A logical framework for querying and repairing inconsistent databases

Greco, Gianluigi; Greco, Sergio; Zumpano, Ester

doi:10.1109/tkde.2003.1245280

Cited by 136 publications

(99 citation statements)

References 30 publications

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“…In [3,20,5,6] a different approach is taken: database repairs are specified as the stable models of disjunctive logic programs, and in consequence consistent query answering amounts to doing cautious or certain reasoning from logic programs under the stable model semantics. In this way, it is possible to handle any set of universal ICs and any first-order query, and even beyond that, e.g.…”

Section: Introductionmentioning

confidence: 99%

Semantically Correct Query Answers in the Presence of Null Values

Bravo

Bertossi

2006

Current Trends in Database Technology – EDBT 2006

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Abstract. For several reasons a database may not satisfy a given set of integrity constraints (ICs), but most likely most of the information in it is still consistent with those ICs; and could be retrieved when queries are answered. Consistent answers to queries wrt a set of ICs have been characterized as answers that can be obtained from every possible minimally repaired consistent version of the original database. In this paper we consider databases that contain null values and are also repaired, if necessary, using null values. For this purpose, we propose first a precise semantics for IC satisfaction in a database with null values that is compatible with the way null values are treated in commercial database management systems. Next, a precise notion of repair is introduced that privileges the introduction of null values when repairing foreign key constraints, in such a way that these new values do not create an infinite cycle of new inconsistencies. Finally, we analyze how to specify this kind of repairs of a database that contains null values using disjunctive logic programs with stable model semantics.

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Section: Introductionmentioning

confidence: 99%

Semantically Correct Query Answers in the Presence of Null Values

Bravo

Bertossi

2006

Current Trends in Database Technology – EDBT 2006

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“…Actually, they first and naturally emerged when logic programs were used to specify the repairs, with the idea of query this compact specification of repairs in order to obtain the consistent answers. In several papers [5,8,9,15,16,32,43], database repairs were specified as the stable models of disjunctive logic programs with stable model semantics [40] (aka. answer set programs).…”

Section: Student Id Name 1 Peter 2 Jonesmentioning

confidence: 99%

The consistency extractor system: Answer set programs for consistent query answering in databases

Caniupan

Bertossi

2010

Data & Knowledge Engineering

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We describe the Consistency Extractor System (ConsEx) that computes consistent answers to Datalog queries with negation posed to relational databases that may be inconsistent with respect to certain integrity constraints. In order to solve this task, ConsEx uses answers set programming. More precisely, ConsEx uses disjunctive logic programs with stable models semantics to specify and reason with the repairs, i.e. with the consistent virtual instances that minimally depart from the original database. The consistent information is invariant under all repairs. ConsEx achieves efficient query evaluation by implementing magic sets techniques. We describe the general methodology, its optimizations for query answering, and the architecture of the system. We also present encouraging experimental results.

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“…In the framework of Arenas, Bertossi and Chomicki [4], which was adapted by the follow-up papers [5,6,7,8,9,11,12,19,21,25,26,34,41,45,46,49,62], the smallest unit to be deleted from (or added to) a database in the process of repairing is a tuple. A different choice is made by Wijsen [64] where tuples themselves are being repaired.…”

Section: Repairing By Attribute Modificationmentioning

confidence: 99%

“…The problem of computing consistent query answers is the second computational problem studied in the present paper. The notion of consistent query answer proposed by Arenas, Bertossi and Chomicki [4] has been used and extended in many papers [5,6,7,8,9,11,12,16,19,20,21,25,26,27,34,41,45,46,49,62,64]. This research has been surveyed by Bertossi and Chomicki [13].…”

Section: Introductionmentioning

confidence: 99%

On the Computational Complexity of Minimal-Change Integrity Maintenance in Relational Databases

Chomicki

Marcinkowski

2005

Inconsistency Tolerance

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Abstract. We address the problem of minimal-change integrity maintenance in the context of integrity constraints in relational databases. Using the framework proposed by Arenas, Bertossi, and Chomicki [4], we focus on two basic computational issues: repair checking (is a database instance a repair of a given database?) and consistent query answers (is a tuple an answer to a given query in every repair of a given database?). We study the computational complexity of both problems, delineating the boundary between the tractable and the intractable. We review relevant semantical issues and survey different computational mechanisms proposed in this context. Our analysis sheds light on the computational feasibility of minimal-change integrity maintenance. The tractable cases should lead to practical implementations. The intractability results highlight the inherent limitations of any integrity enforcement mechanism, e.g., triggers or referential constraint actions, as a way of performing minimal-change integrity maintenance.

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A logical framework for querying and repairing inconsistent databases

Cited by 136 publications

References 30 publications

Semantically Correct Query Answers in the Presence of Null Values

Semantically Correct Query Answers in the Presence of Null Values

The consistency extractor system: Answer set programs for consistent query answering in databases

On the Computational Complexity of Minimal-Change Integrity Maintenance in Relational Databases

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