0
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: not found
      • Article: not found

      A systematic analysis of term reuse and term overlap across biomedical ontologies

      1 , 1 , 1
      2
      Semantic Web
      IOS Press

      Read this article at

      ScienceOpenPublisherPMC
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          <p class="first" id="P1">Reusing ontologies and their terms is a principle and best practice that most ontology development methodologies strongly encourage. Reuse comes with the promise to support the semantic interoperability and to reduce engineering costs. In this paper, we present a descriptive study of the current extent of term reuse and overlap among biomedical ontologies. We use the corpus of biomedical ontologies stored in the BioPortal repository, and analyze different types of reuse and overlap constructs. While we find an approximate term overlap between 25–31%, the term reuse is only &lt;9%, with most ontologies reusing fewer than 5% of their terms from a small set of popular ontologies. Clustering analysis shows that the terms reused by a common set of ontologies have &gt;90% semantic similarity, hinting that ontology developers tend to reuse terms that are sibling or parent–child nodes. We validate this finding by analysing the logs generated from a Protégé plugin that enables developers to reuse terms from BioPortal. We find most reuse constructs were 2-level subtrees on the higher levels of the class hierarchy. We developed a Web application that visualizes reuse dependencies and overlap among ontologies, and that proposes similar terms from BioPortal for a term of interest. We also identified a set of error patterns that indicate that ontology developers did intend to reuse terms from other ontologies, but that they were using different and sometimes incorrect representations. Our results stipulate the need for semi-automated tools that augment term reuse in the ontology engineering process through personalized recommendations. </p>

          Related collections

          Most cited references15

          • Record: found
          • Abstract: found
          • Article: not found

          Gene Ontology: tool for the unification of biology

          Genomic sequencing has made it clear that a large fraction of the genes specifying the core biological functions are shared by all eukaryotes. Knowledge of the biological role of such shared proteins in one organism can often be transferred to other organisms. The goal of the Gene Ontology Consortium is to produce a dynamic, controlled vocabulary that can be applied to all eukaryotes even as knowledge of gene and protein roles in cells is accumulating and changing. To this end, three independent ontologies accessible on the World-Wide Web (http://www.geneontology.org) are being constructed: biological process, molecular function and cellular component.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            The Unified Medical Language System (UMLS): integrating biomedical terminology.

            The Unified Medical Language System (http://umlsks.nlm.nih.gov) is a repository of biomedical vocabularies developed by the US National Library of Medicine. The UMLS integrates over 2 million names for some 900,000 concepts from more than 60 families of biomedical vocabularies, as well as 12 million relations among these concepts. Vocabularies integrated in the UMLS Metathesaurus include the NCBI taxonomy, Gene Ontology, the Medical Subject Headings (MeSH), OMIM and the Digital Anatomist Symbolic Knowledge Base. UMLS concepts are not only inter-related, but may also be linked to external resources such as GenBank. In addition to data, the UMLS includes tools for customizing the Metathesaurus (MetamorphoSys), for generating lexical variants of concept names (lvg) and for extracting UMLS concepts from text (MetaMap). The UMLS knowledge sources are updated quarterly. All vocabularies are available at no fee for research purposes within an institution, but UMLS users are required to sign a license agreement. The UMLS knowledge sources are distributed on CD-ROM and by FTP.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              The OBO Foundry: coordinated evolution of ontologies to support biomedical data integration.

              The value of any kind of data is greatly enhanced when it exists in a form that allows it to be integrated with other data. One approach to integration is through the annotation of multiple bodies of data using common controlled vocabularies or 'ontologies'. Unfortunately, the very success of this approach has led to a proliferation of ontologies, which itself creates obstacles to integration. The Open Biomedical Ontologies (OBO) consortium is pursuing a strategy to overcome this problem. Existing OBO ontologies, including the Gene Ontology, are undergoing coordinated reform, and new ontologies are being created on the basis of an evolving set of shared principles governing ontology development. The result is an expanding family of ontologies designed to be interoperable and logically well formed and to incorporate accurate representations of biological reality. We describe this OBO Foundry initiative and provide guidelines for those who might wish to become involved.
                Bookmark

                Author and article information

                Journal
                Semantic Web
                SW
                IOS Press
                22104968
                15700844
                August 07 2017
                August 07 2017
                : 8
                : 6
                : 853-871
                Affiliations
                [1 ]Stanford Center for Biomedical Informatics Research, Department of Medicine, Stanford University, USA. E-mails: tudorache@stanford.edu, musen@stanford.edu
                [2 ]University of Kentucky, USA
                Article
                10.3233/SW-160238
                5555235
                28819351
                78ab8f48-3783-4577-a2ec-fe8b08d37952
                © 2017
                History

                Comments

                Comment on this article