Optimizing and implementing repair programs for consistent query answering in databases

Databases may not always satisfy their integrity constraints (ICs) and a number of different reasons can be held accountable for this. However, in most cases an important part of the data is still consistent with the ICs, and can still be retrieved through queries posed to the database. Consistent query answers are characterized as ordinary answers obtained from every minimally repaired and consistent version of the database. Database repairs wrt a wide class of ICs can be specified as stable models of disjunctive logic programs. Thus, Consistent Query Answering (CQA) for first-order queries is translated into cautious reasoning under the stable models semantics. The use of logic programs does not exceed the intrinsic complexity of CQA. However, using them in a straightforward manner is usually inefficient. The goal of this thesis is to develop optimized techniques to evaluate queries over inconsistent databases by using logic programs. More specifically, we optimize the structure of programs, model computation, and evaluation of queries from them. We develop a system which implements optimized logic programs and efficient methods to compute consistent answers to first-order queries. Moreover, we propose the use of the well-founded semantics (WFS) as an alternative way to obtain consistent answers. We show that for a certain class of queries and ICs, the well founded interpretation of a program retrieves the same consistent answers as the stable models semantics. The WFS has lower data complexity than the stable models semantics. We also extend the use of logic programs for retrieving consistent answers to aggregate queries, and we develop a repair semantics for Multidimensional Databases.

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