z-logo
open-access-imgOpen Access
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.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom