Your browser doesn't support javascript.
loading
An empirical analysis of ontology reuse in BioPortal.
Ochs, Christopher; Perl, Yehoshua; Geller, James; Arabandi, Sivaram; Tudorache, Tania; Musen, Mark A.
Afiliação
  • Ochs C; Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA. Electronic address: cro3@njit.edu.
  • Perl Y; Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
  • Geller J; Computer Science Department, New Jersey Institute of Technology, Newark, NJ 07102, USA.
  • Arabandi S; ONTOPRO, Houston, TX, USA.
  • Tudorache T; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA.
  • Musen MA; Stanford Center for Biomedical Informatics Research, Stanford University, Stanford, CA 94305, USA.
J Biomed Inform ; 71: 165-177, 2017 07.
Article em En | MEDLINE | ID: mdl-28583809
Biomedical ontologies often reuse content (i.e., classes and properties) from other ontologies. Content reuse enables a consistent representation of a domain and reusing content can save an ontology author significant time and effort. Prior studies have investigated the existence of reused terms among the ontologies in the NCBO BioPortal, but as of yet there has not been a study investigating how the ontologies in BioPortal utilize reused content in the modeling of their own content. In this study we investigate how 355 ontologies hosted in the NCBO BioPortal reuse content from other ontologies for the purposes of creating new ontology content. We identified 197 ontologies that reuse content. Among these ontologies, 108 utilize reused classes in the modeling of their own classes and 116 utilize reused properties in class restrictions. Current utilization of reuse and quality issues related to reuse are discussed.
Assuntos
Palavras-chave

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Vocabulário Controlado / Ontologias Biológicas Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Software / Vocabulário Controlado / Ontologias Biológicas Idioma: En Revista: J Biomed Inform Assunto da revista: INFORMATICA MEDICA Ano de publicação: 2017 Tipo de documento: Article