Chapter

Resource Discovery

Volume 6799 of the series Lecture Notes in Computer Science pp 57-70

Semantic Map for Structural Bioinformatics: Enhanced Service Discovery Based on High Level Concept Ontology

  • Edouard StrauserAffiliated withMTi, INSERM UMR-S 973, Université Paris Diderot (Paris 7)RPBS, Université Paris Diderot (Paris 7)
  • , Mikaël NaveauAffiliated withMTi, INSERM UMR-S 973, Université Paris Diderot (Paris 7)RPBS, Université Paris Diderot (Paris 7)
  • , Hervé MénagerAffiliated withInstitut Pasteur
  • , Julien MaupetitAffiliated withMTi, INSERM UMR-S 973, Université Paris Diderot (Paris 7)RPBS, Université Paris Diderot (Paris 7)
  • , Zoé LacroixAffiliated withArizona State University
  • , Pierre TufféryAffiliated withMTi, INSERM UMR-S 973, Université Paris Diderot (Paris 7)RPBS, Université Paris Diderot (Paris 7)

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Abstract

The amount of bioinformatics services available over the web has dramatically increased over the last years. Generalist on-line catalogs help identifying a particular service in such a pool. Unfortunately, most of the time, querying those catalogs is only based on a textual search for a particular datatype or a domain of interest. In this context, we have developed the Structural Bioinformatics Semantic Map (SBMap), a dual level ontology that allows users to discover structural bioinformatics resources through the exploration of a graph of high level concepts. In this paper, we present how participative design workshops helped us to improve the navigation experiment. The SBMap discovery tool (release-candidate) is available at: http://sbmap.rpbs.univ-paris-diderot.fr