Allemang Dean Hendler James - Semantic Web for the Working Ontologist,

Since the first edition of Semantic Web for the Working Ontologist came out in June 2008, we have been encouraged by the reception the book has received. Practitioners from a wide variety of industrieshealth care, energy, environmental science, life sciences, national intelligence, and publishing, to name a fewhave told us that the first edition clarified for them the possibilities and capabilities of Semantic Web technology. This was the audience we had hoped to reach, and we are happy to see that we have.

Since that time, the technology standards of the Semantic Web have continued to develop. SPARQL, the query language for RDF, became a Recommendation from the World Wide Web Consortium and was so successful that version 2 is already nearly ready (it will probably be ratified by the time this book sees print). SKOS, which we described as an example of modeling in the wild in the first edition, has raced to the forefront of the Semantic Web with high-profile uses in a wide variety of industries, so we gave it a chapter of its own. Version 2 of the Web Ontology Language, OWL, also appeared during this time.

Probably the biggest development in the Semantic Web standards since the first edition is the rise of the query language SPARQL. Beyond being a query language, SPARQL is a powerful graph-matching language which pushes its utility beyond simple queries. In particular, SPARQL can be used to specify general inferencing in a concise and precise way. We have adopted it as the main expository language for describing inferencing in this book. It turns out to be a lot easier to describe RDF, RDFS, and OWL in terms of SPARQL.

The in the wild sections became problematic in the second edition, but for a good reasonwe had too many good examples to choose from. Were very happy with the final choices, and are pleased with the resulting in the wild ). The Open Graph Protocol and Good Relations are probably responsible for more serious RDF data on the Web than any other efforts. While one may argue (and many have) that FOAF is getting a bit long in the tooth, recent developments in social networking have brought concerns about privacy and ownership of social data to the fore; it was exactly these concerns that motivated FOAF over a decade ago. We also include two scientific examples of models in the wildQUDT (Quantities, Units, Dimensions, and Types) and The Open Biological and Biomedical Ontologies (OBO). QUDT is a great example of how SPARQL can be used to specify detailed computation over a large set of rules (rules for converting units and for performing dimensional analysis). The wealth of information in the OBO has made them perennial favorites in health care and the life sciences. In our presentation, we hope to make them accessible to an audience who doesnt have specialized experience with OBO publication conventions. While these chapters logically build on the material that precedes them, we have done our best to make them stand alone, so that impatient readers who havent yet mastered all the fine points of the earlier chapters can still appreciate the wild examples.

We have added some organizational aids to the book since the first edition. The Challenges that appear throughout the book, as in the first edition, provide examples for how to use the Semantic Web technologies to solve common modeling problems. The FAQ section organizes the challenges by topic, or, more properly, by the task that they illustrate. We have added a numeric index of all the challenges to help the reader cross-reference them.

We hope that the second edition will strike a chord with our readers as the first edition has done.

On a sad note, many of the examples in use Elizabeth Taylor as an example of a living actress. During postproduction of this book, Dame Elizabeth Taylor succumbed to congestive heart failure and died. We were too far along in the production to make the change, so we have kept the examples as they are. May her soul rest in peace.