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Part of: Synthesis digital library of engineering and computer science.

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Includes bibliographical references (p. 93-103).

Preface -- Acknowledgments --

1. Introduction -- 1.1 Database consistency -- 1.2 An appetizer and overview -- 1.3 Outlook --

2. The notions of repair and consistent answer -- 2.1 Preliminaries -- 2.2 Consistent data in inconsistent databases -- 2.3 Characterizing consistent data -- 2.4 What do we do then? -- 2.5 Some repair semantics -- 2.5.1 Tuple- and set-inclusion-based repairs -- 2.5.2 Tuple-deletion- and set-inclusion-based repairs -- 2.5.3 Tuple-insertion- and set-inclusion-based repairs -- 2.5.4 Null insertions-based repairs -- 2.5.5 Tuple- and cardinality-based repairs -- 2.5.6 Attribute-based repairs -- 2.5.7 Project-join repairs --

3. Tractable CQA and query rewriting -- 3.1 Residue-based rewriting -- 3.2 Extending query rewriting -- 3.3 Graphs, hypergraphs and repairs -- 3.4 Keys, trees, forests and roots --

4. Logically specifying repairs -- 4.1 Specifying repairs with logic programs -- 4.1.1 Disjunctive datalog with stable model semantics -- 4.1.2 Repair programs -- 4.1.3 Magic sets for repair programs -- 4.1.4 Logic programs and referential ICs -- 4.1.5 Null-based tuple insertions -- 4.2 Repairs in annotated predicate logic -- 4.3 Second-order representations --

5. Decision problems in CQA: complexity and algorithms -- 5.1 The decision problems -- 5.2 Some upper bounds -- 5.3 Some lower bounds -- 5.4 FO rewriting vs. PTIME and above -- 5.5 Combined decidability and complexity -- 5.6 Aggregation -- 5.7 Cardinality-based repairs -- 5.8 Attribute-based repairs -- 5.8.1 Denial constraints and numerical domains -- 5.8.2 Attribute-based repairs and aggregation constraints -- 5.9 Dynamic aspects, fixed-parameter tractability and comparisons --

6. Repairs and data cleaning -- 6.1 Data cleaning and query answering for FD violations -- 6.2 Repairs and data cleaning under uncertainty -- 6.2.1 Uncertain duplicate elimination -- 6.2.2 Uncertain repairing of FD violations --

Bibliography -- Author's biography.

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Integrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, a database may not satisfy those integrity constraints, and for that reason it is said to be inconsistent. However, and most likely a large portion of the database is still semantically correct, in a sense that has to be made precise. After having provided a formal characterization of consistent data in an inconsistent database, the natural problem emerges of extracting that semantically correct data, as query answers.

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Title from PDF t.p. (viewed on September 25, 2011).