Product Description
Ontologies provide a common vocabulary of an area and define – with different levels of formality – the meaning of the terms and the relationships between them. Ontologies may be reused and shared across applications and groups Concepts in the ontology are usually organized in taxonomies and relations between concepts, properties of concepts, and axioms are typically used for representing the knowledge contained in ontologies. With the growth of information available, e.g. on the WWW, they are popularly applied in knowledge management, semantic web, natural language generation, enterprise modelling, knowledge-based systems, ontology-based brokers, e-commerce platforms and interoperability between systems. This book looks at questions such as: * What is an ontology? * What are the uses of ontologies? * What types of ontologies exist? What are the most well-known ones? * How do I select the best ontology for my application? * What are the principles for building an ontology? * What methodologies should I use to build my own ontology? Which techniques are appropriate for each step? * How do software tools support the process of building and using ontologies? * What language can I use to implement ontologies? * How can I integrate ontologies in a given language? The book presents the theoretical foundations of ontological engineering and covers the practical aspects of selecting and applying methodologies, tools and languages for building ontologies. The applications of ontologies are also illustrated with case studies taken from the areas of knowledge management, e-commerce and the semantic web.
The subject matter is much too complex, does not follow a logical order, is a slow and arduous read, and is not practical.
This book was the subject of a book club where I and a small group of software engineers wanted to learn more about ontologies. Most of the members of the group had some experience with ontology languages. In each one-hour lunch session, we were not able to discuss more than 10 pages at a time due to the complexity of the writing and the subject matter. We finally gave up and none of us has finished the book. Although we read over half of the book before giving up, we gained no practical knowledge from it whatsoever.
Rating: 1 / 5
The book is well organized in introducing the subject in a coherent manner and weaving in all important criteria of ontology together. I especially like to read the comparison of different languagees in light of knowlege represenation and knowlege reasoing. The book is great in terms of getting a broad view (survey) and is also great as a reference. In many pages, there is so much information packed in each sentences. Great book.
Rating: 4 / 5
There is considerable confusion over what is, and is not, an ontology. Unfortunately, in defining an ontology, this book doesn’t provide any negative examples, meaning that confusion will most likely persist. Hopefully this shortcoming will be addressed in a future edition. That said, the book is nevertheless a valuable contribution to the field.
Rating: 4 / 5
The subject of this book is incredibly relevant to today’s world of information management. The chapters are presented in a logical and informative way, though some of the book only skims the surface or barely touches on significant developments, tools, and problems. Overall, I found the text too theoretical, with insufficient ties to messy real-world issues.
Rating: 4 / 5
The book shows progress in how ontologies are defined from various data sets. The subject is a natural field of artificial intelligence, in attempting to automated this filling of an ontology. Various example ontologies are presented, along with the markup languages like RDF and OWL in which these are expressed. The progress is visible, inasmuch as just a few years ago, these languages were devised. Now we see non-trivial ontology constructions using them. Good.
A large portion of the book describes the acute problem of somehow extracting meaning in a programmatic manner from data. Because the manual making of an ontology simply does not seem to scale, given the realities of gigabyte databases. We see that there is a natural decomposition of the problem into a linguistic step and a conceptual step. The former is tied to a particular human language. The latter is the nut of the problem. Current methods look promising, but are certainly not the last word.
Rating: 4 / 5