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This article is part of the supplement: Proceedings of Ontologies in Biomedicine and Life Sciences (OBML 2011)

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OntoCheck: verifying ontology naming conventions and metadata completeness in Protégé 4

Daniel Schober1*, Ilinca Tudose1, Vojtech Svatek2 and Martin Boeker1

Author Affiliations

1 Institute of Medical Biometry and Medical Informatics (IMBI), University Medical Center, 79104 Freiburg, Germany

2 University of Economics, Prague, Nám. W. Churchilla 4, 130 67 Praha 3, Czech Republic

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Journal of Biomedical Semantics 2012, 3(Suppl 2):S4  doi:10.1186/2041-1480-3-S2-S4

Published: 21 September 2012

Abstract

Background

Although policy providers have outlined minimal metadata guidelines and naming conventions, ontologies of today still display inter- and intra-ontology heterogeneities in class labelling schemes and metadata completeness. This fact is at least partially due to missing or inappropriate tools. Software support can ease this situation and contribute to overall ontology consistency and quality by helping to enforce such conventions.

Objective

We provide a plugin for the Protégé Ontology editor to allow for easy checks on compliance towards ontology naming conventions and metadata completeness, as well as curation in case of found violations.

Implementation

In a requirement analysis, derived from a prior standardization approach carried out within the OBO Foundry, we investigate the needed capabilities for software tools to check, curate and maintain class naming conventions. A Protégé tab plugin was implemented accordingly using the Protégé 4.1 libraries. The plugin was tested on six different ontologies. Based on these test results, the plugin could be refined, also by the integration of new functionalities.

Results

The new Protégé plugin, OntoCheck, allows for ontology tests to be carried out on OWL ontologies. In particular the OntoCheck plugin helps to clean up an ontology with regard to lexical heterogeneity, i.e. enforcing naming conventions and metadata completeness, meeting most of the requirements outlined for such a tool. Found test violations can be corrected to foster consistency in entity naming and meta-annotation within an artefact. Once specified, check constraints like name patterns can be stored and exchanged for later re-use. Here we describe a first version of the software, illustrate its capabilities and use within running ontology development efforts and briefly outline improvements resulting from its application. Further, we discuss OntoChecks capabilities in the context of related tools and highlight potential future expansions.

Conclusions

The OntoCheck plugin facilitates labelling error detection and curation, contributing to lexical quality assurance in OWL ontologies. Ultimately, we hope this Protégé extension will ease ontology alignments as well as lexical post-processing of annotated data and hence can increase overall secondary data usage by humans and computers.