Muse: Mapping Understanding and deSign by Example

  • Authors:

  • Bogdan Alexe;Laura Chiticariu;Renee J. Miller;Wang-Chiew Tan

  • Affiliations:

  • University of California, Santa Cruz. abogdan@cs.ucsc.edu;University of California, Santa Cruz. laura@cs.ucsc.edu;University of Toronto. miller@cs.toronto.edu;University of California, Santa Cruz. wctan@cs.ucsc.edu

  • Venue:
  • ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
  • Year:
  • 2008

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Abstract

A fundamental problem in information integration is that of designing the relationships, called schema mappings, between two schemas. The specification of a semantically correct schema mapping is typically a complex task. Automated tools can suggest potential mappings, but few tools are available for helping a designer understand mappings and design alternative mappings. We describe Muse, a mapping design wizard that uses data examples to assist designers in understanding and refining a schema mapping towards the desired specification. We present novel algorithms behind Muse and show how Muse systematically guides the designer on two important components of a mapping design: the specification of the desired grouping semantics for sets of data and the choice among alternative interpretations for semantically ambiguous mappings. In every component, Muse infers the desired semantics based on the designer's actions on a short sequence of small examples. Whenever possible, Muse draws examples from a familiar database, thus facilitating the design process even further. We report our experience with Muse on some publicly available schemas.