Database repairing and consistent query answering
By: Leopoldo Bertossi
Series: Synthesis lectures on data management -- # 20
Publisher: Morgan & Claypool
Published: 2011
Place of publication: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA)
Language: eng
Format: [electronic resource] /
Number of pages: 105
ISBN-13: 9781608457632; 9781608457625
Subjects: Querying (Computer science); Database management; Maintenance and repair; Databases
Other titles: Synthesis digital library of engineering and computer science.
Description: 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.
Notes: Part of: Synthesis digital library of engineering and computer science.

Series from website.

Includes bibliographical references (p. 93-103).

Abstract freely available; full-text restricted to subscribers or individual document purchasers.

Also available in print.

Mode of access: World Wide Web.

System requirements: Adobe Acrobat Reader.
Table of contents: title: Preface; title: Acknowledgments; title: 1. Introduction; title: 1.1 Database consistency; title: 1.2 An appetizer and overview; title: 1.3 Outlook; title: 2. The notions of repair and consistent answer; title: 2.1 Preliminaries; title: 2.2 Consistent data in inconsistent databases; title: 2.3 Characterizing consistent data; title: 2.4 What do we do then?; title: 2.5 Some repair semantics; title: 2.5.1 Tuple- and set-inclusion-based repairs; title: 2.5.2 Tuple-deletion- and set-inclusion-based repairs; title: 2.5.3 Tuple-insertion- and set-inclusion-based repairs; title: 2.5.4 Null insertions-based repairs; title: 2.5.5 Tuple- and cardinality-based repairs; title: 2.5.6 Attribute-based repairs; title: 2.5.7 Project-join repairs; title: 3. Tractable CQA and query rewriting; title: 3.1 Residue-based rewriting; title: 3.2 Extending query rewriting; title: 3.3 Graphs, hypergraphs and repairs; title: 3.4 Keys, trees, forests and roots; title: 4. Logically specifying repairs; title: 4.1 Specifying repairs with logic programs; title: 4.1.1 Disjunctive datalog with stable model semantics; title: 4.1.2 Repair programs; title: 4.1.3 Magic sets for repair programs; title: 4.1.4 Logic programs and referential ICs; title: 4.1.5 Null-based tuple insertions; title: 4.2 Repairs in annotated predicate logic; title: 4.3 Second-order representations; title: 5. Decision problems in CQA: complexity and algorithms; title: 5.1 The decision problems; title: 5.2 Some upper bounds; title: 5.3 Some lower bounds; title: 5.4 FO rewriting vs. PTIME and above; title: 5.5 Combined decidability and complexity; title: 5.6 Aggregation; title: 5.7 Cardinality-based repairs; title: 5.8 Attribute-based repairs; title: 5.8.1 Denial constraints and numerical domains; title: 5.8.2 Attribute-based repairs and aggregation constraints; title: 5.9 Dynamic aspects, fixed-parameter tractability and comparisons; title: 6. Repairs and data cleaning; title: 6.1 Data cleaning and query answering for FD violations; title: 6.2 Repairs and data cleaning under uncertainty; title: 6.2.1 Uncertain duplicate elimination; title: 6.2.2 Uncertain repairing of FD violations; title: Bibliography; title: Author's biography.