Logic Programming And Databases

The topic of logic programming and databases. has gained in creasing interest in recent years. Several events have marked the rapid evolution of this field: the selection, by the Japanese Fifth Generation Project, of Prolog and of the relational data model as the basis for the development of new machine archi tectures; the focusing of research in database theory on logic queries and on recursive query processing; and the pragmatic, application-oriented development of expert database systems and of knowledge-base systems. As a result, an enormous amount of work has been produced in the recent literature, coupled with the spontaneous growth of several advanced projects in this area. The goal of this book is to present a systematic overview of a rapidly evolving discipline, which is presently not described with the same approach in other books. We intend to introduce stu dents and researchers to this new discipline; thus we use a plain, tutorial style, and complement the description of algorithms with examples and exercises. We attempt to achieve a balance be tween theoretical foundations and technological issues; thus we present a careful introduction to the new language Datalog, but we also focus on the efficient interfacing of logic programming formalisms (such as Prolog and Datalog) with large databases.

Time is ubiquitous in information systems. Almost every enterprise faces the problem of its data becoming out of date. However, such data is often valu able, so it should be archived and some means to access it should be provided. Also, some data may be inherently historical, e.g., medical, cadastral, or ju dicial records. Temporal databases provide a uniform and systematic way of dealing with historical data. Many languages have been proposed for tem poral databases, among others temporal logic. Temporal logic combines ab stract, formal semantics with the amenability to efficient implementation. This chapter shows how temporal logic can be used in temporal database applica tions. Rather than presenting new results, we report on recent developments and survey the field in a systematic way using a unified formal framework [GHR94; Ch094]. The handbook [GHR94] is a comprehensive reference on mathematical foundations of temporal logic. In this chapter we study how temporal logic is used as a query and integrity constraint language. Consequently, model-theoretic notions, particularly for mula satisfaction, are of primary interest. Axiomatic systems and proof meth ods for temporal logic [GHR94] have found so far relatively few applications in the context of information systems. Moreover, one needs to bear in mind that for the standard linearly-ordered time domains temporal logic is not re cursively axiomatizable [GHR94]' so recursive axiomatizations are by necessity incomplete.

Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming. The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs. The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.

Foundations of Deductive Databases and Logic Programming focuses on the foundational issues concerning deductive databases and logic programming. The selection first elaborates on negation in logic programming and towards a theory of declarative knowledge. Discussions focus on model theory of stratified programs, fixed point theory of nonmonotonic operators, stratified programs, semantics for negation in terms of special classes of models, relation between closed world assumption and the completed database, negation as a failure, and closed world assumption. The book then takes a look at negation as failure using tight derivations for general logic programs, declarative semantics of logic programs with negation, and declarative semantics of deductive databases and logic programs. The publication tackles converting AND-control to OR-control by program transformation, optimizing dialog, equivalences of logic programs, unification, and logic programming and parallel complexity. Topics include parallelism and structured and unstructured data, parallel algorithms and complexity, solving equations, most general unifiers, systems of equations and inequations, equivalences of logic programs, and optimizing recursive programs. The selection is a valuable source of data for researchers interested in pursuing further studies on the foundations of deductive databases and logic programming.

The use of logic in databases started in the late 1960s. In the early 1970s Codd formalized databases in terms of the relational calculus and the relational algebra. A major influence on the use of logic in databases was the development of the field of logic programming. Logic provides a convenient formalism for studying classical database problems and has the important property of being declarative, that is, it allows one to express what she wants rather than how to get it. For a long time, relational calculus and algebra were considered the relational database languages. However, there are simple operations, such as computing the transitive closure of a graph, which cannot be expressed with these languages. Datalog is a declarative query language for relational databases based on the logic programming paradigm. One of the peculiarities that distinguishes Datalog from query languages like relational algebra and calculus is recursion, which gives Datalog the capability to express queries like computing a graph transitive closure. Recent years have witnessed a revival of interest in Datalog in a variety of emerging application domains such as data integration, information extraction, networking, program analysis, security, cloud computing, ontology reasoning, and many others. The aim of this book is to present the basics of Datalog, some of its extensions, and recent applications to different domains.

The premise behind developing powerful declarative database languages is compelling: by enabling users to specify their queries (and their integrity constraints) in a clear, non-operational way, they make the user's task easier, and provide the database system with more opportunities for optimization. Relational database systems offer a striking proof that this premise is indeed valid. The most popular relational query language, SQL, is based upon relational algebra and calculus, i.e., a small fragment of first-order logic, and the ease of writing queries in SQL (in comparison to more navigational languages) has been an important factor in the commercial success of relational databases. It is well-known that SQL has some important limitations, in spite of its success and popUlarity. Notably, the query language is non-recursive, and support for integrity constraints is limited. Indeed, recognizing these problems, the latest standard, SQL-92, provides increased support for integrity constraints, and it is anticipated that the successor to the SQL-92 standard, called SQL3, RECURSIVE UNION operation [1]. Logic database systems have will include a concentrated on these extensions to the relational database paradigm, and some systems (e.g., Bull's DEL prototype) have even incorporated object-oriented features (another extension likely to appear in SQL3).

This book constitutes the thoroughly refereed and revised post-workshop proceedings of two international meetings devoted to deductive databases and logic programming. The technical papers presenting original research results were carefully reviewed and selected for inclusion in the present book, together with several survey articles summarizing the state of the art in the area. Thus, the book is the ultimate reference for anybody interested in the theory and application of deductive databases and logic programming.

Logic and databases are inextricably intertwined. The relational model in particular is essentially just elementary predicate logic, tailored to fit the needs of database management. Now, if you're a database professional, I'm sure this isn't news to you; but you still might not realize just how much everything we do in the database world is - or should be! - affected by predicate logic. Logic is everywhere. So if you're a database professional you really owe it to yourself to understand the basics of formal logic, and you really ought to be able to explain (and perhaps defend) the connections between formal logic and database management. And that's what this book is about. What it does is show, through a series of partly independent and partly interrelate essays, just how various crucial aspects of database technology-some of them very familiar, others maybe less so- are solidly grounded in formal logic. It is divided into five parts: *Basic Logic *Logic and Database Management *Logic and Database Design *Logic and Algebra *Logic and the Third Manifesto There's also a lengthy appendix, containing a collection of frequently asked questions (and some answers) on various aspects of logic and database management. Overall, my goal is to help you realize the importance of logic in everything you do, and also- I hope- to help you see that logic can be fun.