Proposed SKOS Extensions for BioPortal Terminology Services

  • Cui Tao
  • Natalya F. Noy
  • Harold R. Solbrig
  • Nigam H. Shah
  • Mark A. Musen
  • Christopher G. Chute
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7185)

Abstract

The National Center for Biomedical Ontology (NCBO) BioPortal provides common access for browsing and querying a large set of ontologies that are commonly used in biomedical communities. One of our missions is to align lexical features (i.e., textual definitions) that are commonly used in these ontologies across different representation formats with standard tags and to represent them in a standard way to the users. The Simple Knowledge Organization System (SKOS) is a recommendation of the World-Wide-Web Consortium (W3C) for a common data model for sharing and linking knowledge organization systems on the Semantic Web. The BioPortal is in the process of adopting SKOS in the backend representation for its content. During this process, we discovered that there exists a set of commonly-used lexical features shared by the biomedical ontologies that SKOS does not yet represent. In this paper, we discuss our proposed SKOS extensions to cover this set of commonly used lexical features, the rationales, and the detailed description of each proposed construct.

Keywords

Resource Description Framework Biomedical Ontology Biomedical Domain Lexical Feature Common Data Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
  2. 2.
    ISOcat - data category registry (October 2011), http://www.isocat.org
  3. 3.
    AGROVOC Thesaurus, Food and Agriculture Organization of the United Nations (FAO), http://www.fao.org/agrovoc
  4. 4.
  5. 5.
    Bodenreider, O.: Biomedical Ontologies in Action: Role in Knowledge Management, Data Integration and Decision Support. In: Geissbuhler, A., Kulikowski, C. (eds.) IMIA Yearbook of Medical Informatics, vol. 47, pp. 67–79. International Medical Informatics Association (2008)Google Scholar
  6. 6.
    Chute, C.G.: The Copernican Era of Healthcare Terminology: A Re-Centering of Health Information Systems. In: AMIA Annual Symposium, pp. 68–73 (1998)Google Scholar
  7. 7.
    Chute, C.G.: Clinical Classification and Terminology: Some History and Current Observations. JAMIA 7(3), 298–303 (2000)Google Scholar
  8. 8.
    Library of congress subject headings, the library of congress cataloging distribution service, http://www.loc.gov/cds/lcsh.html
  9. 9.
  10. 10.
    Noy, N.F., Shah, N.H., Whetzel, P.L., Dai, B., Dorf, M., Griffith, N., Jonquet, C., Rubin, D.L., Storey, M.D., Chute, C.G., Musen, M.A.: Bioportal: ontologies and integrated data resources at the click of a mouse. Nucleic Acids Research 37, 170–173 (2009)CrossRefGoogle Scholar
  11. 11.
    The open biomedical ontologies, http://www.obofoundry.org/
  12. 12.
    OWL 2 web ontology language structural specification and functional-style syntax, http://www.w3.org/TR/owl2-syntax/
  13. 13.
  14. 14.
  15. 15.
  16. 16.
    SPARQL Query Language for RDF, www.w3.org/TR/rdf-sparql-query/
  17. 17.
    Tao, C., Pathak, J., Solbrig, H.R., Wei, W., Chute, C.G.: Common terminology guidelines for representing biomedical ontologies in semantic web notations. Journal of Biomedical Informaitcs (submitted)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Cui Tao
    • 1
  • Natalya F. Noy
    • 2
  • Harold R. Solbrig
    • 1
  • Nigam H. Shah
    • 2
  • Mark A. Musen
    • 2
  • Christopher G. Chute
    • 1
  1. 1.Division of Biomedical Statistics and InformaticsMayo Clinic College of MedicineRochester
  2. 2.Stanford Center for Biomedical Informatics ResearchStanford UniversityStanford

Personalised recommendations