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Abstract

This text introduces the standardized knowledge representation languages for modeling ontologies operating at the core of the semantic web. It covers RDF schema, Web Ontology Language (OWL), rules, query languages, the OWL 2 revision, and the forthcoming Rule Interchange Format (RIF). A 2010 CHOICE Outstanding Academic Title ! The nine chapters of the book guide the reader through the major foundational languages for the semantic Web and highlight the formal semantics. ! the book has very interesting supporting material and exercises, is oriented to W3C standards, and provides the necessary foundations for the semantic Web. It will be easy to follow by the computer scientist who already has a basic background on semantic Web issues; it will also be helpful for both self-study and teaching purposes. I recommend this book primarily as a complementary textbook for a graduate or undergraduate course in a computer science or a Web science academic program. --Computing Reviews, February 2010 This book is unique in several respects. It contains an in-depth treatment of all the major foundational languages for the Semantic Web and provides a full treatment of the underlying formal semantics, which is central to the Semantic Web effort. It is also the very first textbook that addresses the forthcoming W3C recommended standards OWL 2 and RIF. Furthermore, the covered topics and underlying concepts are easily accessible for the reader due to a clear separation of syntax and semantics ! I am confident this book will be well received and play an important role in training a larger number of students who will seek to become proficient in this growing discipline.

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Abstract

The focus of research on representing and reasoning with knowledge traditionally has been on single specifications and appropriate inference paradigms to draw conclusions from such data. Accordingly, this is also an essential aspect of ontology research which has received much attention in recent years. But ontologies introduce another new challenge based on the distributed nature of most of their applications, which requires to relate heterogeneous ontological specifications and to integrate information from multiple sources. These problems have of course been recognized, but many current approaches still lack the deep formal backgrounds on which todays reasoning paradigms are already founded. Here we propose category theory as a well-explored and very extensive mathematical foundation for modelling distributed knowledge. A particular prospect is to derive conclusions from the structure of those distributed knowledge bases, as it is for example needed when merging ontologies

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