1. Semantic Data

   1. Chapter 1 Why Semantics?

      1. Data Integration Across the Web
      2. Traditional Data-Modeling Methods
      3. Semantic Relationships
      4. Metadata Is Data
      5. Building for the Unexpected
      6. “Perpetual Beta”

   2. Chapter 2 Expressing Meaning

      1. An Example: Movie Data
      2. Building a Simple Triplestore
      3. Merging Graphs
      4. Adding and Querying Movie Data
      5. Other Examples

   3. Chapter 3 Using Semantic Data

      1. A Simple Query Language
      2. Feed-Forward Inference
      3. Searching for Connections
      4. Shared Keys and Overlapping Graphs
      5. Basic Graph Visualization
      6. Semantic Data Is Flexible

2. Standards and Sources

   1. Chapter 4 Just Enough RDF

      1. What Is RDF?
      2. The RDF Data Model
      3. RDF Serialization Formats
      4. Introducing RDFLib
      5. SPARQL

   2. Chapter 5 Sources of Semantic Data

      1. Friend of a Friend (FOAF)
      2. Linked Data
      3. Freebase

   3. Chapter 6 What Do You Mean, “Ontology”?

      1. What Is It Good For?
      2. An Introduction to Data Modeling
      3. Just Enough OWL
      4. Using Protégé
      5. Just a Bit More OWL
      6. Some Other Ontologies
      7. This Is Not My Beautiful Relational Schema!

   4. Chapter 7 Publishing Semantic Data

      1. Embedding Semantics
      2. Dealing with Legacy Data
      3. RDFLib to Linked Data

3. Putting It into Practice

   1. Chapter 8 Overview of Toolkits

      1. Sesame
      2. Other RDF Stores
      3. SIMILE/Exhibit

   2. Chapter 9 Introspecting Objects from Data

      1. RDFObject Examples
      2. RDFObject Framework
      3. How RDFObject Works

   3. Chapter 10 Tying It All Together

      1. A Job Listing Application
      2. Job Listing Data
      3. Serving the Website
      4. A Generic Viewer
      5. Getting Company Data
      6. Specialized Views
      7. Publishing for Others
      8. Expanding the Data
      9. Sophisticated Queries
      10. Visualizing the Job Data
      11. Further Expansion

4. Epilogue

   1. Chapter 11 The Giant Global Graph

      1. Vision, Hype, and Reality
      2. Participating in the Global Graph Community
      3. Bracing for Continuous Change

1. Colophon

The animal on the cover of Programming the Semantic Web is a red panda (Ailurus fulgens, or "shining cat"), named for its bright, cinnamon-colored fur. Its resemblance to other animals has given it many nicknames, including firefox, cat bear, and lesser panda. Although predominantly red, it has white markings on its face and a black belly and limbs. Its long tail is ringed with red and yellow. Slightly larger than a domestic cat, the red panda is 30 to 50 inches long and weighs about 12 pounds.

Most wild pandas live on the slopes of the Himalayas and in the southwest forests of China. Preferring high altitudes, they move slowly on the ground but are agile climbers and foragers in the canopy. They subsist almost entirely on bamboo. During the hottest part of the day, the pandas sleep in shady treetops with their tails wrapped around their heads, becoming active only in the evening.

The red panda is endangered, due to habitat destruction, and is now a protected species in Nepal and China. No official numbers exist, but the total population is estimated at 2,500 individuals world-wide--mostly in Asian zoos--and rapidly declining. Contributing to their endangerment is the fact that red pandas are solitary creatures with a low birth rate and a high death rate in the wild, although their lifespan in captivity is 10-12 years. To counteract the population decline, zoos around the world have begun breeding programs, and several have successfully released captive-born pandas into the wild.

The cover image is from The Riverside Natural History. The cover font is Adobe ITC Garamond. The text font is Linotype Birka; the heading font is Adobe Myriad Condensed; and the code font is LucasFont's TheSansMonoCondensed.