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This article is part of the supplement: Semantic Web Applications and Tools for Life Sciences (SWAT4LS), 2009

Open Access Highly Accessed Research

Mapping between the OBO and OWL ontology languages

Syed Hamid Tirmizi1*, Stuart Aitken23, Dilvan A Moreira4, Chris Mungall5, Juan Sequeda1, Nigam H Shah6 and Daniel P Miranker17

Author Affiliations

1 Department of Computer Science, The University of Texas at Austin, Austin, Texas 78701, USA

2 Artificial Intelligence Applications Institute, The University of Edinburgh, Edinburgh EH8 9LE, UK

3 Informatics Life-Sciences Institute, The University of Edinburgh, Edinburgh EH8 9LE, UK

4 Department of Computer Science, Mathematics and Computing Institute, University of São Paulo, São Carlos, São Paulo, Brazil

5 Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA

6 Center for Biomedical Informatics Research, School of Medicine, Stanford University, Stanford, California 94305, USA

7 Institute for Cell and Molecular Biology, The University of Texas at Austin, Austin, Texas 78701, USA

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Journal of Biomedical Semantics 2011, 2(Suppl 1):S3  doi:10.1186/2041-1480-2-S1-S3

Published: 7 March 2011

Abstract

Background

Ontologies are commonly used in biomedicine to organize concepts to describe domains such as anatomies, environments, experiment, taxonomies etc. NCBO BioPortal currently hosts about 180 different biomedical ontologies. These ontologies have been mainly expressed in either the Open Biomedical Ontology (OBO) format or the Web Ontology Language (OWL). OBO emerged from the Gene Ontology, and supports most of the biomedical ontology content. In comparison, OWL is a Semantic Web language, and is supported by the World Wide Web consortium together with integral query languages, rule languages and distributed infrastructure for information interchange. These features are highly desirable for the OBO content as well. A convenient method for leveraging these features for OBO ontologies is by transforming OBO ontologies to OWL.

Results

We have developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web itself to guide the work. The approach reveals that the constructs of OBO can be grouped together to form a similar layer cake. Thus we were able to decompose the problem into two parts. Most OBO constructs have easy and obvious equivalence to a construct in OWL. A small subset of OBO constructs requires deeper consideration. We have defined transformations for all constructs in an effort to foster a standard common mapping between OBO and OWL. Our mapping produces OWL-DL, a Description Logics based subset of OWL with desirable computational properties for efficiency and correctness. Our Java implementation of the mapping is part of the official Gene Ontology project source.

Conclusions

Our transformation system provides a lossless roundtrip mapping for OBO ontologies, i.e. an OBO ontology may be translated to OWL and back without loss of knowledge. In addition, it provides a roadmap for bridging the gap between the two ontology languages in order to enable the use of ontology content in a language independent manner.