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

ABSTRACT

Biological databases are blooming today at an increasing rate to deal with the huge amount of data produced by genomic and post-genomic research. The need for a well-maintained searchable directory is therefore an important issue for a good exploitation of these databases. The BioRegistry repository is automatically generated from a publicly available list of biological databases (The Molecular Biology Database Collection published in Nucleic Acids Research) and aims at associating content metadata with each database in view of database retrieval and/or discovery. Such content metadata are either simple keywords or terms belonging to a medical thesaurus. Querying modalities including a search by semantic similarity are described. The use of conceptual clustering methods is proposed to build a semantic classification of biological databases enabling browsing through the BioRegistry repository and discovering previously unknown databases.

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INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.7 Digital Libraries
          Subjects: Collection

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.7 Digital Libraries
          Subjects: User issues

General Terms:
Design, Documentation

Keywords:
biological databases, conceptual clustering, metadata, resource discovery