Data sharing through query translation in autonomous sources

  • Authors:
  • Anastasios Kementsietsidis;Marcelo Arenas

  • Affiliations:
  • Dept. of Computer Science, University of Toronto;Dept. of Computer Science, University of Toronto

  • Venue:
  • VLDB '04 Proceedings of the Thirtieth international conference on Very large data bases - Volume 30
  • Year:
  • 2004

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Abstract

We consider the problem of data sharing between autonomous data sources in an environment where constraints cannot be placed on the shared contents of sources. Our solutions rely on the use of mapping tables which define how data from different sources are associated. In this setting, the answer to a local query, that is, a query posed against the schema of a single source, is augmented by retrieving related data from associated sources. This retrieval of data is achieved by translating, through mapping tables, the local query into a set of queries that are executed against the associated sources. We consider both sound translations (which only retrieve correct answers) and complete translations (which retrieve all correct answers, and no incorrect answers) and we present algorithms to compute such translations. Our solutions are implemented and tested experimentally and we describe here our key findings.