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The center for expanded data annotation and retrieval.
Musen, Mark A; Bean, Carol A; Cheung, Kei-Hoi; Dumontier, Michel; Durante, Kim A; Gevaert, Olivier; Gonzalez-Beltran, Alejandra; Khatri, Purvesh; Kleinstein, Steven H; O'Connor, Martin J; Pouliot, Yannick; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Wiser, Jeffrey A.
Afiliação
  • Musen MA; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA musen@stanford.edu.
  • Bean CA; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
  • Cheung KH; Interdepartmental Program in Computational Biology and Bioinformatics, Department of Emergency Medicine, Yale University School of Medicine, New Haven, CT USA.
  • Dumontier M; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
  • Durante KA; Stanford University Libraries, Stanford University, Stanford, CA USA.
  • Gevaert O; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
  • Gonzalez-Beltran A; Oxford e-Research Centre, University of Oxford, Oxford, UK.
  • Khatri P; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA Stanford Institute for Immunity, Transplantation, and Infection, Stanford, CA USA.
  • Kleinstein SH; Interdepartmental Program in Computational Biology and Bioinformatics, Departments of Pathology and Immunobiology, Yale University School of Medicine, New Haven, CT USA.
  • O'Connor MJ; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
  • Pouliot Y; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA USA.
  • Rocca-Serra P; Oxford e-Research Centre, University of Oxford, Oxford, UK.
  • Sansone SA; Oxford e-Research Centre, University of Oxford, Oxford, UK.
  • Wiser JA; Northrop Grumman Corporation, West Falls Church, VA USA.
J Am Med Inform Assoc ; 22(6): 1148-52, 2015 Nov.
Article em En | MEDLINE | ID: mdl-26112029
The Center for Expanded Data Annotation and Retrieval is studying the creation of comprehensive and expressive metadata for biomedical datasets to facilitate data discovery, data interpretation, and data reuse. We take advantage of emerging community-based standard templates for describing different kinds of biomedical datasets, and we investigate the use of computational techniques to help investigators to assemble templates and to fill in their values. We are creating a repository of metadata from which we plan to identify metadata patterns that will drive predictive data entry when filling in metadata templates. The metadata repository not only will capture annotations specified when experimental datasets are initially created, but also will incorporate links to the published literature, including secondary analyses and possible refinements or retractions of experimental interpretations. By working initially with the Human Immunology Project Consortium and the developers of the ImmPort data repository, we are developing and evaluating an end-to-end solution to the problems of metadata authoring and management that will generalize to other data-management environments.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Mineração de Dados / Conjuntos de Dados como Assunto Limite: Humans País como assunto: America do norte Idioma: En Ano de publicação: 2015 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Pesquisa Biomédica / Mineração de Dados / Conjuntos de Dados como Assunto Limite: Humans País como assunto: America do norte Idioma: En Ano de publicação: 2015 Tipo de documento: Article