A unified software framework for deriving, visualizing, and exploring abstraction networks for ontologies

Christopher Ochs, James Geller, Yehoshua Perl, Mark A. Musen

Research output: Contribution to journalArticlepeer-review

18 Scopus citations

Abstract

Software tools play a critical role in the development and maintenance of biomedical ontologies. One important task that is difficult without software tools is ontology quality assurance. In previous work, we have introduced different kinds of abstraction networks to provide a theoretical foundation for ontology quality assurance tools. Abstraction networks summarize the structure and content of ontologies. One kind of abstraction network that we have used repeatedly to support ontology quality assurance is the partial-area taxonomy. It summarizes structurally and semantically similar concepts within an ontology. However, the use of partial-area taxonomies was ad hoc and not generalizable. In this paper, we describe the Ontology Abstraction Framework (OAF), a unified framework and software system for deriving, visualizing, and exploring partial-area taxonomy abstraction networks. The OAF includes support for various ontology representations (e.g., OWL and SNOMED CT's relational format). A Protégé plugin for deriving "live partial-area taxonomies" is demonstrated.

Original languageEnglish (US)
Pages (from-to)90-105
Number of pages16
JournalJournal of Biomedical Informatics
Volume62
DOIs
StatePublished - Aug 1 2016

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Health Informatics

Keywords

  • Abstraction network derivation
  • Ontology exploration
  • Ontology summarization
  • Ontology tools
  • Visualization of ontology content

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