K2/Kleisli and GUS: experiments in integrated access to genomic data sources

  • Authors:

  • S. B. Davidson;J. Crabtree;B. P. Brunk;J. Schug;V. Tannen;G. C. Overton;C. J. Stoeckert, Jr.

  • Affiliations:

  • Center for Bioinformatics and Department of Computer and Information Science, University of Pennsylvania, 200 South 33rd Street, Philadelphia, Pennsylvania;Center for Bioinformatics, University of Pennsylvania, 1315 Blockley Hall, Philadelphia, Pennsylvania;Center for Bioinformatics, University of Pennsylvania, 1316 Blockley Hall, Philadelphia, Pennsylvania;Center for Bioinformatics, University of Pennsylvania, 1315 Blockley Hall, Philadelphia, Pennsylvania;Department of Computer and Information Science, University of Pennsylvania, 200 South 33rd Street, Philadelphia, Pennsylvania;Center for Bioinformatics and Department of Genetics, University of Pennsylvania, 1312 Blockley Hall, Philadelphia, Pennsylvania;University of Pennsylvania, 1313 Blockley Hall, Philadelphia, Pennsylvania

  • Venue:
  • IBM Systems Journal - Deep computing for the life sciences
  • Year:
  • 2001

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Abstract

The integrated access to heterogeneous data sources is a major challenge for the biomedical community. Several solution strategies have been explored: link-driven federation of databases, view integration, and warehousing. In this paper we report on our experiences with two systems that were developed at the University of Pennsylvania: K2, a view integration implementation, and GUS, a data warehouse. Although the view integration and the warehouse approaches each have advantages, there is no clear "winner." Therefore, in selecting the best strategy for a particular application, users must consider the data characteristics, the performance guarantees required, and the programming resources available. Our experiences also point to some practical tips on how database updates should be published, and how XML can be used to facilitate the processing of updates in a warehousing environment.