BMC Bioinformatics (Apr 2009)

Survey-based naming conventions for use in OBO Foundry ontology development

  • Mungall Chris,
  • Lomax Jane,
  • Kusnierczyk Waclaw,
  • Lewis Suzanna E,
  • Smith Barry,
  • Schober Daniel,
  • Taylor Chris F,
  • Rocca-Serra Philippe,
  • Sansone Susanna-Assunta

DOI
https://doi.org/10.1186/1471-2105-10-125
Journal volume & issue
Vol. 10, no. 1
p. 125

Abstract

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Abstract Background A wide variety of ontologies relevant to the biological and medical domains are available through the OBO Foundry portal, and their number is growing rapidly. Integration of these ontologies, while requiring considerable effort, is extremely desirable. However, heterogeneities in format and style pose serious obstacles to such integration. In particular, inconsistencies in naming conventions can impair the readability and navigability of ontology class hierarchies, and hinder their alignment and integration. While other sources of diversity are tremendously complex and challenging, agreeing a set of common naming conventions is an achievable goal, particularly if those conventions are based on lessons drawn from pooled practical experience and surveys of community opinion. Results We summarize a review of existing naming conventions and highlight certain disadvantages with respect to general applicability in the biological domain. We also present the results of a survey carried out to establish which naming conventions are currently employed by OBO Foundry ontologies and to determine what their special requirements regarding the naming of entities might be. Lastly, we propose an initial set of typographic, syntactic and semantic conventions for labelling classes in OBO Foundry ontologies. Conclusion Adherence to common naming conventions is more than just a matter of aesthetics. Such conventions provide guidance to ontology creators, help developers avoid flaws and inaccuracies when editing, and especially when interlinking, ontologies. Common naming conventions will also assist consumers of ontologies to more readily understand what meanings were intended by the authors of ontologies used in annotating bodies of data.