Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL

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Elsevier, Jul 5, 2011 - Computers - 384 pages
Semantic Web for the Working Ontologist: Effective Modeling in RDFS and OWL, Second Edition, discusses the capabilities of Semantic Web modeling languages, such as RDFS (Resource Description Framework Schema) and OWL (Web Ontology Language). Organized into 16 chapters, the book provides examples to illustrate the use of Semantic Web technologies in solving common modeling problems. It uses the life and works of William Shakespeare to demonstrate some of the most basic capabilities of the Semantic Web. The book first provides an overview of the Semantic Web and aspects of the Web. It then discusses semantic modeling and how it can support the development from chaotic information gathering to one characterized by information sharing, cooperation, and collaboration. It also explains the use of RDF to implement the Semantic Web by allowing information to be distributed over the Web, along with the use of SPARQL to access RDF data. Moreover, the reader is introduced to components that make up a Semantic Web deployment and how they fit together, the concept of inferencing in the Semantic Web, and how RDFS differs from other schema languages. Finally, the book considers the use of SKOS (Simple Knowledge Organization System) to manage vocabularies by taking advantage of the inferencing structure of RDFS-Plus. This book is intended for the working ontologist who is trying to create a domain model on the Semantic Web.
  • Updated with the latest developments and advances in Semantic Web technologies for organizing, querying, and processing information, including SPARQL, RDF and RDFS, OWL 2.0, and SKOS
  • Detailed information on the ontologies used in today's key web applications, including ecommerce, social networking, data mining, using government data, and more
  • Even more illustrative examples and case studies that demonstrate what semantic technologies are and how they work together to solve real-world problems
 

Contents

Chapter 1 What is the Semantic Web?
1
Chapter 2 Semantic modeling
13
Chapter 3 RDFThe basis of the Semantic Web
27
Chapter 4 Semantic Web application architecture
51
Chapter 5 Querying the Semantic WebSPARQL
61
Chapter 6 RDF and inferencing
113
Chapter 7 RDF schema
125
Chapter 8 RDFSPlus
153
Chapter 11 Basic OWL
221
Chapter 12 Counting and sets in OWL
249
Chapter 13 Ontologies on the Webputting it all together
279
Chapter 14 Good and bad modeling practices
307
Chapter 15 Expert modeling in OWL
325
Chapter 16 Conclusions
335
Appendix Frequently asked questions
339
Further reading
343

Chapter 9 Using RDFSPlus in the wild
187
Chapter 10 SKOSmanaging vocabularies with RDFSPlus
207
Index
347
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About the author (2011)

Dean Allemang is the chief scientist at TopQuadrant, Inc.—the first company in the United States devoted to consulting, training, and products for the Semantic Web. He co-developed (with Professor Hendler) TopQuadrant’s successful Semantic Web training series, which he has been delivering on a regular basis since 2003. He has served as an invited expert on numerous international review boards, including a review of the Digital Enterprise Research Institute—the world’s largest Semantic Web research institute — and the Innovative Medicines Initiative, a collaboration between 10 pharmaceutical companies and the European Commission to set the roadmap for the pharmaceutical industry for the near future.

Jim Hendler is the Tetherless World Senior Constellation Chair at Rensselaer Polytechnic Institute, and has authored over 200 technical papers in the areas of artificial intelligence, Semantic Web, agent-based computing, and web science. One of the early developers of the Semantic Web, he is the Editor-in-Chief emeritus of IEEE Intelligent Systems and is the first computer scientist to serve on the Board of Reviewing Editors for Science. In 2010, he was chosen as one of the 20 most innovative professors in America by Playboy magazine, Hendler currently serves as an "Internet Web Expert" for the U.S. government, providing guidance to the Data.gov project.

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