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Integrity constraints are semantic conditions that a database should satisfy in order to be an appropriate model of external reality. In practice, and for many reasons, a database may not satisfy those integrity constraints, and for that reason it is said to be inconsistent. However, and most likely, a large portion of the database is still semantically correct, in a sense that has to be made precise. After having provided a formal characterization of consistent data in an inconsistent database, the natural problem emerges of extracting that semantically correct data, as query answers. The consistent data in an inconsistent database is usually characterized as the data that persists across all the database instances that are consistent and minimally differ from the inconsistent instance. Those are the so-called repairs of the database. In particular, the consistent answers to a query posed to the inconsistent database are those answers that can be simultaneously obtained from all the database repairs. As expected, the notion of repair requires an adequate notion of distance that allows for the comparison of databases with respect to how much they differ from the inconsistent instance. On this basis, the minimality condition on repairs can be properly formulated. In this monograph we present and discuss these fundamental concepts, different repair semantics, algorithms for computing consistent answers to queries, and also complexity-theoretic results related to the computation of repairs and doing consistent query answering. Table of Contents: Introduction / The Notions of Repair and Consistent Answer / Tractable CQA and Query Rewriting / Logically Specifying Repairs / Decision Problems in CQA: Complexity and Algorithms / Repairs and Data Cleaning

Query compilation is the problem of translating user requests formulated over purely conceptual and domain specific ways of understanding data, commonly called logical designs, to efficient executable programs called query plans. Such plans access various concrete data sources through their low-level often iterator-based interfaces. An appreciation of the concrete data sources, their interfaces and how such capabilities relate to logical design is commonly called a physical design. This book is an introduction to the fundamental methods underlying database technology that solves the problem of query compilation. The methods are presented in terms of first-order logic which serves as the vehicle for specifying physical design, expressing user requests and query plans, and understanding how query plans implement user requests. Table of Contents: Introduction / Logical Design and User Queries / Basic Physical Design and Query Plans / On Practical Physical Design / Query Compilation and Plan Synthesis / Updating Data