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Abstract. We present the Consistency Extractor System (ConsEx) that uses answer set programming to compute consistent answers to first-order queries posed to relational databases that may be inconsistent wrt their integrity constraints. Among other features, ConsEx implements a magic sets technique to evaluate queries via disjunctive logic programs with stable model semantics that specify the repair of the original database. We describe the methodology and the system; and also present some experimental results. 1

Query answering from inconsistent databases amounts to finding “meaningful” answers to queries posed over database instances that do not satisfy integrity constraints specified over their schema. A declarative approach to this problem relies on the notion of repair, i.e., a database that satisfies integrity constraints and is obtained from the original inconsistent database by “minimally” adding and/or deleting tuples. Consistent answers to a user query are those answers that are in the evaluation of the query over each repair. Motivated by the fact that computing consistent answers from inconsistent databases is in general intractable, the present paper investigates techniques that allow to localize the difficult part of the computation on a small fragment of the database at hand, called “affected ” part. Based on a number of localization results, an approach to query answering from inconsistent data is presented, in which the query is evaluated over each of the repairs of the affected part only, augmented with the part that is not affected. Single query results are then suitably recombined. For some relevant classes of queries and constraints, techniques are also discussed to factorize repairs into components that can be processed independently of one another, thereby guaranteeing exponential gain w.r.t. the basic approach, which is not based on localization. The effectiveness of the results is demonstrated for consistent query answering over expressive schemas,

The problem of extracting consistent information from relational databases violating integrity constraints on numerical data is addressed. In particular, aggregate constraints defined as linear inequalities on aggregate-sum queries on input data are considered. The notion of repair as consistent set of updates at attribute-value level is exploited, and the characterization of several data-complexity issues related to repairing data and computing consistent query answers is provided. Moreover, a method for computing “reasonable ” repairs of inconsistent numerical databases is provided, for a restricted but expressive class of aggregate constraints. Several experiments are presented, which assess the effectiveness of the proposed approach in real-life application scenarios.

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

Abstract. We propose and investigate a semantics for peer data exchange systems (or peer data management systems) where different peers are pairwise related to each other by means of data exchange constraints and trust relationships. These two elements plus the data at the peers’ sites and the local integrity constraints for a peer are made compatible via the proposed semantics by determining a set of solution instances, which are the intended virtual instances for the peer. The semantically correct answers from a peer to a query, called its peer consistent answers, are defined as those answers that are invariant under all its different solution instances. We show that solution instances can be specified as the models of logic programs with a stable model semantics. 1

c ○ Copyright by Loreto Bravo, 2007 For several reasons a database may not satisfy certain integrity constraints (ICs), for example, when it is the result of integrating several independent data sources. However, most likely, information in it is still consistent with the ICs; and could be retrieved when queries are answered. Consistent answers with respect to a set of ICs have been characterized as answers that can be obtained from every possible minimal repair of the database. The goal of this research is to develop methods to retrieve consistent answers for a wide and practical class of constraints and queries from relational databases and from data integration systems. We will put special interest on databases with null values. We will give a semantics of satisfaction of constraints in the presence of null that generalizes the one used in commercial DBMS. Since there are interesting connections between the area of consistently querying virtual data integration systems and other areas, like querying incomplete databases, merging inconsistent theories, semantic reconciliation of data, schema mapping, data exchange, and query answering in peer data management systems, the results of this research could also be applied to them. In our research, we explore in more depth the connection with virtual data integration systems and peer data management systems. ii To my husband

Abstract. A Data Warehouse (DW) is a data repository that integrates data from multiple sources and organizes the data according to a set of data structures called dimensions. Each dimension provides a perspective upon which the data can be viewed. In order to support an efficient processing of queries, a dimension is usually required to satisfy different classes of integrity constraints. In this paper, we study the problem of repairing a dimension when it fails to satisfy a set of two classes of integrity constraints: strictness constraints andcovering constraints. We introduce the notion of minimal repair of a dimension in this context. A minimal repair is defined as a new dimension that is consistent with respect to the integrity constraints, which is obtained by applying a minimal amount of updatestotheoriginal dimension. Westudythecomplexityofcomputing minimal repairs. Finally, we show how to characterize and compute minimal repairs of a dimension using Datalog programs with stable model semantics. 1

The framework of consistent query answers and repairs has been introduced to alleviate the impact of inconsistent data on the answers to a query. A repair is a minimally different consistent instance and an answer is consistent if it is present in every repair. In this article we study the complexity of consistent query answers and repair checking in the presence of universal constraints. We propose an extended version of the conflict hypergraph which allows to capture all repairs w.r.t. a set of universal constraints. We show that repair checking is in PTIME for the class of full tuple-generating dependencies and denial constraints, and we present a polynomial repair algorithm. This algorithm is sound, i.e. always produces a repair, but also complete, i.e. every repair can be constructed. Next, we present a polynomial-time algorithm computing consistent answers to ground quantifier-free queries in the presence of denial constraints, join dependencies, and acyclic full-tuple generating dependencies. Finally, we show that extending the class of constraints leads to intractability. For arbitrary full tuple-generating dependencies consistent query answering becomes coNP-complete. For arbitrary universal constraints consistent query answering is Π p 2-complete and repair checking coNPcomplete. Key words: Inconsistent databases, consistent query answers, repair checking, database repairing. Preprint submitted to Information Systems 9 September 2008 1

Abstract. Consistent answers to a query from an inconsistent database are answers that can be simultaneously retrieved from every possible repair; and repairs are consistent instances that minimally differ from the original instance. Database repairs can be specified as the stable models of a disjunctive logic program. In this paper we show how to use the repair programs to transform the problem of consistent query answering into a problem of reasoning wrt a concrete theory written in second-order predicate logic. It also investigated how a first-order theory can be obtained instead, by applying second-order quantifier elimination techniques. 1