Syntactic and semantic metadata integration for science data use

  • Authors:

  • Sunil Movva;Rahul Ramachandran;Xiang Li;Sarita Khaire;Ken Keiser;Helen Conover;Sara Graves

  • Affiliations:

  • Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA;Information Technology and Systems Center, University of Alabama in Huntsville, Huntsville, AL-38599, USA

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2005

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Abstract

This paper proposes a novel metadata solution to allow applications to intelligently use science data in an automated fashion. The solution provides rich syntactic and semantic metadata, where the semantic metadata is linked with an ontology to define the semantic terms. This solution allows applications to exploit the syntactic metadata to read the data and the semantic metadata to infer the content and the meaning of the data. The solution presented in this paper leverages the Earth Science Markup Language for providing the syntactic metadata and adds a semantic metadata component along with links to the appropriate ontology. This new semantic component is orthogonal to the syntactic metadata, so it does not perturb the existing design. An example application was designed and built that integrates this syntactic and semantic metadata via an ontology to perform a data processing operation.