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Computer Science - Software Engineering | Model Driven Engineering and Ontology Development

Model Driven Engineering and Ontology Development

Gaševic, Dragan, Djuric, Dragan, Devedžic, Vladan

2nd ed. 2009

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  • Explains in detail how to use standards like MDA and UML for ontology development
  • First detailed description of OMG’s upcoming ODM (Ontology Definition Metamodel) standard
  • Illustrated throughout with useful and easily digestible examples
  • Complemented by an additional website with further examples and teaching material

Defining a formal domain ontology is generally considered a useful, not to say necessary step in almost every software project. This is because software deals with ideas rather than with self-evident physical artefacts. However, this development step is hardly ever done, as ontologies rely on well-defined and semantically powerful AI concepts such as description logics or rule-based systems, and most software engineers are largely unfamiliar with these.

Gaševic and his co-authors try to fill this gap by detailing how to use model-driven engineering for ontology development on the Semantic Web. Part I of their book describes existing technologies, tools, and standards like XML, RDF, OWL, MDA, and UML. Part II presents the first detailed description of OMG's new ODM (Ontology Definition Metamodel) initiative, a specification which is expected to be in the form of an OMG language like UML. Finally, Part III is dedicated to applications and practical aspects of developing ontologies using MDA-based languages.

For this second edition, the descriptions of the related standards (like MOF, ODM, OCL, and OWL) have been revised and updated; new chapters introducing the basic principles of model-driven engineering, recent research results on metamodeling Semantic Web rule languages, an introduction to the Atlas Transformation Language (ATL) and its tool support, and, last but not least, many new examples have been added.

Content Level » Research

Keywords » Ontologie - artificial intelligence - knowledge - knowledge representation - modeling - semantic web - software engineering

Related subjects » Artificial Intelligence - Database Management & Information Retrieval - Software Engineering

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