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

UDC.coleccionInvestigaciónes_ES
UDC.departamentoCiencias da Computación e Tecnoloxías da Informaciónes_ES
UDC.grupoInvRedes de Neuronas Artificiais e Sistemas Adaptativos -Informática Médica e Diagnóstico Radiolóxico (RNASA - IMEDIR)es_ES
UDC.journalTitleJournal of Biomedical Semanticses_ES
UDC.volume8es_ES
dc.contributor.authorMartínez-Romero, Marcos
dc.contributor.authorJonquet, Clement
dc.contributor.authorO'Connor, Martin J.
dc.contributor.authorGraybeal, John
dc.contributor.authorPazos, A.
dc.contributor.authorMusen, Mark A.
dc.date.accessioned2019-03-29T12:26:26Z
dc.date.available2019-03-29T12:26:26Z
dc.date.issued2017-06-07
dc.description.abstract[Abstract] Background. 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. Methods. 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. Results. 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. Conclusions. 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 and usefulness. Ontology Recommender 2.0 recommends over 500 biomedical ontologies from the NCBO BioPortal platform, where it is openly available (both via the user interface at http://bioportal.bioontology.org/recommender, and via a Web service API).es_ES
dc.description.sponsorshipNational Institutes of Health (United States); U54 HG004028es_ES
dc.description.sponsorshipCenter for Expanded Data Annotationand Retrieval (CEDAR); U54 AI11792es_ES
dc.description.sponsorshipAgence nationale de la recherche (France); NR-12-JS02-01001es_ES
dc.identifier.citationMartínez-Romero M, Jonquet C, O'Connor MJ, et al. NCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendation. J Biomed Semantics. 2017; 8: 21es_ES
dc.identifier.issn2041-1480
dc.identifier.urihttp://hdl.handle.net/2183/22429
dc.language.isoenges_ES
dc.publisherBioMed Centrales_ES
dc.relation.urihttps://doi.org/10.1186/s13326-017-0128-yes_ES
dc.rightsAtribución 3.0 Españaes_ES
dc.rights.accessRightsopen accesses_ES
dc.rights.urihttp://creativecommons.org/licenses/by/3.0/es/*
dc.subjectOntology selectiones_ES
dc.subjectOntology recommendationes_ES
dc.subjectOntology evaluationes_ES
dc.subjectSemantic webes_ES
dc.subjectBiomedical ontologieses_ES
dc.subjectNCBO BioPortales_ES
dc.titleNCBO Ontology Recommender 2.0: an enhanced approach for biomedical ontology recommendationes_ES
dc.typejournal articlees_ES
dspace.entity.typePublication
relation.isAuthorOfPublication82422cee-4f76-42f8-9289-19c2304abb80
relation.isAuthorOfPublicationfa192a4c-bffd-4b23-87ae-e68c29350cdc
relation.isAuthorOfPublication.latestForDiscovery82422cee-4f76-42f8-9289-19c2304abb80

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