Foundations of uncertain-data integration
Author(s) -
Parag Agrawal,
Anish Das Sarma,
Jeffrey D. Ullman,
Jennifer Widom
Publication year - 2010
Publication title -
proceedings of the vldb endowment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.946
H-Index - 134
ISSN - 2150-8097
DOI - 10.14778/1920841.1920976
Subject(s) - consistency (knowledge bases) , uncertain data , data integration , isolation (microbiology) , computer science , set (abstract data type) , data integrity , data consistency , weak consistency , theoretical computer science , data mining , mathematics , strong consistency , artificial intelligence , database , programming language , microbiology and biotechnology , biology , statistics , estimator
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.
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