Foundations of uncertain-data integration

  • Authors:

  • Parag Agrawal;Anish Das Sarma;Jeffrey Ullman;Jennifer Widom

  • Affiliations:

  • Stanford University;Yahoo! Research;Stanford University;Stanford University

  • Venue:
  • Proceedings of the VLDB Endowment
  • Year:
  • 2010

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Abstract

There has been considerable past work studying data integration and uncertain data in isolation. We develop the foundations for local-as-view (LAV) data integration when the sources being integrated are uncertain. We motivate two distinct settings for uncertain-data integration. We then define containment of uncertain databases in these settings, which allows us to express uncertain sources as views over a virtual mediated uncertain database. Next, we define consistency of a set of uncertain sources and show intractability of consistency-checking. We identify an interesting special case for which consistency-checking is polynomial. Finally, the notion of certain answers from traditional LAV data integration does not generalize to the uncertain setting, so we define a corresponding notion of correct answers.