By Leopoldo Bertossi, M. Tamer Ozsu
Integrity constraints are semantic stipulations database may still fulfill which will be a suitable version of exterior truth. In perform, and for plenty of purposes, a database would possibly not fulfill these integrity constraints, and accordingly it's stated to be inconsistent. even though, and probably, a wide section of the database remains to be semantically right, in a feeling that needs to be made unique. After having supplied a proper characterization of constant information in an inconsistent database, the common challenge emerges of extracting that semantically right info, as question solutions. The constant information in an inconsistent database is generally characterised because the information that persists throughout all of the database cases which are constant and minimally range from the inconsistent example. these are the so-called maintenance of the database. specifically, the constant solutions to a question posed to the inconsistent database are these solutions that may be concurrently got from the entire database maintenance. As anticipated, the suggestion of fix calls for an enough inspiration of distance that enables for the comparability of databases with admire to how a lot they range from the inconsistent example. in this foundation, the minimality on maintenance should be effectively formulated. during this monograph we current and talk about those basic thoughts, diverse fix semantics, algorithms for computing constant solutions to queries, and likewise complexity-theoretic effects concerning the computation of upkeep and doing constant question answering. desk of Contents: creation / The Notions of fix and constant solution / Tractable CQA and question Rewriting / Logically Specifying maintenance / selection difficulties in CQA: Complexity and Algorithms / maintenance and knowledge cleansing
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Extra resources for Database Repairing and Consistent Query Answering
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Bravo and Bertossi [2006] use a single null value for restoring consistency, and it behaves as an SQL NULL. This same repair semantics has been used in peer data exchange systems [Bertossi and Bravo, 2007]. Data are moved around at query answering time, and this process is driven by consistency restoration of inter-peer data exchange constraints. Both unknown and labeled nulls (from a collection N = {λ1 , λ2 , . }) are used by Molinaro and Greco [2010] to restore consistency wrt a restricted class of FDs and referential ICs.
There are natural and useful syntactic classes of queries and ICs for which T has these properties. We mention some of them here. For soundness, the following is a sufficient condition. 26 3. TRACTABLE CQA AND QUERY REWRITING 1. , logically equivalent to sentences in prenex normal form with only universal quantifiers. For example, functional dependencies, some inclusion dependencies without existential quantifiers, like ∀x(P (x) → Q(x)), ∀x∀y(R(x, y) → P (x)). 1. 2. , ∃xP (x, y), ∃x∀y(R(x, y) → S(x, y)).
With them, and trying to minimally change the given instance, we find only two possible alternative and consistent instances, namely: D1 Students StuNum 101 104 107 StuName john bell claire stevens pat norton D2 Students StuNum 101 104 107 StuName joe logan claire stevens pat norton These two instances are consistent wrt the FD, and they stay close to D. Now we observe that the tuple (104, claire stewens) persists in all repairs, which is not surprising since it does not participate in the violation of FD.