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Preserving mapping consistency under schema changes

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Abstract.

In dynamic environments like the Web, data sources may change not only their data but also their schemas, their semantics, and their query capabilities. When a mapping is left inconsistent by a schema change, it has to be detected and updated. We present a novel framework and a tool (ToMAS) for automatically adapting (rewriting) mappings as schemas evolve. Our approach considers not only local changes to a schema but also changes that may affect and transform many components of a schema. Our algorithm detects mappings affected by structural or constraint changes and generates all the rewritings that are consistent with the semantics of the changed schemas. Our approach explicitly models mapping choices made by a user and maintains these choices, whenever possible, as the schemas and mappings evolve. When there is more than one candidate rewriting, the algorithm may rank them based on how close they are to the semantics of the existing mappings.

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Authors and Affiliations

  1. University of Toronto, 40 St. George Str., Toronto, ON, Canada

    Yannis Velegrakis & Renée J. Miller

  2. IBM Almaden Research Center, 650 Harry Road, 95120, San Jose, CA, USA

    Lucian Popa

Authors
  1. Yannis Velegrakis
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  2. Renée J. Miller
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  3. Lucian Popa
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Corresponding author

Correspondence to Yannis Velegrakis.

Additional information

Received: 13 January 2004, Accepted: 26 March 2004, Published online: 12 August 2004

Edited by: M. Carey

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Velegrakis, Y., Miller, R.J. & Popa, L. Preserving mapping consistency under schema changes. VLDB 13, 274–293 (2004). https://doi.org/10.1007/s00778-004-0136-2

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  • DOI: https://doi.org/10.1007/s00778-004-0136-2

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