In this chapter, we summarize the research on querying inconsistent databases we have been conducting over the last five years. The formal framework we have used is based on two concepts: repair and consistent query answer. We describe different approaches to the issue of computing consistent query answers: query transformation, logic programming, inference in annotated logics, and specialized algorithms. We also characterize the computational complexity of this problem. Finally, we discuss related research in artificial intelligence, databases, and logic programming.

We address the problem of minimal-change integrity maintenance in the context of integrity constraints in relational databases. We assume that integrity-restoration actions are limited to tuple deletions. We focus on two basic computational issues: repair checking (is a database instance a repair of a given database?) and consistent query answers [3] (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 cases. We consider denial constraints, general functional and inclusion dependencies, as well as key and foreign key constraints. Our results shed 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. 1

We solve the problem of obtaining answers to queries posed to a mediated integration system under the local-as-view paradigm that are consistent wrt to certain global integrity constraints. For this, the query program is combined with logic programming specifications under the stable model semantics of the class of minimal global instances, and of

Many data integration systems provide transparent access to heterogeneous data sources through a unified view of all data in terms of a global schema, which may be equipped with integrity constraints on the data. Since these constraints might be violated by the data retrieved from the sources, methods for handling such a situation are needed. To this end, recent approaches model query answering in data integration systems in terms of nonmonotonic logic programs.

Consistent answers from a relational database that violates a given set of integrity constraints (ICs) are characterized as ordinary answers that can be obtained from every minimally repaired version of the database (a repair). Repairs can be specified and interpreted as the stable models of a simple disjunctive normal logic program with database predicates extended with appropriate annotation arguments. In consequence, consistent query answers can be obtained by running a query program in combination with the repair program under the cautious or skeptical stable model semantics. In this paper we show how to write repair programs for universal and referential ICs; we establish their correctness and show how to run them on top of the DLV system.

A relational database may not satisfy certain integrity constraints (ICs) for several reasons. However most likely most of the information in it is still consistent with the ICs. The answers to queries that are consistent with the ICs can be considered sematically correct answers, and are characterized [2] as ordinary answers that can be obtained from every minimally repaired version of the database. In this paper we address the problem of specifying those repaired versions as the minimal models of a theory written in Annotated Predicate Logic [27]. It is also shown how to specify database repairs using disjunctive logic program with annotation arguments and a classical stable model semantics.

When data sources are virtually integrated there is no common and centralized mechanism for maintaining global consistency. In consequHHj9 it is likely that inconsistencies with respect to certain global integrity constraints (ICs)will occu; In this chapter we consider the problem of defining andcompu2;) those answers that are consistent wrt the global ICs when global qubal) are posed tovirtuM data integration systems whosesou)33 are specified following the local-as-view approach.

Abstract. We study peer-to-peer data integration, where each peer models an autonomous system that exports data in terms of its own schema, and data interoperation is achieved by means of mappings among the peer schemas, rather than through a global schema. We propose a multi-modal epistemic semantics based on the idea that each peer is conceived as a rational agent that exchanges knowledge/belief with other peers, thus nicely modeling the modular structure of the system. We then address the issue of dealing with possible inconsistencies, and distinguish between two types of inconsistencies, called local and P2P, respectively. We define a nonmonotonic extension of our logic that is able to reason on the beliefs of peers under inconsistency tolerance. Tolerance to local inconsistency essentially means that the presence of inconsistency within one peer does not affect the consistency of the whole system. Tolerance to P2P inconsistency means being able to resolve inconsistencies arising from the interaction between peers. We study query answering and its data complexity in this setting, and we present an algorithm that is sound and complete with respect to the proposed semantics, and optimal with respect to worst-case complexity. 1

Abstract. The problem of answering queries posed to a peer who is a member of a peer-to-peer data exchange system is studied.The answers have to be consistent wrt to both the local semantic constraints and the data exchange constraints with other peers; and must also respect certain trust relationships between peers. A semantics for peer consistent answers under exchange constraints and trust relationships is introduced and some techniques for obtaining those answers are presented. 1

We address the problem of retrieving certain and consistent answers to queries posed to a mediated data integration system with open sources under the local-as-view paradigm using conjunctive and disjunctive view definitions. For obtaining certain answers a query program is run on top of a normal deductive database with choice that defines the class of minimal legal instances of the integration system under the cautious stable model semantics. This methodology works for all monotone Datalog queries. To compute answers to queries that are consistent wrt given global integrity constraints, the specification of minimal legal instances is combined with another disjunctive deductive database that specifies the repairs of those legal instances. This allows to retrieve the consistent answers to any Datalog query, for any set of universal and acyclic referential integrity constraints.