BioRegistry: Automatic extraction of metadata for biological database retrieval and discovery

Authors:
Marie-Dominique Devignes;Philippe Franiatte;Nizar Messai;Emmanuel Bresso;Amedeo Napoli;Malika Smail-Tabbone
Affiliations:
LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France.;LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France.;LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France.;LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France.;LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France.;LORIA UMR 7503, CNRS, INRIA Nancy Grand-Est, Nancy-Universite, 615, rue du Jardin Botanique, 54600 Villers-les-Nancy, France
Venue:
International Journal of Metadata, Semantics and Ontologies
Year:
2010

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Abstract

The need for a well-maintained searchable directory is an important issue with regard to the numerous biological databases produced by genomic and post-genomic research. The BioRegistry repository aims to associate content metadata belonging to a biomedical thesaurus with biological databases in view of retrieval or discovery. It is automatically generated from a publicly available list of biological databases. The querying modalities include a search by semantic similarity. The system performance is evaluated in terms of precision and recall on a collection test. A classification method is proposed for browsing and discovering databases through the BioRegistry.