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

Document Type

Article

Publication Date

8-1-2016

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.

Identifier

84976897918 (Scopus)

Publication Title

Journal of Biomedical Informatics

External Full Text Location

https://doi.org/10.1016/j.jbi.2016.06.008

ISSN

15320464

PubMed ID

27345947

First Page

90

Last Page

105

Volume

62

Grant

R01CA190779

Fund Ref

National Institutes of Health

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