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This article is part of the supplement: Proceedings of Ontologies in Biomedicine and Life Sciences (OBML 2010)

Open Access Proceedings

Anatomy ontologies and potential users: bridging the gap

Ravensara S Travillian1*, Tomasz Adamusiak1, Tony Burdett1, Michael Gruenberger2, John Hancock3, Ann-Marie Mallon3, James Malone1, Paul Schofield2 and Helen Parkinson1

Author Affiliations

1 EMBL-EBI, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SD, UK

2 Department of Physiology, Development, and Neuroscience, University of Cambridge, Downing Street, Cambridge CB2 3DY, UK

3 MRC Mammalian Genetics Unit, Harwell, Oxfordshire OX11 0RD, UK

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Journal of Biomedical Semantics 2011, 2(Suppl 4):S3  doi:10.1186/2041-1480-2-S4-S3

Published: 9 August 2011

Abstract

Motivation

To evaluate how well current anatomical ontologies fit the way real-world users apply anatomy terms in their data annotations.

Methods

Annotations from three diverse multi-species public-domain datasets provided a set of use cases for matching anatomical terms in two major anatomical ontologies (the Foundational Model of Anatomy and Uberon), using two lexical-matching applications (Zooma and Ontology Mapper).

Results

Approximately 1500 terms were identified; Uberon/Zooma mappings provided 286 matches, compared to the control and Ontology Mapper returned 319 matches. For the Foundational Model of Anatomy, Zooma returned 312 matches, and Ontology Mapper returned 397.

Conclusions

Our results indicate that for our datasets the anatomical entities or concepts are embedded in user-generated complex terms, and while lexical mapping works, anatomy ontologies do not provide the majority of terms users supply when annotating data. Provision of searchable cross-products for compositional terms is a key requirement for using ontologies.