Logics For Databases And Information Systems

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 Almost every enterprise faces the problem of its data becoming out of date.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.

In this era of heterogeneous and distributed data sources, ranging from semistructured documents to knowledge about coordination processes or workflows, logic provides a rich set of tools and techniques with which to address the questions of how to represent, query and reason about complex data. This book provides a state-of-the-art overview of research on the application of logic-based methods to information systems, covering highly topical and emerging fields: XML programming and querying, intelligent agents, workflow modeling and verification, data integration, temporal and dynamic information, data mining, authorization, and security. It provides both scientists and graduate students with a wealth of material and references for their own research and education.

In the past, applied artificial intelligence systems were built with particular emphasis on general reasoning methods intended to function efficiently, even when only relatively little domain-specific knowledge was available. In other words, AI technology aimed at the processing of knowledge stored under comparatively general representation schemes. Nowadays, the focus has been redirected to the role played by specific and detailed knowledge, rather than to the reasoning methods themselves. Many new application systems are centered around knowledge bases, i. e. , they are based on large collections offacts, rules, and heuristics that cap ture knowledge about a specific domain of applications. Experience has shown that when used in combination with rich knowledge bases, even simple reasoning methods can be extremely effective in a wide variety of problem domains. Knowledge base construction and management will thus become the key factor in the development of viable knowledge-based ap plications. Knowledge Base Management Systems (KBMSs) are being proposed that provide user-friendly environments for the construction, retrieval, and manipUlation of large shared knowledge bases. In addition to deductive reasoning, KBMSs require operational characteristics such as concurrent access, integrity maintenance, error recovery, security, and perhaps distribution. For the development ofKBMSs, the need to integrate concepts and technologies from different areas, such as Artificial Intel ligence, Databases, and Logic, has been widely recognized. One of the central issues for KBMSs is the framework used for knowledge representation-semantic networks, frames, rules, and logics are proposed by the AI and logic communities.

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.

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.

If we look back to pre-database systems and the data units which were in use, we will establish a hierarchy starting with the concept of 'field' used to build 'records' which were in turn used to build higher data units such as 'files'. The file was considered to be the ultimate data unit of information processing and data binding 'monolith'. Moreover, pre database systems were designed with one or more programming languages in mind and this in effect restricted independent develop ment and modelling of the applications and associated storage structures. Database systems came along not to turn the above three units into outmoded concepts, but rather to extend them further by establishing a higher logical unit for data description and thereby offer high level data manipulation functions. It also becomes possible for computer professionals and other users to view all information processing needs of an organisation through an integrated, disciplined and methodical approach. So, database systems employ the concepts field, record and file without necessarily making them transparent to the user who is in effect offered a high level language to define data units and relation ships, and another language to manipulate these. A major objective of database systems is to allow logical manipulations to be carried out independent of storage manipulations and vice versa.

Logic and the Organization of Information closely examines the historical and contemporary methodologies used to catalogue information objects—books, ebooks, journals, articles, web pages, images, emails, podcasts and more—in the digital era. This book provides an in-depth technical background for digital librarianship, and covers a broad range of theoretical and practical topics including: classification theory, topic annotation, automatic clustering, generalized synonymy and concept indexing, distributed libraries, semantic web ontologies and Simple Knowledge Organization System (SKOS). It also analyzes the challenges facing today’s information architects, and outlines a series of techniques for overcoming them. Logic and the Organization of Information is intended for practitioners and professionals working at a design level as a reference book for digital librarianship. Advanced-level students, researchers and academics studying information science, library science, digital libraries and computer science will also find this book invaluable.

This book constitutes the strictly refereed post-workshop proceedings of the International Workshop on Logic in Databases, LID'96, held in San Miniato, Italy, in July 1996, as the final meeting of an EC-US cooperative activity. The volume presents 21 revised full papers selected from 49 submissions as well as 3 invited contributions and a summary of a panel discussion on deductive databases: challenges, opportunities and future directions. The retrospective survey on logic and databases by Jack Minker deserves a special mention: it is a 56-page overview and lists 357 references. The papers are organized in sections on uncertainty, temporal and spatial reasoning, updates, active databases, semantics, advanced applications, query evaluation, language extensions, and logic constructs and expressive power.