Model-driven development (MDD) and model-driven architecture (MDA) are terms one has to deal with when developing software for many modern applications, like those running in real time. They are relatively well known to software engineers. On the other hand, I would say that “ontology” is not a term that would be familiar to most people in the software engineering community. Encouraged by the combination of both terms in the title, I launched into reading this book in the hope that I would systematize my understanding of MDA, and learn something more practical about the use of ontologies. When I began browsing the book, however, it turned out, to my disappointment, that the title was a little misleading. This is not a book on MDA. At least, MDA is not its major topic, as the title suggests. A title such as Application of model-driven architecture to ontology development would more adequately reflect the book’s contents.

The book consists of three parts, which lead the reader logically through the material. Part 1 addresses basic concepts, such as knowledge representation, ontologies, the semantic Web, MDA, and modeling spaces. I was especially interested in seeing how the authors understood the term “ontology,” which does not seem to have a precisely defined meaning. Unfortunately, I wasn’t able to find a definition given by the authors, although they quote and review several definitions given by others. A word of warning for those to whom the term “ontology” is new: do not try to relate it to the meaning in philosophy, from which it has been derived. Contrary to the claims of its inventors, there is no relation between “ontology” in philosophy and “ontology” as used in information systems (artificial intelligence). The former is a science, while the latter is used in the meaning of a description of a system, with its vocabulary, structure, relations, and rules of inference.

Part 2 is central to the book, discussing the use of MDA to develop ontologies. Beginning with general software engineering approaches to ontology development, the authors move to a discussion of MDA-based ontology infrastructure, a description of the ontology definition metamodel, the ontology unified modeling language (UML) profile, and mappings between MDA-based languages and ontologies. Part 3 ends the book, with a presentation of sample applications for ontology modeling.

By reading this book, I definitely expanded my horizons regarding my understanding of ontologies and their potential use, especially in the area of the applicability of the relatively large number of standards involved. It also seems to me that the authors were successful in reaching the goal stated in their preface, “to fill the gap in the literature covering the subject of applications of the MDA for ontology development and the semantic Web.” Not being an expert in ontology development, I will not comment on whether the concepts presented in the book are of any significant practical value. However, from what the authors have to say, it is clear that ontologies and the semantic Web are very interesting research concepts, although if and how they can be applied in practice remains to be seen.