinary structure "Information Technologies" in the context of the competence approach to education, the architecture of the competence descriptors of semantic analysis system is proposed. It implements the algorithm for integrating the ontological and product models of knowledge representation about the subject domain

Building a developmental toxicity ontology.

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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.

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

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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.

MELLO: Medical lifelog ontology for data terms from self-tracking and lifelog devices.

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Kim, Hye Hyeon; Lee, Soo Youn; Baik, Su Youn; Kim, Ju Han

2015-12-01

The increasing use of health self-tracking devices is making the integration of heterogeneous data and shared decision-making more challenging. Computational analysis of lifelog data has been hampered by the lack of semantic and syntactic consistency among lifelog terms and related ontologies. Medical lifelog ontology (MELLO) was developed by identifying lifelog concepts and relationships between concepts, and it provides clear definitions by following ontology development methods. MELLO aims to support the classification and semantic mapping of lifelog data from diverse health self-tracking devices. MELLO was developed using the General Formal Ontology method with a manual iterative process comprising five steps: (1) defining the scope of lifelog data, (2) identifying lifelog concepts, (3) assigning relationships among MELLO concepts, (4) developing MELLO properties (e.g., synonyms, preferred terms, and definitions) for each MELLO concept, and (5) evaluating representative layers of the ontology content. An evaluation was performed by classifying 11 devices into 3 classes by subjects, and performing pairwise comparisons of lifelog terms among 5 devices in each class as measured using the Jaccard similarity index. MELLO represents a comprehensive knowledge base of 1998 lifelog concepts, with 4996 synonyms for 1211 (61%) concepts and 1395 definitions for 926 (46%) concepts. The MELLO Browser and MELLO Mapper provide convenient access and annotating non-standard proprietary terms with MELLO (http://mello.snubi.org/). MELLO covers 88.1% of lifelog terms from 11 health self-tracking devices and uses simple string matching to match semantically similar terms provided by various devices that are not yet integrated. The results from the comparisons of Jaccard similarities between simple string matching and MELLO matching revealed increases of 2.5, 2.2, and 5.7 folds for physical activity,body measure, and sleep classes, respectively. MELLO is the first ontology for

USE OF ONTOLOGIES FOR KNOWLEDGE BASES CREATION TUTORING COMPUTER SYSTEMS

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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

Phenotype ontologies and cross-species analysis for translational research.

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Peter N Robinson

2014-04-01

Full Text Available The use of model organisms as tools for the investigation of human genetic variation has significantly and rapidly advanced our understanding of the aetiologies underlying hereditary traits. However, while equivalences in the DNA sequence of two species may be readily inferred through evolutionary models, the identification of equivalence in the phenotypic consequences resulting from comparable genetic variation is far from straightforward, limiting the value of the modelling paradigm. In this review, we provide an overview of the emerging statistical and computational approaches to objectively identify phenotypic equivalence between human and model organisms with examples from the vertebrate models, mouse and zebrafish. Firstly, we discuss enrichment approaches, which deem the most frequent phenotype among the orthologues of a set of genes associated with a common human phenotype as the orthologous phenotype, or phenolog, in the model species. Secondly, we introduce and discuss computational reasoning approaches to identify phenotypic equivalences made possible through the development of intra- and interspecies ontologies. Finally, we consider the particular challenges involved in modelling neuropsychiatric disorders, which illustrate many of the remaining difficulties in developing comprehensive and unequivocal interspecies phenotype mappings.

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

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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.

Gradient Learning Algorithms for Ontology Computing

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Gao, Wei; Zhu, Linli

2014-01-01

The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting. PMID:25530752

Gradient Learning Algorithms for Ontology Computing

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Wei Gao

2014-01-01

Full Text Available The gradient learning model has been raising great attention in view of its promising perspectives for applications in statistics, data dimensionality reducing, and other specific fields. In this paper, we raise a new gradient learning model for ontology similarity measuring and ontology mapping in multidividing setting. The sample error in this setting is given by virtue of the hypothesis space and the trick of ontology dividing operator. Finally, two experiments presented on plant and humanoid robotics field verify the efficiency of the new computation model for ontology similarity measure and ontology mapping applications in multidividing setting.

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

Towards Ontology-Driven Information Systems: Guidelines to the Creation of New Methodologies to Build Ontologies

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Soares, Andrey

2009-01-01

This research targeted the area of Ontology-Driven Information Systems, where ontology plays a central role both at development time and at run time of Information Systems (IS). In particular, the research focused on the process of building domain ontologies for IS modeling. The motivation behind the research was the fact that researchers have…

Database Concepts in a Domain Ontology

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Gorskis Henrihs

2017-12-01

Full Text Available There are multiple approaches for mapping from a domain ontology to a database in the task of ontology-based data access. For that purpose, external mapping documents are most commonly used. These documents describe how the data necessary for the description of ontology individuals and other values, are to be obtained from the database. The present paper investigates the use of special database concepts. These concepts are not separated from the domain ontology; they are mixed with domain concepts to form a combined application ontology. By creating natural relationships between database concepts and domain concepts, mapping can be implemented more easily and with a specific purpose. The paper also investigates how the use of such database concepts in addition to domain concepts impacts ontology building and data retrieval.

Identifying disease-centric subdomains in very large medical ontologies : A case-study on breast cancer concepts in SNOMED CT. Or: Finding 2500 out of 300.000

NARCIS (Netherlands)

Milian, Krystyna; Aleksovski, Zharko; Vdovjak, Richard; Ten Teije, Annette; Van Harmelen, Frank

2010-01-01

Modern medical vocabularies can contain up to hundreds of thousands of concepts. In any particular use-case only a small fraction of these will be needed. In this paper we first define two notions of a disease-centric subdomain of a large ontology. We then explore two methods for identifying

A high-resolution anatomical ontology of the developing murine genitourinary tract

Science.gov (United States)

Little, Melissa H.; Brennan, Jane; Georgas, Kylie; Davies, Jamie A.; Davidson, Duncan R.; Baldock, Richard A.; Beverdam, Annemiek; Bertram, John F.; Capel, Blanche; Chiu, Han Sheng; Clements, Dave; Cullen-McEwen, Luise; Fleming, Jean; Gilbert, Thierry; Houghton, Derek; Kaufman, Matt H.; Kleymenova, Elena; Koopman, Peter A.; Lewis, Alfor G.; McMahon, Andrew P.; Mendelsohn, Cathy L.; Mitchell, Eleanor K.; Rumballe, Bree A.; Sweeney, Derina E.; Valerius, M. Todd; Yamada, Gen; Yang, Yiya; Yu., Jing

2007-01-01

Cataloguing gene expression during development of the genitourinary tract will increase our understanding not only of this process but also of congenital defects and disease affecting this organ system. We have developed a high-resolution ontology with which to describe the subcompartments of the developing murine genitourinary tract. This ontology incorporates what can be defined histologically and begins to encompass other structures and cell types already identified at the molecular level. The ontology is being used to annotate in situ hybridisation data generated as part of the Genitourinary Development Molecular Anatomy Project (GUDMAP), a publicly available data resource on gene and protein expression during genitourinary development. The GUDMAP ontology encompasses Theiler stage (TS) 17 to 27 of development as well as the sexually mature adult. It has been written as a partonomic, text-based, hierarchical ontology that, for the embryological stages, has been developed as a high-resolution expansion of the existing Edinburgh Mouse Atlas Project (EMAP) ontology. It also includes group terms for well-characterised structural and/or functional units comprising several sub-structures, such as the nephron and juxtaglomerular complex. Each term has been assigned a unique identification number. Synonyms have been used to improve the success of query searching and maintain wherever possible existing EMAP terms relating to this organ system. We describe here the principles and structure of the ontology and provide representative diagrammatic, histological, and whole mount and section RNA in situ hybridisation images to clarify the terms used within the ontology. Visual examples of how terms appear in different specimen types are also provided. PMID:17452023

On Algebraic Spectrum of Ontology Evaluation

OpenAIRE

Adekoya Adebayo Felix; kinwale Adio Taofiki; Sofoluwe Adetokunbo

2011-01-01

Ontology evaluation remains an important open problem in the area of its application. The ontology structure evaluation framework for benchmarking the internal graph structures was proposed. The framework was used in transport and biochemical ontology. The corresponding adjacency, incidence matrices and other structural properties due to the class hierarchical structure of the transport and biochemical ontology were computed using MATLAB. The results showed that the choice of suitable choice ...

MIRO: guidelines for minimum information for the reporting of an ontology.

Science.gov (United States)

Matentzoglu, Nicolas; Malone, James; Mungall, Chris; Stevens, Robert

2018-01-18

Creation and use of ontologies has become a mainstream activity in many disciplines, in particular, the biomedical domain. Ontology developers often disseminate information about these ontologies in peer-reviewed ontology description reports. There appears to be, however, a high degree of variability in the content of these reports. Often, important details are omitted such that it is difficult to gain a sufficient understanding of the ontology, its content and method of creation. We propose the Minimum Information for Reporting an Ontology (MIRO) guidelines as a means to facilitate a higher degree of completeness and consistency between ontology documentation, including published papers, and ultimately a higher standard of report quality. A draft of the MIRO guidelines was circulated for public comment in the form of a questionnaire, and we subsequently collected 110 responses from ontology authors, developers, users and reviewers. We report on the feedback of this consultation, including comments on each guideline, and present our analysis on the relative importance of each MIRO information item. These results were used to update the MIRO guidelines, mainly by providing more detailed operational definitions of the individual items and assigning degrees of importance. Based on our revised version of MIRO, we conducted a review of 15 recently published ontology description reports from three important journals in the Semantic Web and Biomedical domain and analysed them for compliance with the MIRO guidelines. We found that only 41.38% of the information items were covered by the majority of the papers (and deemed important by the survey respondents) and a large number of important items are not covered at all, like those related to testing and versioning policies. We believe that the community-reviewed MIRO guidelines can contribute to improving significantly the quality of ontology description reports and other documentation, in particular by increasing consistent

Use of Ontologies for Data Integration and Curation

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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.

The Ontology Lookup Service, a lightweight cross-platform tool for controlled vocabulary queries

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Apweiler Rolf

2006-02-01

Full Text Available Abstract Background With the vast amounts of biomedical data being generated by high-throughput analysis methods, controlled vocabularies and ontologies are becoming increasingly important to annotate units of information for ease of search and retrieval. Each scientific community tends to create its own locally available ontology. The interfaces to query these ontologies tend to vary from group to group. We saw the need for a centralized location to perform controlled vocabulary queries that would offer both a lightweight web-accessible user interface as well as a consistent, unified SOAP interface for automated queries. Results The Ontology Lookup Service (OLS was created to integrate publicly available biomedical ontologies into a single database. All modified ontologies are updated daily. A list of currently loaded ontologies is available online. The database can be queried to obtain information on a single term or to browse a complete ontology using AJAX. Auto-completion provides a user-friendly search mechanism. An AJAX-based ontology viewer is available to browse a complete ontology or subsets of it. A programmatic interface is available to query the webservice using SOAP. The service is described by a WSDL descriptor file available online. A sample Java client to connect to the webservice using SOAP is available for download from SourceForge. All OLS source code is publicly available under the open source Apache Licence. Conclusion The OLS provides a user-friendly single entry point for publicly available ontologies in the Open Biomedical Ontology (OBO format. It can be accessed interactively or programmatically at http://www.ebi.ac.uk/ontology-lookup/.

A meta-ontological framework for multi-agent systems design

OpenAIRE

Sokolova, Marina; Fernández Caballero, Antonio

2007-01-01

The paper introduces an approach to using a meta-ontology framework for complex multi-agent systems design, and illustrates it in an application related to ecological-medical issues. The described shared ontology is pooled from private sub-ontologies, which represent a problem area ontology, an agent ontology, a task ontology, an ontology of interactions, and the multi-agent system architecture ontology.

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.

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

Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available switchLanguage; BLAST Search Image Search Home About Archive Update History Data List Contact us FANTOM....biosciencedbc.jp/archive/fantom5/datafiles/LATEST/extra/Ontology/ File size: 1.8 MB Simple search URL - Dat...t Us Sample ontology, GOstat and ontology term enrichment - FANTOM5 | LSDB Archive ...

Community-based Ontology Development, Annotation and Discussion with MediaWiki extension Ontokiwi and Ontokiwi-based Ontobedia

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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

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

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

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.

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

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

InfAcrOnt: calculating cross-ontology term similarities using information flow by a random walk.

Science.gov (United States)

Cheng, Liang; Jiang, Yue; Ju, Hong; Sun, Jie; Peng, Jiajie; Zhou, Meng; Hu, Yang

2018-01-19

Since the establishment of the first biomedical ontology Gene Ontology (GO), the number of biomedical ontology has increased dramatically. Nowadays over 300 ontologies have been built including extensively used Disease Ontology (DO) and Human Phenotype Ontology (HPO). Because of the advantage of identifying novel relationships between terms, calculating similarity between ontology terms is one of the major tasks in this research area. Though similarities between terms within each ontology have been studied with in silico methods, term similarities across different ontologies were not investigated as deeply. The latest method took advantage of gene functional interaction network (GFIN) to explore such inter-ontology similarities of terms. However, it only used gene interactions and failed to make full use of the connectivity among gene nodes of the network. In addition, all existent methods are particularly designed for GO and their performances on the extended ontology community remain unknown. We proposed a method InfAcrOnt to infer similarities between terms across ontologies utilizing the entire GFIN. InfAcrOnt builds a term-gene-gene network which comprised ontology annotations and GFIN, and acquires similarities between terms across ontologies through modeling the information flow within the network by random walk. In our benchmark experiments on sub-ontologies of GO, InfAcrOnt achieves a high average area under the receiver operating characteristic curve (AUC) (0.9322 and 0.9309) and low standard deviations (1.8746e-6 and 3.0977e-6) in both human and yeast benchmark datasets exhibiting superior performance. Meanwhile, comparisons of InfAcrOnt results and prior knowledge on pair-wise DO-HPO terms and pair-wise DO-GO terms show high correlations. The experiment results show that InfAcrOnt significantly improves the performance of inferring similarities between terms across ontologies in benchmark set.

Proposed actions are no actions: re-modeling an ontology design pattern with a realist top-level ontology.

Science.gov (United States)

Seddig-Raufie, Djamila; Jansen, Ludger; Schober, Daniel; Boeker, Martin; Grewe, Niels; Schulz, Stefan

2012-09-21

Ontology Design Patterns (ODPs) are representational artifacts devised to offer solutions for recurring ontology design problems. They promise to enhance the ontology building process in terms of flexibility, re-usability and expansion, and to make the result of ontology engineering more predictable. In this paper, we analyze ODP repositories and investigate their relation with upper-level ontologies. In particular, we compare the BioTop upper ontology to the Action ODP from the NeOn an ODP repository. In view of the differences in the respective approaches, we investigate whether the Action ODP can be embedded into BioTop. We demonstrate that this requires re-interpreting the meaning of classes of the NeOn Action ODP in the light of the precepts of realist ontologies. As a result, the re-design required clarifying the ontological commitment of the ODP classes by assigning them to top-level categories. Thus, ambiguous definitions are avoided. Classes of real entities are clearly distinguished from classes of information artifacts. The proposed approach avoids the commitment to the existence of unclear future entities which underlies the NeOn Action ODP. Our re-design is parsimonious in the sense that existing BioTop content proved to be largely sufficient to define the different types of actions and plans. The proposed model demonstrates that an expressive upper-level ontology provides enough resources and expressivity to represent even complex ODPs, here shown with the different flavors of Action as proposed in the NeOn ODP. The advantage of ODP inclusion into a top-level ontology is the given predetermined dependency of each class, an existing backbone structure and well-defined relations. Our comparison shows that the use of some ODPs is more likely to cause problems for ontology developers, rather than to guide them. Besides the structural properties, the explanation of classification results were particularly hard to grasp for 'self-sufficient' ODPs as

Structure-based classification and ontology in chemistry

Directory of Open Access Journals (Sweden)

Hastings Janna

2012-04-01

Full Text Available Abstract Background Recent years have seen an explosion in the availability of data in the chemistry domain. With this information explosion, however, retrieving relevant results from the available information, and organising those results, become even harder problems. Computational processing is essential to filter and organise the available resources so as to better facilitate the work of scientists. Ontologies encode expert domain knowledge in a hierarchically organised machine-processable format. One such ontology for the chemical domain is ChEBI. ChEBI provides a classification of chemicals based on their structural features and a role or activity-based classification. An example of a structure-based class is 'pentacyclic compound' (compounds containing five-ring structures, while an example of a role-based class is 'analgesic', since many different chemicals can act as analgesics without sharing structural features. Structure-based classification in chemistry exploits elegant regularities and symmetries in the underlying chemical domain. As yet, there has been neither a systematic analysis of the types of structural classification in use in chemistry nor a comparison to the capabilities of available technologies. Results We analyze the different categories of structural classes in chemistry, presenting a list of patterns for features found in class definitions. We compare these patterns of class definition to tools which allow for automation of hierarchy construction within cheminformatics and within logic-based ontology technology, going into detail in the latter case with respect to the expressive capabilities of the Web Ontology Language and recent extensions for modelling structured objects. Finally we discuss the relationships and interactions between cheminformatics approaches and logic-based approaches. Conclusion Systems that perform intelligent reasoning tasks on chemistry data require a diverse set of underlying computational

Development and application of an interaction network ontology for literature mining of vaccine-associated gene-gene interactions.

Science.gov (United States)

Hur, Junguk; Özgür, Arzucan; Xiang, Zuoshuang; He, Yongqun

2015-01-01

Literature mining of gene-gene interactions has been enhanced by ontology-based name classifications. However, in biomedical literature mining, interaction keywords have not been carefully studied and used beyond a collection of keywords. In this study, we report the development of a new Interaction Network Ontology (INO) that classifies >800 interaction keywords and incorporates interaction terms from the PSI Molecular Interactions (PSI-MI) and Gene Ontology (GO). Using INO-based literature mining results, a modified Fisher's exact test was established to analyze significantly over- and under-represented enriched gene-gene interaction types within a specific area. Such a strategy was applied to study the vaccine-mediated gene-gene interactions using all PubMed abstracts. The Vaccine Ontology (VO) and INO were used to support the retrieval of vaccine terms and interaction keywords from the literature. INO is aligned with the Basic Formal Ontology (BFO) and imports terms from 10 other existing ontologies. Current INO includes 540 terms. In terms of interaction-related terms, INO imports and aligns PSI-MI and GO interaction terms and includes over 100 newly generated ontology terms with 'INO_' prefix. A new annotation property, 'has literature mining keywords', was generated to allow the listing of different keywords mapping to the interaction types in INO. Using all PubMed documents published as of 12/31/2013, approximately 266,000 vaccine-associated documents were identified, and a total of 6,116 gene-pairs were associated with at least one INO term. Out of 78 INO interaction terms associated with at least five gene-pairs of the vaccine-associated sub-network, 14 terms were significantly over-represented (i.e., more frequently used) and 17 under-represented based on our modified Fisher's exact test. These over-represented and under-represented terms share some common top-level terms but are distinct at the bottom levels of the INO hierarchy. The analysis of these

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.

Vaccine and Drug Ontology Studies (VDOS 2014).

Science.gov (United States)

Tao, Cui; He, Yongqun; Arabandi, Sivaram

2016-01-01

The "Vaccine and Drug Ontology Studies" (VDOS) international workshop series focuses on vaccine- and drug-related ontology modeling and applications. Drugs and vaccines have been critical to prevent and treat human and animal diseases. Work in both (drugs and vaccines) areas is closely related - from preclinical research and development to manufacturing, clinical trials, government approval and regulation, and post-licensure usage surveillance and monitoring. Over the last decade, tremendous efforts have been made in the biomedical ontology community to ontologically represent various areas associated with vaccines and drugs - extending existing clinical terminology systems such as SNOMED, RxNorm, NDF-RT, and MedDRA, developing new models such as the Vaccine Ontology (VO) and Ontology of Adverse Events (OAE), vernacular medical terminologies such as the Consumer Health Vocabulary (CHV). The VDOS workshop series provides a platform for discussing innovative solutions as well as the challenges in the development and applications of biomedical ontologies for representing and analyzing drugs and vaccines, their administration, host immune responses, adverse events, and other related topics. The five full-length papers included in this 2014 thematic issue focus on two main themes: (i) General vaccine/drug-related ontology development and exploration, and (ii) Interaction and network-related ontology studies.

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...

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.

OMIT: dynamic, semi-automated ontology development for the microRNA domain.

Directory of Open Access Journals (Sweden)

Jingshan Huang

Full Text Available As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT, the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

OMIT: dynamic, semi-automated ontology development for the microRNA domain.

Science.gov (United States)

Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A; Natale, Darren A; Tan, Ming

2014-01-01

As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology.

OMIT: Dynamic, Semi-Automated Ontology Development for the microRNA Domain

Science.gov (United States)

Huang, Jingshan; Dang, Jiangbo; Borchert, Glen M.; Eilbeck, Karen; Zhang, He; Xiong, Min; Jiang, Weijian; Wu, Hao; Blake, Judith A.; Natale, Darren A.; Tan, Ming

2014-01-01

As a special class of short non-coding RNAs, microRNAs (a.k.a. miRNAs or miRs) have been reported to perform important roles in various biological processes by regulating respective target genes. However, significant barriers exist during biologists' conventional miR knowledge discovery. Emerging semantic technologies, which are based upon domain ontologies, can render critical assistance to this problem. Our previous research has investigated the construction of a miR ontology, named Ontology for MIcroRNA Target Prediction (OMIT), the very first of its kind that formally encodes miR domain knowledge. Although it is unavoidable to have a manual component contributed by domain experts when building ontologies, many challenges have been identified for a completely manual development process. The most significant issue is that a manual development process is very labor-intensive and thus extremely expensive. Therefore, we propose in this paper an innovative ontology development methodology. Our contributions can be summarized as: (i) We have continued the development and critical improvement of OMIT, solidly based on our previous research outcomes. (ii) We have explored effective and efficient algorithms with which the ontology development can be seamlessly combined with machine intelligence and be accomplished in a semi-automated manner, thus significantly reducing large amounts of human efforts. A set of experiments have been conducted to thoroughly evaluate our proposed methodology. PMID:25025130

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....

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

Using concept similarity in cross ontology for adaptive e-Learning systems

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B. Saleena

2015-01-01

Full Text Available e-Learning is one of the most preferred media of learning by the learners. The learners search the web to gather knowledge about a particular topic from the information in the repositories. Retrieval of relevant materials from a domain can be easily implemented if the information is organized and related in some way. Ontologies are a key concept that helps us to relate information for providing the more relevant lessons to the learner. This paper proposes an adaptive e-Learning system, which generates a user specific e-Learning content by comparing the concepts with more than one system using similarity measures. A cross ontology measure is defined, which consists of fuzzy domain ontology as the primary ontology and the domain expert’s ontology as the secondary ontology, for the comparison process. A personalized document is provided to the user with a user profile, which includes the data obtained from the processing of the proposed method under a User score, which is obtained through the user evaluation. The results of the proposed e-Learning system under the designed cross ontology similarity measure show a significant increase in performance and accuracy under different conditions. The assessment of the comparative analysis, showed the difference in performance of our proposed method over other methods. Based on the assessment results it is proved that the proposed approach is effective over other methods.

An ontology-driven tool for structured data acquisition using Web forms.

Science.gov (United States)

Gonçalves, Rafael S; Tu, Samson W; Nyulas, Csongor I; Tierney, Michael J; Musen, Mark A

2017-08-01

Structured data acquisition is a common task that is widely performed in biomedicine. However, current solutions for this task are far from providing a means to structure data in such a way that it can be automatically employed in decision making (e.g., in our example application domain of clinical functional assessment, for determining eligibility for disability benefits) based on conclusions derived from acquired data (e.g., assessment of impaired motor function). To use data in these settings, we need it structured in a way that can be exploited by automated reasoning systems, for instance, in the Web Ontology Language (OWL); the de facto ontology language for the Web. We tackle the problem of generating Web-based assessment forms from OWL ontologies, and aggregating input gathered through these forms as an ontology of "semantically-enriched" form data that can be queried using an RDF query language, such as SPARQL. We developed an ontology-based structured data acquisition system, which we present through its specific application to the clinical functional assessment domain. We found that data gathered through our system is highly amenable to automatic analysis using queries. We demonstrated how ontologies can be used to help structuring Web-based forms and to semantically enrich the data elements of the acquired structured data. The ontologies associated with the enriched data elements enable automated inferences and provide a rich vocabulary for performing queries.

Anatomy Ontology Matching Using Markov Logic Networks

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Chunhua Li

2016-01-01

Full Text Available The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we need to establish relationships between ontologies describing different species. Ontology matching is a kind of solutions to find semantic correspondences between entities of different ontologies. Markov logic networks which unify probabilistic graphical model and first-order logic provide an excellent framework for ontology matching. We combine several different matching strategies through first-order logic formulas according to the structure of anatomy ontologies. Experiments on the adult mouse anatomy and the human anatomy have demonstrated the effectiveness of proposed approach in terms of the quality of result alignment.

Towards an “Internet of Food”: Food Ontologies for the Internet of Things

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Maged N. Kamel Boulos

2015-10-01

Full Text Available Automated food and drink recognition methods connect to cloud-based lookup databases (e.g., food item barcodes, previously identified food images, or previously classified NIR (Near Infrared spectra of food and drink items databases to match and identify a scanned food or drink item, and report the results back to the user. However, these methods remain of limited value if we cannot further reason with the identified food and drink items, ingredients and quantities/portion sizes in a proposed meal in various contexts; i.e., understand from a semantic perspective their types, properties, and interrelationships in the context of a given user’s health condition and preferences. In this paper, we review a number of “food ontologies”, such as the Food Products Ontology/FOODpedia (by Kolchin and Zamula, Open Food Facts (by Gigandet et al., FoodWiki (Ontology-driven Mobile Safe Food Consumption System by Celik, FOODS-Diabetes Edition (A Food-Oriented Ontology-Driven System by Snae Namahoot and Bruckner, and AGROVOC multilingual agricultural thesaurus (by the UN Food and Agriculture Organization—FAO. These food ontologies, with appropriate modifications (or as a basis, to be added to and further expanded and together with other relevant non-food ontologies (e.g., about diet-sensitive disease conditions, can supplement the aforementioned lookup databases to enable progression from the mere automated identification of food and drinks in our meals to a more useful application whereby we can automatically reason with the identified food and drink items and their details (quantities and ingredients/bromatological composition in order to better assist users in making the correct, healthy food and drink choices for their particular health condition, age, body weight/BMI (Body Mass Index, lifestyle and preferences, etc.

Individual Building Extraction from TerraSAR-X Images Based on Ontological Semantic Analysis

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Rong Gui

2016-08-01

Full Text Available Accurate building information plays a crucial role for urban planning, human settlements and environmental management. Synthetic aperture radar (SAR images, which deliver images with metric resolution, allow for analyzing and extracting detailed information on urban areas. In this paper, we consider the problem of extracting individual buildings from SAR images based on domain ontology. By analyzing a building scattering model with different orientations and structures, the building ontology model is set up to express multiple characteristics of individual buildings. Under this semantic expression framework, an object-based SAR image segmentation method is adopted to provide homogeneous image objects, and three categories of image object features are extracted. Semantic rules are implemented by organizing image object features, and the individual building objects expression based on an ontological semantic description is formed. Finally, the building primitives are used to detect buildings among the available image objects. Experiments on TerraSAR-X images of Foshan city, China, with a spatial resolution of 1.25 m × 1.25 m, have shown the total extraction rates are above 84%. The results indicate the ontological semantic method can exactly extract flat-roof and gable-roof buildings larger than 250 pixels with different orientations.

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...

Model Driven Engineering with Ontology Technologies

Science.gov (United States)

Staab, Steffen; Walter, Tobias; Gröner, Gerd; Parreiras, Fernando Silva

Ontologies constitute formal models of some aspect of the world that may be used for drawing interesting logical conclusions even for large models. Software models capture relevant characteristics of a software artifact to be developed, yet, most often these software models have limited formal semantics, or the underlying (often graphical) software language varies from case to case in a way that makes it hard if not impossible to fix its semantics. In this contribution, we survey the use of ontology technologies for software modeling in order to carry over advantages from ontology technologies to the software modeling domain. It will turn out that ontology-based metamodels constitute a core means for exploiting expressive ontology reasoning in the software modeling domain while remaining flexible enough to accommodate varying needs of software modelers.

Ontology Matching for Big Data Applications in the Smart Dairy Farming Domain.

NARCIS (Netherlands)

Verhoosel, J.P.C.; Bekkum, M.A. van; Evert, F.K. van

2015-01-01

This paper addresses the use of ontologies for combining different sensor data sources to enable big data analysis in the dairy farming domain. We have made existing data sources accessible via linked data RDF mechanisms using OWL ontologies on Virtuoso and D2RQ triple stores. In addition, we have

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.

Ontology-based content analysis of US patent applications from 2001-2010.

Science.gov (United States)

Weber, Lutz; Böhme, Timo; Irmer, Matthias

2013-01-01

Ontology-based semantic text analysis methods allow to automatically extract knowledge relationships and data from text documents. In this review, we have applied these technologies for the systematic analysis of pharmaceutical patents. Hierarchical concepts from the knowledge domains of chemical compounds, diseases and proteins were used to annotate full-text US patent applications that deal with pharmacological activities of chemical compounds and filed in the years 2001-2010. Compounds claimed in these applications have been classified into their respective compound classes to review the distribution of scaffold types or general compound classes such as natural products in a time-dependent manner. Similarly, the target proteins and claimed utility of the compounds have been classified and the most relevant were extracted. The method presented allows the discovery of the main areas of innovation as well as emerging fields of patenting activities - providing a broad statistical basis for competitor analysis and decision-making efforts.

Process attributes in bio-ontologies

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Andrade André Q

2012-08-01

Full Text Available Abstract Background Biomedical processes can provide essential information about the (mal- functioning of an organism and are thus frequently represented in biomedical terminologies and ontologies, including the GO Biological Process branch. These processes often need to be described and categorised in terms of their attributes, such as rates or regularities. The adequate representation of such process attributes has been a contentious issue in bio-ontologies recently; and domain ontologies have correspondingly developed ad hoc workarounds that compromise interoperability and logical consistency. Results We present a design pattern for the representation of process attributes that is compatible with upper ontology frameworks such as BFO and BioTop. Our solution rests on two key tenets: firstly, that many of the sorts of process attributes which are biomedically interesting can be characterised by the ways that repeated parts of such processes constitute, in combination, an overall process; secondly, that entities for which a full logical definition can be assigned do not need to be treated as primitive within a formal ontology framework. We apply this approach to the challenge of modelling and automatically classifying examples of normal and abnormal rates and patterns of heart beating processes, and discuss the expressivity required in the underlying ontology representation language. We provide full definitions for process attributes at increasing levels of domain complexity. Conclusions We show that a logical definition of process attributes is feasible, though limited by the expressivity of DL languages so that the creation of primitives is still necessary. This finding may endorse current formal upper-ontology frameworks as a way of ensuring consistency, interoperability and clarity.

Ontology Mapping Neural Network: An Approach to Learning and Inferring Correspondences among Ontologies

Science.gov (United States)

Peng, Yefei

2010-01-01

An ontology mapping neural network (OMNN) is proposed in order to learn and infer correspondences among ontologies. It extends the Identical Elements Neural Network (IENN)'s ability to represent and map complex relationships. The learning dynamics of simultaneous (interlaced) training of similar tasks interact at the shared connections of the…

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.

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.)

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

Modelling the cybersecurity environment using morphological ontology design engineering

CSIR Research Space (South Africa)

Jansen van Vuuren, JC

2015-03-01

Full Text Available ). This methodology is based on the combination of three different research methods, i.e. design science, general morphological analysis, and ontology based representation. General morphological analysis offers a solution for extracting meaningful information from...

Scientific Digital Libraries, Interoperability, and Ontologies

Science.gov (United States)

Hughes, J. Steven; Crichton, Daniel J.; Mattmann, Chris A.

2009-01-01

Scientific digital libraries serve complex and evolving research communities. Justifications for the development of scientific digital libraries include the desire to preserve science data and the promises of information interconnectedness, correlative science, and system interoperability. Shared ontologies are fundamental to fulfilling these promises. We present a tool framework, some informal principles, and several case studies where shared ontologies are used to guide the implementation of scientific digital libraries. The tool framework, based on an ontology modeling tool, was configured to develop, manage, and keep shared ontologies relevant within changing domains and to promote the interoperability, interconnectedness, and correlation desired by scientists.

Proceedings of a Sickle Cell Disease Ontology workshop — Towards the first comprehensive ontology for Sickle Cell Disease

Directory of Open Access Journals (Sweden)

Nicola Mulder

2016-06-01

The SCD community and H3ABioNet members joined forces at a recent SCD Ontology workshop to develop an ontology covering aspects of SCD under the classes: phenotype, diagnostics, therapeutics, quality of life, disease modifiers and disease stage. The aim of the workshop was for participants to contribute their expertise to development of the structure and contents of the SCD ontology. Here we describe the proceedings of the Sickle Cell Disease Ontology Workshop held in Cape Town South Africa in February 2016 and its outcomes. The objective of the workshop was to bring together experts in SCD from around the world to contribute their expertise to the development of various aspects of the SCD ontology.

Audit Validation Using Ontologies

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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.

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 ...

Análisis de terminologías de salud para su utilización como ontologías computacionales en los sistemas de información clínicos Analysis of health terminologies for use as ontologies in healthcare information systems

Directory of Open Access Journals (Sweden)

Maria Teresa Romá-Ferri

2008-10-01

limitations imposed by standardized terms. The objective of this study was to establish the extent to which terminologies could be used for the design of ontologies, which could be serve as an aid to resolve problems such as semantic interoperability and knowledge reusability in healthcare information systems. Methods: To determine the extent to which terminologies could be used as ontologies, six of the most important terminologies in clinical, epidemiologic, documentation and administrative-economic contexts were analyzed. The following characteristics were verified: conceptual coverage, hierarchical structure, conceptual granularity of the categories, conceptual relations, and the language used for conceptual representation. Results: MeSH, DeCS and UMLS ontologies were considered lightweight. The main differences among these ontologies concern conceptual specification, the types of relation and the restrictions among the associated concepts. SNOMED and GALEN ontologies have declaratory formalism, based on logical descriptions. These ontologies include explicit qualities and show greater restrictions among associated concepts and rule combinations and were consequently considered as heavyweight. Conclusions: Analysis of the declared representation of the terminologies shows the extent to which they could be reused as ontologies. Their degree of usability depends on whether the aim is for healthcare information systems to solve problems of semantic interoperability (lightweight ontologies or to reuse the systems' knowledge as an aid to decision making (heavyweight ontologies and for non-structured information retrieval, extraction, and classification.

A priorean approach to time ontologies

DEFF Research Database (Denmark)

Øhrstrøm, Peter; Schärfe, Henrik

2004-01-01

Any non-trivial top-level ontology should take temporal notions into account. The details of how this should be done, however, are frequently debated. In this paper it is argued that "the four grades of tense-logical involvement" suggested by A.N. Prior form a useful framework for discussing how...... various temporal notions are related in a top-level ontology. Furthermore, a number of modern ontologies are analysed with respect to their incorporation of temporal notions. It is argued that all of them correspond to Prior's first and second grade, and that none of them reflect the views which Prior......'s third and fourth grade represent. Finally, the paper deals with Prior's ideas on a tensed ontology and it is argued that a logic based on the third grade and will be useful in the further development of tensed ontology....

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....

BiOSS: A system for biomedical ontology selection.

Science.gov (United States)

Martínez-Romero, Marcos; Vázquez-Naya, José M; Pereira, Javier; Pazos, Alejandro

2014-04-01

In biomedical informatics, ontologies are considered a key technology for annotating, retrieving and sharing the huge volume of publicly available data. Due to the increasing amount, complexity and variety of existing biomedical ontologies, choosing the ones to be used in a semantic annotation problem or to design a specific application is a difficult task. As a consequence, the design of approaches and tools addressed to facilitate the selection of biomedical ontologies is becoming a priority. In this paper we present BiOSS, a novel system for the selection of biomedical ontologies. BiOSS evaluates the adequacy of an ontology to a given domain according to three different criteria: (1) the extent to which the ontology covers the domain; (2) the semantic richness of the ontology in the domain; (3) the popularity of the ontology in the biomedical community. BiOSS has been applied to 5 representative problems of ontology selection. It also has been compared to existing methods and tools. Results are promising and show the usefulness of BiOSS to solve real-world ontology selection problems. BiOSS is openly available both as a web tool and a web service. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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.

ONSET: Automated foundational ontology selection and explanation

CSIR Research Space (South Africa)

Khan, Z

2012-10-01

Full Text Available It has been shown that using a foundational ontology for domain ontology development is beneficial in theory and practice. However, developers have difficulty with choosing the appropriate foundational ontology, and why. In order to solve...

CONCEPTION OF ONTOLOGY-BASED SECTOR EDUCATIONAL SPACE

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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.

History Matters: Incremental Ontology Reasoning Using Modules

Science.gov (United States)

Cuenca Grau, Bernardo; Halaschek-Wiener, Christian; Kazakov, Yevgeny

The development of ontologies involves continuous but relatively small modifications. Existing ontology reasoners, however, do not take advantage of the similarities between different versions of an ontology. In this paper, we propose a technique for incremental reasoning—that is, reasoning that reuses information obtained from previous versions of an ontology—based on the notion of a module. Our technique does not depend on a particular reasoning calculus and thus can be used in combination with any reasoner. We have applied our results to incremental classification of OWL DL ontologies and found significant improvement over regular classification time on a set of real-world ontologies.

A multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors for functional gene analysis.

Science.gov (United States)

Weber, Kristoffer; Bartsch, Udo; Stocking, Carol; Fehse, Boris

2008-04-01

Functional gene analysis requires the possibility of overexpression, as well as downregulation of one, or ideally several, potentially interacting genes. Lentiviral vectors are well suited for this purpose as they ensure stable expression of complementary DNAs (cDNAs), as well as short-hairpin RNAs (shRNAs), and can efficiently transduce a wide spectrum of cell targets when packaged within the coat proteins of other viruses. Here we introduce a multicolor panel of novel lentiviral "gene ontology" (LeGO) vectors designed according to the "building blocks" principle. Using a wide spectrum of different fluorescent markers, including drug-selectable enhanced green fluorescent protein (eGFP)- and dTomato-blasticidin-S resistance fusion proteins, LeGO vectors allow simultaneous analysis of multiple genes and shRNAs of interest within single, easily identifiable cells. Furthermore, each functional module is flanked by unique cloning sites, ensuring flexibility and individual optimization. The efficacy of these vectors for analyzing multiple genes in a single cell was demonstrated in several different cell types, including hematopoietic, endothelial, and neural stem and progenitor cells, as well as hepatocytes. LeGO vectors thus represent a valuable tool for investigating gene networks using conditional ectopic expression and knock-down approaches simultaneously.

Ontology-based Brucella vaccine literature indexing and systematic analysis of gene-vaccine association network

Science.gov (United States)

2011-01-01

Background Vaccine literature indexing is poorly performed in PubMed due to limited hierarchy of Medical Subject Headings (MeSH) annotation in the vaccine field. Vaccine Ontology (VO) is a community-based biomedical ontology that represents various vaccines and their relations. SciMiner is an in-house literature mining system that supports literature indexing and gene name tagging. We hypothesize that application of VO in SciMiner will aid vaccine literature indexing and mining of vaccine-gene interaction networks. As a test case, we have examined vaccines for Brucella, the causative agent of brucellosis in humans and animals. Results The VO-based SciMiner (VO-SciMiner) was developed to incorporate a total of 67 Brucella vaccine terms. A set of rules for term expansion of VO terms were learned from training data, consisting of 90 biomedical articles related to Brucella vaccine terms. VO-SciMiner demonstrated high recall (91%) and precision (99%) from testing a separate set of 100 manually selected biomedical articles. VO-SciMiner indexing exhibited superior performance in retrieving Brucella vaccine-related papers over that obtained with MeSH-based PubMed literature search. For example, a VO-SciMiner search of "live attenuated Brucella vaccine" returned 922 hits as of April 20, 2011, while a PubMed search of the same query resulted in only 74 hits. Using the abstracts of 14,947 Brucella-related papers, VO-SciMiner identified 140 Brucella genes associated with Brucella vaccines. These genes included known protective antigens, virulence factors, and genes closely related to Brucella vaccines. These VO-interacting Brucella genes were significantly over-represented in biological functional categories, including metabolite transport and metabolism, replication and repair, cell wall biogenesis, intracellular trafficking and secretion, posttranslational modification, and chaperones. Furthermore, a comprehensive interaction network of Brucella vaccines and genes were

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.

A Mobile Army of Ontologies

DEFF Research Database (Denmark)

Juul, Jesper

2015-01-01

Presentation at the Ludo-ontologies panel. Do we need ludo-ontologies, and what are they? In this event several scholars of games and videogames discuss these questions from a variety of perspectives. What different game and videogame ontologies exist and could exist, and why they are important...... for game and videogame research? The round table is designed to promote ludo-ontological dialogue in order to make these questions visible and debated. A series of short presentations (approximately 10 minutes each) will be followed by an intense debate through freeform dialogue. After the industrial...... commercialization of games and videogames their study has shifted between approaches focused on players (ludic processes) and artifacts (ludic objects). Some attempts to analyze the relationship between the process and the object have occasionally been done in terms of ‘ontology’ (Zagal 2005; Leino 2010; Gualeni...

Ontology Versioning and Change Detection on the Web

NARCIS (Netherlands)

Klein, Michel; Fensel, Dieter; Kiryakov, Atanas; Ognyanov, Damyan

2002-01-01

To effectively use ontologies on the Web, it is essential that changes in ontologies are managed well. This paper analyzes the topic of ontology versioning in the context of the Web by looking at the characteristics of the version relation between ontologies and at the identification of online

The logic of surveillance guidelines: an analysis of vaccine adverse event reports from an ontological perspective.

Directory of Open Access Journals (Sweden)

Mélanie Courtot

Full Text Available BACKGROUND: When increased rates of adverse events following immunization are detected, regulatory action can be taken by public health agencies. However to be interpreted reports of adverse events must be encoded in a consistent way. Regulatory agencies rely on guidelines to help determine the diagnosis of the adverse events. Manual application of these guidelines is expensive, time consuming, and open to logical errors. Representing these guidelines in a format amenable to automated processing can make this process more efficient. METHODS AND FINDINGS: Using the Brighton anaphylaxis case definition, we show that existing clinical guidelines used as standards in pharmacovigilance can be logically encoded using a formal representation such as the Adverse Event Reporting Ontology we developed. We validated the classification of vaccine adverse event reports using the ontology against existing rule-based systems and a manually curated subset of the Vaccine Adverse Event Reporting System. However, we encountered a number of critical issues in the formulation and application of the clinical guidelines. We report these issues and the steps being taken to address them in current surveillance systems, and in the terminological standards in use. CONCLUSIONS: By standardizing and improving the reporting process, we were able to automate diagnosis confirmation. By allowing medical experts to prioritize reports such a system can accelerate the identification of adverse reactions to vaccines and the response of regulatory agencies. This approach of combining ontology and semantic technologies can be used to improve other areas of vaccine adverse event reports analysis and should inform both the design of clinical guidelines and how they are used in the future. AVAILABILITY: Sufficient material to reproduce our results is available, including documentation, ontology, code and datasets, at http://purl.obolibrary.org/obo/aero.

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.

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.

Self-organizing ontology of biochemically relevant small molecules.

Science.gov (United States)

Chepelev, Leonid L; Hastings, Janna; Ennis, Marcus; Steinbeck, Christoph; Dumontier, Michel

2012-01-06

The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest. To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development. We conclude that the proposed methodology can ease the burden of chemical data annotators and

Self-organizing ontology of biochemically relevant small molecules

Science.gov (United States)

2012-01-01

Background The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI) are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest. Results To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development. Conclusions We conclude that the proposed methodology can ease the burden of

Self-organizing ontology of biochemically relevant small molecules

Directory of Open Access Journals (Sweden)

Chepelev Leonid L

2012-01-01

Full Text Available Abstract Background The advent of high-throughput experimentation in biochemistry has led to the generation of vast amounts of chemical data, necessitating the development of novel analysis, characterization, and cataloguing techniques and tools. Recently, a movement to publically release such data has advanced biochemical structure-activity relationship research, while providing new challenges, the biggest being the curation, annotation, and classification of this information to facilitate useful biochemical pattern analysis. Unfortunately, the human resources currently employed by the organizations supporting these efforts (e.g. ChEBI are expanding linearly, while new useful scientific information is being released in a seemingly exponential fashion. Compounding this, currently existing chemical classification and annotation systems are not amenable to automated classification, formal and transparent chemical class definition axiomatization, facile class redefinition, or novel class integration, thus further limiting chemical ontology growth by necessitating human involvement in curation. Clearly, there is a need for the automation of this process, especially for novel chemical entities of biological interest. Results To address this, we present a formal framework based on Semantic Web technologies for the automatic design of chemical ontology which can be used for automated classification of novel entities. We demonstrate the automatic self-assembly of a structure-based chemical ontology based on 60 MeSH and 40 ChEBI chemical classes. This ontology is then used to classify 200 compounds with an accuracy of 92.7%. We extend these structure-based classes with molecular feature information and demonstrate the utility of our framework for classification of functionally relevant chemicals. Finally, we discuss an iterative approach that we envision for future biochemical ontology development. Conclusions We conclude that the proposed methodology

Automatic Tamil lyric generation based on ontological interpretation ...

Indian Academy of Sciences (India)

This system proposes an -gram based approach to automatic Tamil lyric generation, by the ontological semantic interpretation of the input scene. The approach is based on identifying the semantics conveyed in the scenario, thereby making the system understand the situation and generate lyrics accordingly. The heart of ...

Ontological realism: A methodology for coordinated evolution of scientific ontologies.

Science.gov (United States)

Smith, Barry; Ceusters, Werner

2010-11-15

Since 2002 we have been testing and refining a methodology for ontology development that is now being used by multiple groups of researchers in different life science domains. Gary Merrill, in a recent paper in this journal, describes some of the reasons why this methodology has been found attractive by researchers in the biological and biomedical sciences. At the same time he assails the methodology on philosophical grounds, focusing specifically on our recommendation that ontologies developed for scientific purposes should be constructed in such a way that their terms are seen as referring to what we call universals or types in reality. As we show, Merrill's critique is of little relevance to the success of our realist project, since it not only reveals no actual errors in our work but also criticizes views on universals that we do not in fact hold. However, it nonetheless provides us with a valuable opportunity to clarify the realist methodology, and to show how some of its principles are being applied, especially within the framework of the OBO (Open Biomedical Ontologies) Foundry initiative.

Terminology representation guidelines for biomedical ontologies in the semantic web notations.

Science.gov (United States)

Tao, Cui; Pathak, Jyotishman; Solbrig, Harold R; Wei, Wei-Qi; Chute, Christopher G

2013-02-01

Terminologies and ontologies are increasingly prevalent in healthcare and biomedicine. However they suffer from inconsistent renderings, distribution formats, and syntax that make applications through common terminologies services challenging. To address the problem, one could posit a shared representation syntax, associated schema, and tags. We identified a set of commonly-used elements in biomedical ontologies and terminologies based on our experience with the Common Terminology Services 2 (CTS2) Specification as well as the Lexical Grid (LexGrid) project. We propose guidelines for precisely such a shared terminology model, and recommend tags assembled from SKOS, OWL, Dublin Core, RDF Schema, and DCMI meta-terms. We divide these guidelines into lexical information (e.g. synonyms, and definitions) and semantic information (e.g. hierarchies). The latter we distinguish for use by informal terminologies vs. formal ontologies. We then evaluate the guidelines with a spectrum of widely used terminologies and ontologies to examine how the lexical guidelines are implemented, and whether our proposed guidelines would enhance interoperability. Copyright © 2012 Elsevier Inc. All rights reserved.

The foundational ontology library ROMULUS

CSIR Research Space (South Africa)

Khan, ZC

2013-09-01

Full Text Available . We present here a basic step in that direction with the Repository of Ontologies for MULtiple USes, ROMULUS, which is the first online library of machine-processable, modularised, aligned, and logic-based merged foundational ontologies. In addition...

Tracking Changes during Ontology Evolution

NARCIS (Netherlands)

Noy, Natalya F.; Kunnatur, Sandhya; Klein, Michel; Musen, Mark A.

2004-01-01

As ontology development becomes a collaborative process, developers face the problem of maintaining versions of ontologies akin to maintaining versions of software code or versions of documents in large projects. Traditional versioning systems enable users to compare versions, examine changes, and

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.

Annotation of phenotypic diversity: decoupling data curation and ontology curation using Phenex.

Science.gov (United States)

Balhoff, James P; Dahdul, Wasila M; Dececchi, T Alexander; Lapp, Hilmar; Mabee, Paula M; Vision, Todd J

2014-01-01

Phenex (http://phenex.phenoscape.org/) is a desktop application for semantically annotating the phenotypic character matrix datasets common in evolutionary biology. Since its initial publication, we have added new features that address several major bottlenecks in the efficiency of the phenotype curation process: allowing curators during the data curation phase to provisionally request terms that are not yet available from a relevant ontology; supporting quality control against annotation guidelines to reduce later manual review and revision; and enabling the sharing of files for collaboration among curators. We decoupled data annotation from ontology development by creating an Ontology Request Broker (ORB) within Phenex. Curators can use the ORB to request a provisional term for use in data annotation; the provisional term can be automatically replaced with a permanent identifier once the term is added to an ontology. We added a set of annotation consistency checks to prevent common curation errors, reducing the need for later correction. We facilitated collaborative editing by improving the reliability of Phenex when used with online folder sharing services, via file change monitoring and continual autosave. With the addition of these new features, and in particular the Ontology Request Broker, Phenex users have been able to focus more effectively on data annotation. Phenoscape curators using Phenex have reported a smoother annotation workflow, with much reduced interruptions from ontology maintenance and file management issues.

Complex overlapping concepts: An effective auditing methodology for families of similarly structured BioPortal ontologies.

Science.gov (United States)

Zheng, Ling; Chen, Yan; Elhanan, Gai; Perl, Yehoshua; Geller, James; Ochs, Christopher

2018-05-28

In previous research, we have demonstrated for a number of ontologies that structurally complex concepts (for different definitions of "complex") in an ontology are more likely to exhibit errors than other concepts. Thus, such complex concepts often become fertile ground for quality assurance (QA) in ontologies. They should be audited first. One example of complex concepts is given by "overlapping concepts" (to be defined below.) Historically, a different auditing methodology had to be developed for every single ontology. For better scalability and efficiency, it is desirable to identify family-wide QA methodologies. Each such methodology would be applicable to a whole family of similar ontologies. In past research, we had divided the 685 ontologies of BioPortal into families of structurally similar ontologies. We showed for four ontologies of the same large family in BioPortal that "overlapping concepts" are indeed statistically significantly more likely to exhibit errors. In order to make an authoritative statement concerning the success of "overlapping concepts" as a methodology for a whole family of similar ontologies (or of large subhierarchies of ontologies), it is necessary to show that "overlapping concepts" have a higher likelihood of errors for six out of six ontologies of the family. In this paper, we are demonstrating for two more ontologies that "overlapping concepts" can successfully predict groups of concepts with a higher error rate than concepts from a control group. The fifth ontology is the Neoplasm subhierarchy of the National Cancer Institute thesaurus (NCIt). The sixth ontology is the Infectious Disease subhierarchy of SNOMED CT. We demonstrate quality assurance results for both of them. Furthermore, in this paper we observe two novel, important, and useful phenomena during quality assurance of "overlapping concepts." First, an erroneous "overlapping concept" can help with discovering other erroneous "non-overlapping concepts" in its vicinity

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.

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,…

GFVO: the Genomic Feature and Variation Ontology

KAUST Repository

Baran, Joachim; Durgahee, Bibi Sehnaaz Begum; Eilbeck, Karen; Antezana, Erick; Hoehndorf, Robert; Dumontier, Michel

2015-01-01

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.

Using an ontology pattern stack to engineer a core ontology of Accounting Information Systems

NARCIS (Netherlands)

Blums, Ivar; Weigand, Hans

Although the field of Accounting Information Systems (AIS) has a long tradition, there is still a lack of a widely adopted conceptualization. In this paper, The UFO ontology patterns are regarded for application by analogy and extension in the engineering of a core ontology for AIS. The new IASB

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).

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.

Versioning System for Distributed Ontology Development

Science.gov (United States)

2016-03-15

Framework for Grid Computing and Semantic Web Services,” Trust Management, Springer Berlin Heidelberg (2004), pp. 16−26. [TIME] W3C, “Time Ontology in...Distributed Ontology Development S.K. Damodaran 15 March 2016 This material is based on work supported by the Assistant Secretary of Defense for...Distributed Ontology Development S.K. Damodaran Formerly Group 59 15 March 2016 Massachusetts Institute of Technology Lincoln Laboratory

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

A PRACTICAL ONTOLOGY FOR THE LARGE-SCALE MODELING OF SCHOLARLY ARTIFACTS AND THEIR USAGE

Energy Technology Data Exchange (ETDEWEB)

RODRIGUEZ, MARKO A. [Los Alamos National Laboratory; BOLLEN, JOHAN [Los Alamos National Laboratory; VAN DE SOMPEL, HERBERT [Los Alamos National Laboratory

2007-01-30

The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real world instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. They present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.

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

Improving software product line using an ontological approach

Indian Academy of Sciences (India)

An ontological based approach is proposed following first-order logic (FOL) rules to identify defects namely dead features and false optional features. The classification of cases forthese defects in FMs that represent variability of SPL is defined. The presented approach has been explained with the help of an FM derived ...

An ontology-based intrusion patterns classification system | Shonubi ...

African Journals Online (AJOL)

Studies have shown that computer intrusions have been on the increase in recent times. Many techniques and patterns are being used by intruders to gain access to data on host computer networks. In this work, intrusion patterns were identified and classified and inherent knowledge were represented using an ontology of ...

FOCIH: Form-Based Ontology Creation and Information Harvesting

Science.gov (United States)

Tao, Cui; Embley, David W.; Liddle, Stephen W.

Creating an ontology and populating it with data are both labor-intensive tasks requiring a high degree of expertise. Thus, scaling ontology creation and population to the size of the web in an effort to create a web of data—which some see as Web 3.0—is prohibitive. Can we find ways to streamline these tasks and lower the barrier enough to enable Web 3.0? Toward this end we offer a form-based approach to ontology creation that provides a way to create Web 3.0 ontologies without the need for specialized training. And we offer a way to semi-automatically harvest data from the current web of pages for a Web 3.0 ontology. In addition to harvesting information with respect to an ontology, the approach also annotates web pages and links facts in web pages to ontological concepts, resulting in a web of data superimposed over the web of pages. Experience with our prototype system shows that mappings between conceptual-model-based ontologies and forms are sufficient for creating the kind of ontologies needed for Web 3.0, and experiments with our prototype system show that automatic harvesting, automatic annotation, and automatic superimposition of a web of data over a web of pages work well.

Ontology Based Model Transformation Infrastructure

NARCIS (Netherlands)

Göknil, Arda; Topaloglu, N.Y.

2005-01-01

Using MDA in ontology development has been investigated in several works recently. The mappings and transformations between the UML constructs and the OWL elements to develop ontologies are the main concern of these research projects. We propose another approach in order to achieve the collaboration

BioPortal: enhanced functionality via new Web services from the National Center for Biomedical Ontology to access and use ontologies in software applications.

Science.gov (United States)

Whetzel, Patricia L; Noy, Natalya F; Shah, Nigam H; Alexander, Paul R; Nyulas, Csongor; Tudorache, Tania; Musen, Mark A

2011-07-01

The National Center for Biomedical Ontology (NCBO) is one of the National Centers for Biomedical Computing funded under the NIH Roadmap Initiative. Contributing to the national computing infrastructure, NCBO has developed BioPortal, a web portal that provides access to a library of biomedical ontologies and terminologies (http://bioportal.bioontology.org) via the NCBO Web services. BioPortal enables community participation in the evaluation and evolution of ontology content by providing features to add mappings between terms, to add comments linked to specific ontology terms and to provide ontology reviews. The NCBO Web services (http://www.bioontology.org/wiki/index.php/NCBO_REST_services) enable this functionality and provide a uniform mechanism to access ontologies from a variety of knowledge representation formats, such as Web Ontology Language (OWL) and Open Biological and Biomedical Ontologies (OBO) format. The Web services provide multi-layered access to the ontology content, from getting all terms in an ontology to retrieving metadata about a term. Users can easily incorporate the NCBO Web services into software applications to generate semantically aware applications and to facilitate structured data collection.

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

The current landscape of pitfalls in Ontologies

CSIR Research Space (South Africa)

Keet, CM

2013-09-01

Full Text Available 2Ontology Engineering Group, Departamento de Inteligencia Artificial, Universidad Polite´cnica de Madrid, Madrid, Spain keet@ukzn.ac.za, {mcsuarez,mpoveda}@fi.upm.es Keywords: Ontology Development : Ontology Quality : Pitfall Abstract: A growing... in Ontologies C. Maria Keet1, Mari Carmen Sua´rez-Figueroa2 and Marı´a Poveda-Villalo´n2 1School of Mathematics, Statistics, and Computer Science, University of KwaZulu-Natal, and UKZN/CSIR-Meraka Centre for Artificial Intelligence Research, Durban, South Africa...

Toward semantic interoperability with linked foundational ontologies in ROMULUS

CSIR Research Space (South Africa)

Khan, ZC

2013-06-01

Full Text Available A purpose of a foundational ontology is to solve interoperability issues among ontologies. Many foundational ontologies have been developed, reintroducing the ontology interoperability problem. We address this with the new online foundational...

A Simulation Model Articulation of the REA Ontology

Science.gov (United States)

Laurier, Wim; Poels, Geert

This paper demonstrates how the REA enterprise ontology can be used to construct simulation models for business processes, value chains and collaboration spaces in supply chains. These models support various high-level and operational management simulation applications, e.g. the analysis of enterprise sustainability and day-to-day planning. First, the basic constructs of the REA ontology and the ExSpect modelling language for simulation are introduced. Second, collaboration space, value chain and business process models and their conceptual dependencies are shown, using the ExSpect language. Third, an exhibit demonstrates the use of value chain models in predicting the financial performance of an enterprise.

ONTOLOGY-DRIVEN TOOL FOR UTILIZING PROGRAMMING STYLES

Directory of Open Access Journals (Sweden)

Nikolay Sidorov

2017-07-01

Full Text Available Activities of a programmer will be more effective and the software will be more understandable when within the process of software development, programming styles (standards are used, providing clarity of software texts. Purpose: In this research, we present the tool for the realization of new ontology-based methodology automated reasoning techniques for utilizing programming styles. In particular, we focus on representing programming styles in the form of formal ontologies, and study how description logic reasoner can assist programmers in utilizing programming standards. Our research hypothesis is as follows: ontological representation of programming styles can provide additional benefits over existing approaches in utilizing programmer of programming standards. Our research goal is to develop a tool to support the ontology-based utilizing programming styles. Methods: ontological representation of programming styles; object-oriented programming; ontology-driven utilizing of programming styles. Results: the architecture was obtained and the tool was developed in the Java language, which provide tool support of ontology-driven programming styles application method. On the example of naming of the Java programming language standard, features of implementation and application of the tool are provided. Discussion: application of programming styles in coding of program; lack of automated tools for the processes of programming standards application; tool based on new method of ontology-driven application of programming styles; an example of the implementation of tool architecture for naming rules of the Java language standard.

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...

Product line based ontology development for semantic web service

DEFF Research Database (Denmark)

Zhang, Weishan; Kunz, Thomas

2006-01-01

Ontology is recognized as a key technology for the success of the Semantic Web. Building reusable and evolve-able ontologies in order to cope with ontology evolution and requirement changes is increasingly important. But the existing methodologies and tools fail to support effective ontology reuse...... will lead to the initial implementation of the meta-onotologies using design by reuse and with the objective of design for reuse. After that step new ontologies could be generated by reusing these meta-ontologies. We demonstrate our approach with a Semantic Web Service application to show how to build...

Learning Ontology from Object-Relational Database

Directory of Open Access Journals (Sweden)

Kaulins Andrejs

2015-12-01

Full Text Available This article describes a method of transformation of object-relational model into ontology. The offered method uses learning rules for such complex data types as object tables and collections – arrays of a variable size, as well as nested tables. Object types and their transformation into ontologies are insufficiently considered in scientific literature. This fact served as motivation for the authors to investigate this issue and to write the article on this matter. In the beginning, we acquaint the reader with complex data types and object-oriented databases. Then we describe an algorithm of transformation of complex data types into ontologies. At the end of the article, some examples of ontologies described in the OWL language are given.

A-DaGO-Fun: an adaptable Gene Ontology semantic similarity-based functional analysis tool.

Science.gov (United States)

Mazandu, Gaston K; Chimusa, Emile R; Mbiyavanga, Mamana; Mulder, Nicola J

2016-02-01

Gene Ontology (GO) semantic similarity measures are being used for biological knowledge discovery based on GO annotations by integrating biological information contained in the GO structure into data analyses. To empower users to quickly compute, manipulate and explore these measures, we introduce A-DaGO-Fun (ADaptable Gene Ontology semantic similarity-based Functional analysis). It is a portable software package integrating all known GO information content-based semantic similarity measures and relevant biological applications associated with these measures. A-DaGO-Fun has the advantage not only of handling datasets from the current high-throughput genome-wide applications, but also allowing users to choose the most relevant semantic similarity approach for their biological applications and to adapt a given module to their needs. A-DaGO-Fun is freely available to the research community at http://web.cbio.uct.ac.za/ITGOM/adagofun. It is implemented in Linux using Python under free software (GNU General Public Licence). gmazandu@cbio.uct.ac.za or Nicola.Mulder@uct.ac.za Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Semantic Similarity between Web Documents Using Ontology

Science.gov (United States)

Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

2018-06-01

The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

Semantic Similarity between Web Documents Using Ontology

Science.gov (United States)

Chahal, Poonam; Singh Tomer, Manjeet; Kumar, Suresh

2018-03-01

The World Wide Web is the source of information available in the structure of interlinked web pages. However, the procedure of extracting significant information with the assistance of search engine is incredibly critical. This is for the reason that web information is written mainly by using natural language, and further available to individual human. Several efforts have been made in semantic similarity computation between documents using words, concepts and concepts relationship but still the outcome available are not as per the user requirements. This paper proposes a novel technique for computation of semantic similarity between documents that not only takes concepts available in documents but also relationships that are available between the concepts. In our approach documents are being processed by making ontology of the documents using base ontology and a dictionary containing concepts records. Each such record is made up of the probable words which represents a given concept. Finally, document ontology's are compared to find their semantic similarity by taking the relationships among concepts. Relevant concepts and relations between the concepts have been explored by capturing author and user intention. The proposed semantic analysis technique provides improved results as compared to the existing techniques.

Comparing Relational and Ontological Triple Stores in Healthcare Domain

Directory of Open Access Journals (Sweden)

Ozgu Can

2017-01-01

Full Text Available Today’s technological improvements have made ubiquitous healthcare systems that converge into smart healthcare applications in order to solve patients’ problems, to communicate effectively with patients, and to improve healthcare service quality. The first step of building a smart healthcare information system is representing the healthcare data as connected, reachable, and sharable. In order to achieve this representation, ontologies are used to describe the healthcare data. Combining ontological healthcare data with the used and obtained data can be maintained by storing the entire health domain data inside big data stores that support both relational and graph-based ontological data. There are several big data stores and different types of big data sets in the healthcare domain. The goal of this paper is to determine the most applicable ontology data store for storing the big healthcare data. For this purpose, AllegroGraph and Oracle 12c data stores are compared based on their infrastructural capacity, loading time, and query response times. Hence, healthcare ontologies (GENE Ontology, Gene Expression Ontology (GEXO, Regulation of Transcription Ontology (RETO, Regulation of Gene Expression Ontology (REXO are used to measure the ontology loading time. Thereafter, various queries are constructed and executed for GENE ontology in order to measure the capacity and query response times for the performance comparison between AllegroGraph and Oracle 12c triple stores.

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...

A histological ontology of the human cardiovascular system.

Science.gov (United States)

Mazo, Claudia; Salazar, Liliana; Corcho, Oscar; Trujillo, Maria; Alegre, Enrique

2017-10-02

In this paper, we describe a histological ontology of the human cardiovascular system developed in collaboration among histology experts and computer scientists. The histological ontology is developed following an existing methodology using Conceptual Models (CMs) and validated using OOPS!, expert evaluation with CMs, and how accurately the ontology can answer the Competency Questions (CQ). It is publicly available at http://bioportal.bioontology.org/ontologies/HO and https://w3id.org/def/System . The histological ontology is developed to support complex tasks, such as supporting teaching activities, medical practices, and bio-medical research or having natural language interactions.

An Iterative and Incremental Approach for E-Learning Ontology Engineering

Directory of Open Access Journals (Sweden)

Sudath Rohitha Heiyanthuduwage

2009-03-01

Full Text Available Abstract - There is a boost in the interest on ontology with the developments in Semantic Web technologies. Ontologies play a vital role in semantic web. Even though there is lot of work done on ontology, still a standard framework for ontology engineering has not been defined. Even though current ontology engineering methodologies are available they need improvements. The effort of our work is to integrate various methods, techniques, tools and etc to different stages of proposed ontology engineering life cycle to create a comprehensive framework for ontology engineering. Current methodologies discuss ontology engineering stages and collaborative environments with user collaboration. However, discussion on increasing effectiveness and correct inference has been given less attention. More over, these methodologies provide little discussion on usability of domain ontologies. We consider these aspects as more important in our work. Also, ontology engineering has been done for various domains and for various purposes. Our effort is to propose an iterative and incremental approach for ontology engineering especially for e-learning domain with the intention of achieving a higher usability and effectiveness of e-learning systems. This paper introduces different aspects of the proposed ontology engineering framework and evaluation of it.

Biomedicine: an ontological dissection.

Science.gov (United States)

Baronov, David

2008-01-01

Though ubiquitous across the medical social sciences literature, the term "biomedicine" as an analytical concept remains remarkably slippery. It is argued here that this imprecision is due in part to the fact that biomedicine is comprised of three interrelated ontological spheres, each of which frames biomedicine as a distinct subject of investigation. This suggests that, depending upon one's ontological commitment, the meaning of biomedicine will shift. From an empirical perspective, biomedicine takes on the appearance of a scientific enterprise and is defined as a derivative category of Western science more generally. From an interpretive perspective, biomedicine represents a symbolic-cultural expression whose adherence to the principles of scientific objectivity conceals an ideological agenda. From a conceptual perspective, biomedicine represents an expression of social power that reflects structures of power and privilege within capitalist society. No one perspective exists in isolation and so the image of biomedicine from any one presents an incomplete understanding. It is the mutually-conditioning interrelations between these ontological spheres that account for biomedicine's ongoing development. Thus, the ontological dissection of biomedicine that follows, with particular emphasis on the period of its formal crystallization in the latter nineteenth and early twentieth century, is intended to deepen our understanding of biomedicine as an analytical concept across the medical social sciences literature.

Construction of ontology augmented networks for protein complex prediction.

Science.gov (United States)

Zhang, Yijia; Lin, Hongfei; Yang, Zhihao; Wang, Jian

2013-01-01

Protein complexes are of great importance in understanding the principles of cellular organization and function. The increase in available protein-protein interaction data, gene ontology and other resources make it possible to develop computational methods for protein complex prediction. Most existing methods focus mainly on the topological structure of protein-protein interaction networks, and largely ignore the gene ontology annotation information. In this article, we constructed ontology augmented networks with protein-protein interaction data and gene ontology, which effectively unified the topological structure of protein-protein interaction networks and the similarity of gene ontology annotations into unified distance measures. After constructing ontology augmented networks, a novel method (clustering based on ontology augmented networks) was proposed to predict protein complexes, which was capable of taking into account the topological structure of the protein-protein interaction network, as well as the similarity of gene ontology annotations. Our method was applied to two different yeast protein-protein interaction datasets and predicted many well-known complexes. The experimental results showed that (i) ontology augmented networks and the unified distance measure can effectively combine the structure closeness and gene ontology annotation similarity; (ii) our method is valuable in predicting protein complexes and has higher F1 and accuracy compared to other competing methods.

ONTOLOGY IN PHARMACY

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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.

Finding the best visualization of an ontology

DEFF Research Database (Denmark)

Fabritius, Christina; Madsen, Nadia; Clausen, Jens

2006-01-01

An ontology is a classification model for a given domain.In information retrieval ontologies are used to perform broad searches.An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

Finding the best visualization of an ontology

DEFF Research Database (Denmark)

Fabritius, Christina Valentin; Madsen, Nadia Lyngaa; Clausen, Jens

2004-01-01

An ontology is a classification model for a given domain. In information retrieval ontologies are used to perform broad searches. An ontology can be visualized as nodes and edges. Each node represents an element and each edge a relation between a parent and a child element. Working with an ontology....... One method uses a discrete location model to create an initial solution and we propose heuristic methods to further improve the visual result. We evaluate the visual results according to our success criteria and the feedback from users. Running times of the heuristic indicate that an improved version...

Manufacturing ontology through templates

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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.

Technique for designing a domain ontology

OpenAIRE

Palagin, A. V.; Petrenko, N. G.; Malakhov, K. S.

2018-01-01

The article describes the technique for designing a domain ontology, shows the flowchart of algorithm design and example of constructing a fragment of the ontology of the subject area of Computer Science is considered.

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...

Ontological and Epistemological Issues Regarding Climate Models and Computer Experiments

Science.gov (United States)

Vezer, M. A.

2010-12-01

Recent philosophical discussions (Parker 2009; Frigg and Reiss 2009; Winsberg, 2009; Morgon 2002, 2003, 2005; Gula 2002) about the ontology of computer simulation experiments and the epistemology of inferences drawn from them are of particular relevance to climate science as computer modeling and analysis are instrumental in understanding climatic systems. How do computer simulation experiments compare with traditional experiments? Is there an ontological difference between these two methods of inquiry? Are there epistemological considerations that result in one type of inference being more reliable than the other? What are the implications of these questions with respect to climate studies that rely on computer simulation analysis? In this paper, I examine these philosophical questions within the context of climate science, instantiating concerns in the philosophical literature with examples found in analysis of global climate change. I concentrate on Wendy Parker’s (2009) account of computer simulation studies, which offers a treatment of these and other questions relevant to investigations of climate change involving such modelling. Two theses at the center of Parker’s account will be the focus of this paper. The first is that computer simulation experiments ought to be regarded as straightforward material experiments; which is to say, there is no significant ontological difference between computer and traditional experimentation. Parker’s second thesis is that some of the emphasis on the epistemological importance of materiality has been misplaced. I examine both of these claims. First, I inquire as to whether viewing computer and traditional experiments as ontologically similar in the way she does implies that there is no proper distinction between abstract experiments (such as ‘thought experiments’ as well as computer experiments) and traditional ‘concrete’ ones. Second, I examine the notion of materiality (i.e., the material commonality between

The epistemology and ontology of human-computer interaction

NARCIS (Netherlands)

Brey, Philip A.E.

2005-01-01

This paper analyzes epistemological and ontological dimensions of Human-Computer Interaction (HCI) through an analysis of the functions of computer systems in relation to their users. It is argued that the primary relation between humans and computer systems has historically been epistemic:

Rice Transcriptome Analysis to Identify Possible Herbicide Quinclorac Detoxification Genes

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Wenying eXu

2015-09-01

Full Text Available Quinclorac is a highly selective auxin-type herbicide, and is widely used in the effective control of barnyard grass in paddy rice fields, improving the world’s rice yield. The herbicide mode of action of quinclorac has been proposed and hormone interactions affect quinclorac signaling. Because of widespread use, quinclorac may be transported outside rice fields with the drainage waters, leading to soil and water pollution and environmental health problems.In this study, we used 57K Affymetrix rice whole-genome array to identify quinclorac signaling response genes to study the molecular mechanisms of action and detoxification of quinclorac in rice plants. Overall, 637 probe sets were identified with differential expression levels under either 6 or 24 h of quinclorac treatment. Auxin-related genes such as GH3 and OsIAAs responded to quinclorac treatment. Gene Ontology analysis showed that genes of detoxification-related family genes were significantly enriched, including cytochrome P450, GST, UGT, and ABC and drug transporter genes. Moreover, real-time RT-PCR analysis showed that top candidate P450 families such as CYP81, CYP709C and CYP72A genes were universally induced by different herbicides. Some Arabidopsis genes for the same P450 family were up-regulated under quinclorac treatment.We conduct rice whole-genome GeneChip analysis and the first global identification of quinclorac response genes. This work may provide potential markers for detoxification of quinclorac and biomonitors of environmental chemical pollution.

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...

Player-Specific Conflict Handling Ontology

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Charline Hondrou

2014-09-01

Full Text Available This paper presents an ontology that leads the player of a serious game - regarding conflict handling - to the educative experience from which they will benefit the most. It provides a clearly defined tree of axioms that maps the player’s visually manifested affective cues and emotional stimuli from the serious game to conflict handling styles and proposes interventions. The importance of this ontology lies in the fact that it promotes natural interaction (non-invasive methods and at the same time makes the game as player-specific as it can be for its educational goal. It is an ontology that can be adapted to different educational theories and serve various educational purposes.

Ontology Matching with Semantic Verification.

Science.gov (United States)

Jean-Mary, Yves R; Shironoshita, E Patrick; Kabuka, Mansur R

2009-09-01

ASMOV (Automated Semantic Matching of Ontologies with Verification) is a novel algorithm that uses lexical and structural characteristics of two ontologies to iteratively calculate a similarity measure between them, derives an alignment, and then verifies it to ensure that it does not contain semantic inconsistencies. In this paper, we describe the ASMOV algorithm, and then present experimental results that measure its accuracy using the OAEI 2008 tests, and that evaluate its use with two different thesauri: WordNet, and the Unified Medical Language System (UMLS). These results show the increased accuracy obtained by combining lexical, structural and extensional matchers with semantic verification, and demonstrate the advantage of using a domain-specific thesaurus for the alignment of specialized ontologies.

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...

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

ContoExam: an ontology on context-aware examinations

NARCIS (Netherlands)

Brandt, P.; Basten, A.A.; Stuijk, S.

2014-01-01

Patient observations in health care, subjective surveys in social research or dyke sensor data in water management are all examples of measurements. Several ontologies already exist to express measurements, W3C's SSN ontology being a prominent example. However, these ontologies address quantities

On the ontological emergence from quantum regime

Energy Technology Data Exchange (ETDEWEB)

Luty, Damian [Adam Mickiewicz University, Poznan (Poland)

2014-07-01

There are several views on the relation between quantum physics and theory of relativity (especially General Relativity, GR). A popular perspective is this: GR with its macroscopic gravitational effects will turn out to be a limit of a more fundamental theory which should consider discrete physics and not deal with continuity (like theory of relativity). Thus, GR will emerge from a more basic theory, which should be quantum-like. One could call this an epistemic emergence view towards fundamental theories. The question is, given that scientific realism is valid: should emergence be a fundamental notion in our ontological view about the evolving, physical Universe? Is there an ontological emergence fully compatible with the notion of fundamentality? I argue that if we want to defend ontological emergence (from quantum to macroscopic regime) as something fundamental, we will arrive at the position of metaphysics of dispositions (and I argue, why this is undesirable), or conclude, that we cannot square fully fundamental ontology with the notion of emergence, and that we have to accept an ontological pluralism relativised to a certain scale. I defend the latter proposition, showing, that epistemic emergence doesn't entail (logically) ontological emergence.

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...

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.

Semantics and metaphysics in informatics: toward an ontology of tasks.

Science.gov (United States)

Figdor, Carrie

2011-04-01

This article clarifies three principles that should guide the development of any cognitive ontology. First, that an adequate cognitive ontology depends essentially on an adequate task ontology; second, that the goal of developing a cognitive ontology is independent of the goal of finding neural implementations of the processes referred to in the ontology; and third, that cognitive ontologies are neutral regarding the metaphysical relationship between cognitive and neural processes. Copyright © 2011 Cognitive Science Society, Inc.

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.

Ontology through a Mindfulness Process

Science.gov (United States)

Bearance, Deborah; Holmes, Kimberley

2015-01-01

Traditionally, when ontology is taught in a graduate studies course on social research, there is a tendency for this concept to be examined through the process of lectures and readings. Such an approach often leaves graduate students to grapple with a personal embodiment of this concept and to comprehend how ontology can ground their research.…

A topographic feature taxonomy for a U.S. national topographic mapping ontology

Science.gov (United States)

Varanka, Dalia E.

2013-01-01

Using legacy feature lists from the U.S. National Topographic Mapping Program of the twentieth century, a taxonomy of features is presented for purposes of developing a national topographic feature ontology for geographic mapping and analysis. After reviewing published taxonomic classifications, six basic classes are suggested; terrain, surface water, ecological regimes, built-up areas, divisions, and events. Aspects of ontology development are suggested as the taxonomy is described.

Center of excellence in research reporting in neurosurgery--diagnostic ontology.

Directory of Open Access Journals (Sweden)

Amrapali Zaveri

Full Text Available MOTIVATION: Evidence-based medicine (EBM, in the field of neurosurgery, relies on diagnostic studies since Randomized Controlled Trials (RCTs are uncommon. However, diagnostic study reporting is less standardized which increases the difficulty in reliably aggregating results. Although there have been several initiatives to standardize reporting, they have shown to be sub-optimal. Additionally, there is no central repository for storing and retrieving related articles. RESULTS: In our approach we formulate a computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct Systematic Reviews-Meta Analysis (SR-MA for diagnostic studies, which will assist in standardized reporting of diagnostic articles. SR-MA are studies that aggregate several studies to come to one conclusion for a particular research question. We also report high percentage of agreement among five observers as a result of the interobserver agreement test that we conducted among them to annotate 13 articles using the diagnostic ontology. Moreover, we extend our existing repository CERR-N to include diagnostic studies. AVAILABILITY: The ontology is available for download as an.owl file at: http://bioportal.bioontology.org/ontologies/3013.

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

An Ontology for Description of Drug Discovery Investigations

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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

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.

Menthor Editor: An Ontology-Driven Conceptual Modeling Platform

NARCIS (Netherlands)

Moreira, João Luiz; Sales, Tiago Prince; Guerson, John; Braga, Bernardo F.B; Brasileiro, Freddy; Sobral, Vinicius

2016-01-01

The lack of well-founded constructs in ontology tools can lead to the construction of non-intended models. In this demonstration we present the Menthor Editor, an ontology-driven conceptual modelling platform which incorporates the theories of the Unified Foundational Ontology (UFO). We illustrate

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),

Science Fiction and Ontologies of Leadership

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Jana Vizmuller-Zocco

2014-12-01

Full Text Available The role of leadership in science fiction receives a particular analysis which is based on what can be termed transhumanist novels published in Italy between 2008 and 2013. The main purpose of this study is to answer the following question: What happens to (the nature of leadership in a technologically-driven society? Four novels form the backbone of the description of futuristic leadership. The four conclusions drawn from this analysis regarding the nature of leadership in a technologically-driven society point to a much greater need for leadership studies to pay attention to technological advances (and the philosophical underpinnings of, specifically, transhumanism. The impact of nano-bio-technology affecting the role of leaders, followers, goals, alignment, commitment has ontological repercussions on the manner in which (augmented and unaugmented humans deal with each other. If early augmented humans/cyborgs and any other sentient beings are in fact comparable to Giambattista Vico’s brutes, and if his corsi e ricorsi (ebbs and flows of human history can apply to non-human, sentient beings’ history, then the work is cut out for all disciplines, but especially for those which deal with ontologies of leadership.

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.

St. Thomas and the hilemorfic ontology

Directory of Open Access Journals (Sweden)

Lawrence Dewan, O.P.

2009-06-01

Full Text Available This article presents the relevancy of Aristotle’s hylemorphic ontology.Aristotle himself highlighted the importance and astonishing complexityof the problem of prime matter’s ontological status and he presenting thesolution in his doctrine of hylemorphism. As Saint Thomas Aquinasnoted, it is a crucial issue for philosophy because all four, hilemorfism,logic, physics and metaphysics, stand or fall depending on a correctunderstanding of the ontology of prime matter and of the kind of causalrelationship which exist between prime matter and substantial form ingenerable and corruptible substance.

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

The ultimate constituents of the material world. In search of an ontology for fundamental physics

Energy Technology Data Exchange (ETDEWEB)

Kuhlmann, Meinard

2010-07-01

Today, quantum field theory (QFT) - the mathematical and conceptual framework for contemporary elementary particle physics - is the best starting point for analysing the fundamental building blocks of the material world. QFT if taken seriously in its metaphysical implications yields a picture of the world that is at variance with central classical conceptions. The core of Kuhlmann's investigation consists in the analysis of various ontological interpretations of QFT, e.g. substance ontologies as well as a process-ontological approach. Eventually, Kuhlmann proposes a dispositional trope ontology, according to which particularized properties and not things are the most basic entities, in terms of which all other entities are to be analysed, e.g as bundles of properties. This book was chosen for the 2009 ontos-Award for research on analytical ontology and metaphysics by the German Society for Analytical Philosophy. (orig.)

The ultimate constituents of the material world. In search of an ontology for fundamental physics

International Nuclear Information System (INIS)

Kuhlmann, Meinard

2010-01-01

Today, quantum field theory (QFT) - the mathematical and conceptual framework for contemporary elementary particle physics - is the best starting point for analysing the fundamental building blocks of the material world. QFT if taken seriously in its metaphysical implications yields a picture of the world that is at variance with central classical conceptions. The core of Kuhlmann's investigation consists in the analysis of various ontological interpretations of QFT, e.g. substance ontologies as well as a process-ontological approach. Eventually, Kuhlmann proposes a dispositional trope ontology, according to which particularized properties and not things are the most basic entities, in terms of which all other entities are to be analysed, e.g as bundles of properties. This book was chosen for the 2009 ontos-Award for research on analytical ontology and metaphysics by the German Society for Analytical Philosophy. (orig.)

Axiomatic Ontology Learning Approaches for English Translation of the Meaning of Quranic Texts

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Saad Saidah

2017-01-01

Full Text Available Ontology learning (OL is the computational task of generating a knowledge base in the form of an ontology, given an unstructured corpus in natural language (NL. While most works in the field of ontology learning have been primarily based on a statistical approach to extract lightweight OL, very few attempts have been made to extract axiomatic OL (called heavyweight OL from NL text documents. Axiomatic OL supports more precise formal logic-based reasoning when compared to lightweight OL. Lexico-syntactic pattern matching and statisticsal one cannot lead to very accurate learning, mostly because of several linguistic nuances in the NL. Axiomatic OL is an alternative methodology that has not been explored much, where a deep linguistics analysis in computational linguistics is used to generate formal axioms and definitions instead of simply inducing a taxonomy. The ontology that is created not only stores the information about the application domain in explicit knowledge, but also can deduce the implicit knowledge from this ontology. This research will explore the English translation of the meaning of Quranic texts.

Conflict Resolution in Partially Ordered OWL DL Ontologies

NARCIS (Netherlands)

Ji, Q.; Gao, Z.; Huang, Z.

2014-01-01

Inconsistency handling in OWL DL ontologies is an important problem because an ontology can easily be inconsistent when it is generated or modified. Current approaches to dealing with inconsistent ontologies often assume that there exists a total order over axioms and use such an order to select

An Ontology for Modeling Complex Inter-relational Organizations

Science.gov (United States)

Wautelet, Yves; Neysen, Nicolas; Kolp, Manuel

This paper presents an ontology for organizational modeling through multiple complementary aspects. The primary goal of the ontology is to dispose of an adequate set of related concepts for studying complex organizations involved in a lot of relationships at the same time. In this paper, we define complex organizations as networked organizations involved in a market eco-system that are playing several roles simultaneously. In such a context, traditional approaches focus on the macro analytic level of transactions; this is supplemented here with a micro analytic study of the actors' rationale. At first, the paper overviews enterprise ontologies literature to position our proposal and exposes its contributions and limitations. The ontology is then brought to an advanced level of formalization: a meta-model in the form of a UML class diagram allows to overview the ontology concepts and their relationships which are formally defined. Finally, the paper presents the case study on which the ontology has been validated.

Applying novel technologies and methods to inform the ontology of self-regulation.

Science.gov (United States)

Eisenberg, Ian W; Bissett, Patrick G; Canning, Jessica R; Dallery, Jesse; Enkavi, A Zeynep; Whitfield-Gabrieli, Susan; Gonzalez, Oscar; Green, Alan I; Greene, Mary Ann; Kiernan, Michaela; Kim, Sunny Jung; Li, Jamie; Lowe, Michael R; Mazza, Gina L; Metcalf, Stephen A; Onken, Lisa; Parikh, Sadev S; Peters, Ellen; Prochaska, Judith J; Scherer, Emily A; Stoeckel, Luke E; Valente, Matthew J; Wu, Jialing; Xie, Haiyi; MacKinnon, David P; Marsch, Lisa A; Poldrack, Russell A

2018-02-01

Self-regulation is a broad construct representing the general ability to recruit cognitive, motivational and emotional resources to achieve long-term goals. This construct has been implicated in a host of health-risk behaviors, and is a promising target for fostering beneficial behavior change. Despite its clear importance, the behavioral, psychological and neural components of self-regulation remain poorly understood, which contributes to theoretical inconsistencies and hinders maximally effective intervention development. We outline a research program that seeks to define a neuropsychological ontology of self-regulation, articulating the cognitive components that compose self-regulation, their relationships, and their associated measurements. The ontology will be informed by two large-scale approaches to assessing individual differences: first purely behaviorally using data collected via Amazon's Mechanical Turk, then coupled with neuroimaging data collected from a separate population. To validate the ontology and demonstrate its utility, we will then use it to contextualize health risk behaviors in two exemplar behavioral groups: overweight/obese adults who binge eat and smokers. After identifying ontological targets that precipitate maladaptive behavior, we will craft interventions that engage these targets. If successful, this work will provide a structured, holistic account of self-regulation in the form of an explicit ontology, which will better clarify the pattern of deficits related to maladaptive health behavior, and provide direction for more effective behavior change interventions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Discovering Diabetes Complications: an Ontology Based Model.

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Daghistani, Tahani; Shammari, Riyad Al; Razzak, Muhammad Imran

2015-12-01

Diabetes is a serious disease that spread in the world dramatically. The diabetes patient has an average of risk to experience complications. Take advantage of recorded information to build ontology as information technology solution will help to predict patients who have average of risk level with certain complication. It is helpful to search and present patient's history regarding different risk factors. Discovering diabetes complications could be useful to prevent or delay the complications. We designed ontology based model, using adult diabetes patients' data, to discover the rules of diabetes with its complications in disease to disease relationship. Various rules between different risk factors of diabetes Patients and certain complications generated. Furthermore, new complications (diseases) might be discovered as new finding of this study, discovering diabetes complications could be useful to prevent or delay the complications. The system can identify the patients who are suffering from certain risk factors such as high body mass index (obesity) and starting controlling and maintaining plan.

An Ontological Architecture for Orbital Debris Data

OpenAIRE

Rovetto, Robert J.

2017-01-01

The orbital debris problem presents an opportunity for inter-agency and international cooperation toward the mutually beneficial goals of debris prevention, mitigation, remediation, and improved space situational awareness (SSA). Achieving these goals requires sharing orbital debris and other SSA data. Toward this, I present an ontological architecture for the orbital debris domain, taking steps in the creation of an orbital debris ontology (ODO). The purpose of this ontological system is to ...

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...

MultiFarm: A Benchmark for Multilingual Ontology Matching

NARCIS (Netherlands)

Meilicke, C.; García-Castro, R.; Freitas, F.; van Hage, W.R.; Montiel-Ponsoda, E.; Ribeiro de Azevedo, R.; Stuckenschmidt, H.; Svab-Zamazal, O.; Svatek, V.; Tamalin, A.; Wang, S.

2012-01-01

In this paper we present the MultiFarm dataset, which has been designed as a benchmark for multilingual ontology matching. The MultiFarm dataset is composed of a set of ontologies translated in different languages and the corresponding alignments between these ontologies. It is based on the OntoFarm

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

Collaborative ontology development for the geosciences

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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

Building an Ontology of Tablewares using 'Legacy Data'

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Daniël van Helden

2018-05-01

Full Text Available This article aims to demonstrate how an ontology can be constructed to encompass many of the criteria needed for more consumption-orientated approaches to Roman tablewares. For this it demonstrates how a dataset in a relational database can be organised for the format and capabilities of an ontology, and then how these data are input into the ontology model. Finally it includes some sample analyses to show the effectiveness of such an ontology for types of analyses that are relevant to this network.

Ontology: ambiguity and accuracy

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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.

Ontology for the asexual development and anatomy of the colonial chordate Botryllus schlosseri.

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Lucia Manni

Full Text Available Ontologies provide an important resource to integrate information. For developmental biology and comparative anatomy studies, ontologies of a species are used to formalize and annotate data that are related to anatomical structures, their lineage and timing of development. Here, we have constructed the first ontology for anatomy and asexual development (blastogenesis of a bilaterian, the colonial tunicate Botryllus schlosseri. Tunicates, like Botryllus schlosseri, are non-vertebrates and the only chordate taxon species that reproduce both sexually and asexually. Their tadpole larval stage possesses structures characteristic of all chordates, i.e. a notochord, a dorsal neural tube, and gill slits. Larvae settle and metamorphose into individuals that are either solitary or colonial. The latter reproduce both sexually and asexually and these two reproductive modes lead to essentially the same adult body plan. The Botryllus schlosseri Ontology of Development and Anatomy (BODA will facilitate the comparison between both types of development. BODA uses the rules defined by the Open Biomedical Ontologies Foundry. It is based on studies that investigate the anatomy, blastogenesis and regeneration of this organism. BODA features allow the users to easily search and identify anatomical structures in the colony, to define the developmental stage, and to follow the morphogenetic events of a tissue and/or organ of interest throughout asexual development. We invite the scientific community to use this resource as a reference for the anatomy and developmental ontology of B. schlosseri and encourage recommendations for updates and improvements.

Application of neuroanatomical ontologies for neuroimaging data annotation

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Jessica A Turner

2010-06-01

Full Text Available The annotation of functional neuroimaging results for data sharing and reuse is particularly challenging, due to the diversity of terminologies of neuroanatomical structures and cortical parcellation schemes. To address this challenge, we extended the Foundational Model of Anatomy Ontology (FMA to include cytoarchitectural, Brodmann area labels, and a morphological cortical labeling scheme (e.g., the part of Brodmann area 6 in the left precentral gyrus. This representation was also used to augment the neuroanatomical axis of RadLex, the ontology for clinical imaging. The resulting neuroanatomical ontology contains explicit relationships indicating which brain regions are “part of” which other regions, across cytoarchitectural and morphological labeling schemas. We annotated a large functional neuroimaging dataset with terms from the ontology and applied a reasoning engine to analyze this dataset in conjunction with the ontology, and achieved successful inferences from the most specific level (e.g., how many subjects showed activation in a sub-part of the middle frontal gyrus to more general (how many activations were found in areas connected via a known white matter tract?. In summary, we have produced a neuroanatomical ontology that harmonizes several different terminologies of neuroanatomical structures and cortical parcellation schemes. This neuranatomical ontology is publicly available as a view of FMA at the Bioportal website at http://rest.bioontology.org/bioportal/ontologies/download/10005. The ontological encoding of anatomic knowledge can be exploited by computer reasoning engines to make inferences about neuroanatomical relationships described in imaging datasets using different terminologies. This approach could ultimately enable knowledge discovery from large, distributed fMRI studies or medical record mining.

HuPSON: the human physiology simulation ontology.

Science.gov (United States)

Gündel, Michaela; Younesi, Erfan; Malhotra, Ashutosh; Wang, Jiali; Li, Hui; Zhang, Bijun; de Bono, Bernard; Mevissen, Heinz-Theodor; Hofmann-Apitius, Martin

2013-11-22

Large biomedical simulation initiatives, such as the Virtual Physiological Human (VPH), are substantially dependent on controlled vocabularies to facilitate the exchange of information, of data and of models. Hindering these initiatives is a lack of a comprehensive ontology that covers the essential concepts of the simulation domain. We propose a first version of a newly constructed ontology, HuPSON, as a basis for shared semantics and interoperability of simulations, of models, of algorithms and of other resources in this domain. The ontology is based on the Basic Formal Ontology, and adheres to the MIREOT principles; the constructed ontology has been evaluated via structural features, competency questions and use case scenarios.The ontology is freely available at: http://www.scai.fraunhofer.de/en/business-research-areas/bioinformatics/downloads.html (owl files) and http://bishop.scai.fraunhofer.de/scaiview/ (browser). HuPSON provides a framework for a) annotating simulation experiments, b) retrieving relevant information that are required for modelling, c) enabling interoperability of algorithmic approaches used in biomedical simulation, d) comparing simulation results and e) linking knowledge-based approaches to simulation-based approaches. It is meant to foster a more rapid uptake of semantic technologies in the modelling and simulation domain, with particular focus on the VPH domain.

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.

Ontology Alignment Architecture for Semantic Sensor Web Integration

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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.

Development and Evaluation of an Adolescents' Depression Ontology for Analyzing Social Data.

Science.gov (United States)

Jung, Hyesil; Park, Hyeoun-Ae; Song, Tae-Min

2016-01-01

This study aims to develop and evaluate an ontology for adolescents' depression to be used for collecting and analyzing social data. The ontology was developed according to the 'ontology development 101' methodology. Concepts were extracted from clinical practice guidelines and related literatures. The ontology is composed of five sub-ontologies which represent risk factors, sign and symptoms, measurement, diagnostic result and management care. The ontology was evaluated in four different ways: First, we examined the frequency of ontology concept appeared in social data; Second, the content coverage of ontology was evaluated by comparing ontology concepts with concepts extracted from the youth depression counseling records; Third, the structural and representational layer of the ontology were evaluated by 5 ontology and psychiatric nursing experts; Fourth, the scope of the ontology was examined by answering 59 competency questions. The ontology was improved by adding new concepts and synonyms and revising the level of structure.

THE USE OF ONTOLOGIES OF EDUCATIONAL PURPOSES FOR THE FORMATION OF EDUCATIONAL AND OPERATIONAL ENVIRONMENT

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О. Буров

2012-04-01

Full Text Available Object of study - an ontology for educational purposes and theirimpact on the effectiveness of training. Purpose -substantiation the feasibility of using ontologies of educational purposes for the formation learningenvironment of specialists in the field of aviation. The method of study - an analysis of existing methods and meansofforming an ontology for educational purposes, in particular by the method of structuring the domain and the methodof generalization. The main aspects of the formation of knowledge bases for educational purposes with the useof ontologies are considered. The approaches and means of forming domains of knowledge bases based on ontologiesare described. Shaped ergonomic requirements for content and form of ontologies for educational purposes. It isestablished that the introduction and use of ontologies for educational purposes requires a much larger audience insearch of independence and mastery of new knowledge that provides a high level of intensification of educationalprocess, as well asincrease the efficiency of the educational process by intensifyingand enhancing learning andcognitive activities, giving her the creative direction of research that is a prerequisite for more effective learning

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.

Ontology-based Metadata Portal for Unified Semantics

Data.gov (United States)

National Aeronautics and Space Administration — The Ontology-based Metadata Portal for Unified Semantics (OlyMPUS) will extend the prototype Ontology-Driven Interactive Search Environment for Earth Sciences...

Quantum physics and relational ontology

Energy Technology Data Exchange (ETDEWEB)

Cordovil, Joao [Center of Philosophy of Sciences of University of Lisbon (Portugal)

2013-07-01

The discovery of the quantum domain of reality put a serious ontological challenge, a challenge that is still well present in the recent developments of Quantum Physics. Physics was conceived from an atomistic conception of the world, reducing it, in all its diversity, to two types of entities: simple, individual and immutable entities (atoms, in metaphysical sense) and composite entities, resulting solely from combinations. Linear combinations, additive, indifferent to the structure or to the context. However, the discovery of wave-particle dualism and the developments in Quantum Field Theories and in Quantum Nonlinear Physical, showed that quantum entities are not, in metaphysical sense, neither simple, nor merely the result of linear (or additive) combinations. In other words, the ontological foundations of Physics revealed as inadequate to account for the nature of quantum entities. Then a fundamental challenge arises: How to think the ontic nature of these entities? In my view, this challenge appeals to a relational and dynamist ontology of physical entities. This is the central hypothesis of this communication. In this sense, this communication has two main intentions: 1) positively characterize this relational and dynamist ontology; 2) show some elements of its metaphysical suitability to contemporary Quantum Physics.

Knowledge Representation in Patient Safety Reporting: An Ontological Approach

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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.

Ontology-based concept map learning path reasoning system using SWRL rules

Energy Technology Data Exchange (ETDEWEB)

Chu, K.-K.; Lee, C.-I. [National Univ. of Tainan, Taiwan (China). Dept. of Computer Science and Information Learning Technology

2010-08-13

Concept maps are graphical representations of knowledge. Concept mapping may reduce students' cognitive load and extend simple memory function. The purpose of this study was on the diagnosis of students' concept map learning abilities and the provision of personally constructive advice dependant on their learning path and progress. Ontology is a useful method with which to represent and store concept map information. Semantic web rule language (SWRL) rules are easy to understand and to use as specific reasoning services. This paper discussed the selection of grade 7 lakes and rivers curriculum for which to devise a concept map learning path reasoning service. The paper defined a concept map e-learning ontology and two SWRL semantic rules, and collected users' concept map learning path data to infer implicit knowledge and to recommend the next learning path for users. It was concluded that the designs devised in this study were feasible and advanced and the ontology kept the domain knowledge preserved. SWRL rules identified an abstraction model for inferred properties. Since they were separate systems, they did not interfere with each other, while ontology or SWRL rules were maintained, ensuring persistent system extensibility and robustness. 15 refs., 1 tab., 8 figs.

The Cognitive Paradigm Ontology: Design and Application

Science.gov (United States)

Laird, Angela R.

2013-01-01

We present the basic structure of the Cognitive Paradigm Ontology (CogPO) for human behavioral experiments. While the experimental psychology and cognitive neuroscience literature may refer to certain behavioral tasks by name (e.g., the Stroop paradigm or the Sternberg paradigm) or by function (a working memory task, a visual attention task), these paradigms can vary tremendously in the stimuli that are presented to the subject, the response expected from the subject, and the instructions given to the subject. Drawing from the taxonomy developed and used by the BrainMap project (www.brainmap.org) for almost two decades to describe key components of published functional imaging results, we have developed an ontology capable of representing certain characteristics of the cognitive paradigms used in the fMRI and PET literature. The Cognitive Paradigm Ontology is being developed to be compliant with the Basic Formal Ontology (BFO), and to harmonize where possible with larger ontologies such as RadLex, NeuroLex, or the Ontology of Biomedical Investigations (OBI). The key components of CogPO include the representation of experimental conditions focused on the stimuli presented, the instructions given, and the responses requested. The use of alternate and even competitive terminologies can often impede scientific discoveries. Categorization of paradigms according to stimulus, response, and instruction has been shown to allow advanced data retrieval techniques by searching for similarities and contrasts across multiple paradigm levels. The goal of CogPO is to develop, evaluate, and distribute a domain ontology of cognitive paradigms for application and use in the functional neuroimaging community. PMID:21643732

PANTHER version 11: expanded annotation data from Gene Ontology and Reactome pathways, and data analysis tool enhancements.

Science.gov (United States)

Mi, Huaiyu; Huang, Xiaosong; Muruganujan, Anushya; Tang, Haiming; Mills, Caitlin; Kang, Diane; Thomas, Paul D

2017-01-04

The PANTHER database (Protein ANalysis THrough Evolutionary Relationships, http://pantherdb.org) contains comprehensive information on the evolution and function of protein-coding genes from 104 completely sequenced genomes. PANTHER software tools allow users to classify new protein sequences, and to analyze gene lists obtained from large-scale genomics experiments. In the past year, major improvements include a large expansion of classification information available in PANTHER, as well as significant enhancements to the analysis tools. Protein subfamily functional classifications have more than doubled due to progress of the Gene Ontology Phylogenetic Annotation Project. For human genes (as well as a few other organisms), PANTHER now also supports enrichment analysis using pathway classifications from the Reactome resource. The gene list enrichment tools include a new 'hierarchical view' of results, enabling users to leverage the structure of the classifications/ontologies; the tools also allow users to upload genetic variant data directly, rather than requiring prior conversion to a gene list. The updated coding single-nucleotide polymorphisms (SNP) scoring tool uses an improved algorithm. The hidden Markov model (HMM) search tools now use HMMER3, dramatically reducing search times and improving accuracy of E-value statistics. Finally, the PANTHER Tree-Attribute Viewer has been implemented in JavaScript, with new views for exploring protein sequence evolution. © The Author(s) 2016. Published by Oxford University Press on behalf of Nucleic Acids Research.

Self-supervised Chinese ontology learning from online encyclopedias.

Science.gov (United States)

Hu, Fanghuai; Shao, Zhiqing; Ruan, Tong

2014-01-01

Constructing ontology manually is a time-consuming, error-prone, and tedious task. We present SSCO, a self-supervised learning based chinese ontology, which contains about 255 thousand concepts, 5 million entities, and 40 million facts. We explore the three largest online Chinese encyclopedias for ontology learning and describe how to transfer the structured knowledge in encyclopedias, including article titles, category labels, redirection pages, taxonomy systems, and InfoBox modules, into ontological form. In order to avoid the errors in encyclopedias and enrich the learnt ontology, we also apply some machine learning based methods. First, we proof that the self-supervised machine learning method is practicable in Chinese relation extraction (at least for synonymy and hyponymy) statistically and experimentally and train some self-supervised models (SVMs and CRFs) for synonymy extraction, concept-subconcept relation extraction, and concept-instance relation extraction; the advantages of our methods are that all training examples are automatically generated from the structural information of encyclopedias and a few general heuristic rules. Finally, we evaluate SSCO in two aspects, scale and precision; manual evaluation results show that the ontology has excellent precision, and high coverage is concluded by comparing SSCO with other famous ontologies and knowledge bases; the experiment results also indicate that the self-supervised models obviously enrich SSCO.

Gastric Cancer Associated Genes Identified by an Integrative Analysis of Gene Expression Data

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Bing Jiang

2017-01-01

Full Text Available Gastric cancer is one of the most severe complex diseases with high morbidity and mortality in the world. The molecular mechanisms and risk factors for this disease are still not clear since the cancer heterogeneity caused by different genetic and environmental factors. With more and more expression data accumulated nowadays, we can perform integrative analysis for these data to understand the complexity of gastric cancer and to identify consensus players for the heterogeneous cancer. In the present work, we screened the published gene expression data and analyzed them with integrative tool, combined with pathway and gene ontology enrichment investigation. We identified several consensus differentially expressed genes and these genes were further confirmed with literature mining; at last, two genes, that is, immunoglobulin J chain and C-X-C motif chemokine ligand 17, were screened as novel gastric cancer associated genes. Experimental validation is proposed to further confirm this finding.

An improved ontological representation of dendritic cells as a paradigm for all cell types

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Mungall Chris

2009-02-01

Full Text Available Abstract Background Recent increases in the volume and diversity of life science data and information and an increasing emphasis on data sharing and interoperability have resulted in the creation of a large number of biological ontologies, including the Cell Ontology (CL, designed to provide a standardized representation of cell types for data annotation. Ontologies have been shown to have significant benefits for computational analyses of large data sets and for automated reasoning applications, leading to organized attempts to improve the structure and formal rigor of ontologies to better support computation. Currently, the CL employs multiple is_a relations, defining cell types in terms of histological, functional, and lineage properties, and the majority of definitions are written with sufficient generality to hold across multiple species. This approach limits the CL's utility for computation and for cross-species data integration. Results To enhance the CL's utility for computational analyses, we developed a method for the ontological representation of cells and applied this method to develop a dendritic cell ontology (DC-CL. DC-CL subtypes are delineated on the basis of surface protein expression, systematically including both species-general and species-specific types and optimizing DC-CL for the analysis of flow cytometry data. We avoid multiple uses of is_a by linking DC-CL terms to terms in other ontologies via additional, formally defined relations such as has_function. Conclusion This approach brings benefits in the form of increased accuracy, support for reasoning, and interoperability with other ontology resources. Accordingly, we propose our method as a general strategy for the ontological representation of cells. DC-CL is available from http://www.obofoundry.org.

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.

Rat Strain Ontology: structured controlled vocabulary designed to facilitate access to strain data at RGD.

Science.gov (United States)

Nigam, Rajni; Munzenmaier, Diane H; Worthey, Elizabeth A; Dwinell, Melinda R; Shimoyama, Mary; Jacob, Howard J

2013-11-22

The Rat Genome Database (RGD) ( http://rgd.mcw.edu/) is the premier site for comprehensive data on the different strains of the laboratory rat (Rattus norvegicus). The strain data are collected from various publications, direct submissions from individual researchers, and rat providers worldwide. Rat strain, substrain designation and nomenclature follow the Guidelines for Nomenclature of Mouse and Rat Strains, instituted by the International Committee on Standardized Genetic Nomenclature for Mice. While symbols and names aid in identifying strains correctly, the flat nature of this information prohibits easy search and retrieval, as well as other data mining functions. In order to improve these functionalities, particularly in ontology-based tools, the Rat Strain Ontology (RS) was developed. The Rat Strain Ontology (RS) reflects the breeding history, parental background, and genetic manipulation of rat strains. This controlled vocabulary organizes strains by type: inbred, outbred, chromosome altered, congenic, mutant and so on. In addition, under the chromosome altered category, strains are organized by chromosome, and further by type of manipulations, such as mutant or congenic. This allows users to easily retrieve strains of interest with modifications in specific genomic regions. The ontology was developed using the Open Biological and Biomedical Ontology (OBO) file format, and is organized on the Directed Acyclic Graph (DAG) structure. Rat Strain Ontology IDs are included as part of the strain report (RS: ######). As rat researchers are often unaware of the number of substrains or altered strains within a breeding line, this vocabulary now provides an easy way to retrieve all substrains and accompanying information. Its usefulness is particularly evident in tools such as the PhenoMiner at RGD, where users can now easily retrieve phenotype measurement data for related strains, strains with similar backgrounds or those with similar introgressed regions. This

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

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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.

An ontology design pattern for surface water features

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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.

Ontology Translation: The Semiotic Engineering of Content Management Systems

Directory of Open Access Journals (Sweden)

Alejandro Villamarin M.

2015-12-01

Full Text Available The present paper proposes the application of Semiotic Engineering theory to Content Management Systems (CMS focusing on the analysis of how the use of different ontologies can affect the user’s efficiency when performing tasks in a CMS. The analysis is performed using the theoretical semiotic model Web-Semiotic Interface Design Evaluation (W-SIDE model.

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

Development of FuGO: An Ontology for Functional Genomics Investigations

Science.gov (United States)

Whetzel, Patricia L.; Brinkman, Ryan R.; Causton, Helen C.; Fan, Liju; Field, Dawn; Fostel, Jennifer; Fragoso, Gilberto; Gray, Tanya; Heiskanen, Mervi; Hernandez-Boussard, Tina; Morrison, Norman; Parkinson, Helen; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Schober, Daniel; Smith, Barry; Stevens, Robert; Stoeckert, Christian J.; Taylor, Chris; White, Joe; Wood, Andrew

2009-01-01

The development of the Functional Genomics Investigation Ontology (FuGO) is a collaborative, international effort that will provide a resource for annotating functional genomics investigations, including the study design, protocols and instrumentation used, the data generated and the types of analysis performed on the data. FuGO will contain both terms that are universal to all functional genomics investigations and those that are domain specific. In this way, the ontology will serve as the “semantic glue” to provide a common understanding of data from across these disparate data sources. In addition, FuGO will reference out to existing mature ontologies to avoid the need to duplicate these resources, and will do so in such a way as to enable their ease of use in annotation. This project is in the early stages of development; the paper will describe efforts to initiate the project, the scope and organization of the project, the work accomplished to date, and the challenges encountered, as well as future plans. PMID:16901226

Where to search top-K biomedical ontologies?

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Oliveira, Daniela; Butt, Anila Sahar; Haller, Armin; Rebholz-Schuhmann, Dietrich; Sahay, Ratnesh

2018-03-20

Searching for precise terms and terminological definitions in the biomedical data space is problematic, as researchers find overlapping, closely related and even equivalent concepts in a single or multiple ontologies. Search engines that retrieve ontological resources often suggest an extensive list of search results for a given input term, which leads to the tedious task of selecting the best-fit ontological resource (class or property) for the input term and reduces user confidence in the retrieval engines. A systematic evaluation of these search engines is necessary to understand their strengths and weaknesses in different search requirements. We have implemented seven comparable Information Retrieval ranking algorithms to search through ontologies and compared them against four search engines for ontologies. Free-text queries have been performed, the outcomes have been judged by experts and the ranking algorithms and search engines have been evaluated against the expert-based ground truth (GT). In addition, we propose a probabilistic GT that is developed automatically to provide deeper insights and confidence to the expert-based GT as well as evaluating a broader range of search queries. The main outcome of this work is the identification of key search factors for biomedical ontologies together with search requirements and a set of recommendations that will help biomedical experts and ontology engineers to select the best-suited retrieval mechanism in their search scenarios. We expect that this evaluation will allow researchers and practitioners to apply the current search techniques more reliably and that it will help them to select the right solution for their daily work. The source code (of seven ranking algorithms), ground truths and experimental results are available at https://github.com/danielapoliveira/bioont-search-benchmark.

Design and Implementation of a Hybrid Ontological-Relational Data Repository for SIEM Systems

Directory of Open Access Journals (Sweden)

Igor Saenko

2013-07-01

Full Text Available The technology of Security Information and Event Management (SIEM becomes one of the most important research applications in the area of computer network security. The overall functionality of SIEM systems depends largely on the quality of solutions implemented at the data storage level, which is purposed for the representation of heterogeneous security events, their storage in the data repository, and the extraction of relevant data for analytical modules of SIEM systems. The paper discusses the key issues of design and implementation of a hybrid SIEM data repository, which combines relational and ontological data representations. Based on the analysis of existing SIEM systems and standards, the ontological approach is chosen as a core component of the repository, and an example of the ontological data model for vulnerabilities representation is outlined. The hybrid architecture of the repository is proposed for implementation in SIEM systems. Since the most of works on the repositories of SIEM systems is based on the relational data model, the paper focuses mainly on the ontological part of the hybrid approach. To test the repository we used the data model intended for attack modeling and security evaluation, which includes both ontological and relational dimensions.

Ontology - MicrobeDB.jp | LSDB Archive [Life Science Database Archive metadata

Lifescience Database Archive (English)

Full Text Available gzip) consists of some directories (see the following table). Data file File name: ontology....tar.gz File URL: ftp://ftp.biosciencedbc.jp/archive/microbedb/LATEST/ontology.tar.gz File size: 9...he NCBI Taxonomy and INSDC ontology files were obtained from the DDBJ web site. O...ples Data item Description ontology/meo/meo.ttl An ontology for describing organismal habitats (especially focused on microbes). onto...logy/meo/meo_fma_mapping.ttl An ontology mapping files t

Ontological, Epistemological and Methodological Assumptions: Qualitative versus Quantitative

Science.gov (United States)

Ahmed, Abdelhamid

2008-01-01

The review to follow is a comparative analysis of two studies conducted in the field of TESOL in Education published in "TESOL QUARTERLY." The aspects to be compared are as follows. First, a brief description of each study will be presented. Second, the ontological, epistemological and methodological assumptions underlying each study…

Ontology Enabled Generation of Embedded Web Services