With this book, the promise of the Semantic Web -- in which machines can find, share, and combine data on the Web -- is not just a technical possibility, but a practical reality Programming the Semantic Web demonstrates several ways to implement semantic web applications, using current and emerging standards and technologies. You'll learn how to incorporate existing data sources into semantically aware applications and publish rich semantic data. Each chapter walks you through a single piece of semantic technology and explains how you can use it to solve real problems. Whether you're writing a simple mashup or maintaining a high-performance enterprise solution,Programming the Semantic Web provides a standard, flexible approach for integrating and future-proofing systems and data. This book will help you:

• Learn how the Semantic Web allows new and unexpected uses of data to emerge

• Understand how semantic technologies promote data portability with a simple, abstract model for knowledge representation

• Become familiar with semantic standards, such as the Resource Description Framework (RDF) and the Web Ontology Language (OWL)

• Make use of semantic programming techniques to both enrich and simplify current web applications

Amazon.com® Reader Reviews (Ranked by Helpfulness)

Average Amazon.com® Rating:  Based on 9 Ratings

Welcomed book, but some disappointments - 2009-08-17
Reviewer Rating:
While I am glad to see books about Semantic Web technologies that are written specifically for software developers, I am disappointed that I cannot give this book more than 3 stars. Why? The book contains misleading statements that may lead a developer new to these technologies astray and encourage non-optimal practices. I will give a few examples illustrating what I mean:

-On page 131, the example explaining property domains may lead the reader to believe that having two separate domain statements (ex:hasEyeColor rdfs: domain ex:Human and ex:hasEyeColor rdfs: domain ex:Animal) is "the" way to do things. Such a practice creates issues which are not properly explained. And the diagram 6-1 illustrating this modeling example is wrong. Looking at it, the reader is left believing that the domain of ex:hasEyeColor property is a universe of things that includes Humans and Animals, while in reality it is an intersection of Humans and Animals. If someone were now to add another domain triple such as ex:hasEyeColor rdfs: domain ex:Dog, the domain would become the intersection of Humans, Animals and Dogs and a conclusion could be drawn that Jamie Taylor is a dog - obviously, not what was intended.

-On page 140 it is stated that RDF schemas are usually stored in the same graph with the data they represent. This is not true and, to the contrary, is considered to be a poor practice - keeping schema and data separate is important for schema reuse. Did the writers intended to say that they are usually put in the same triple store? The statement is confusing and it is contradicted by the book examples such as those using FOAF. It is clear that FOAF schema and FOAF data files are separate graphs.

-While modularity is talked about ("semantic data model is not a monolithic thing"), the key mechanisms used for modularity (e.g., imports and named graphs) are not mentioned anywhere.

-Describing SPARQL as a "read only" language is not correct. While INSERT or DELETE keywords are not part of SPARQL 1.0, the CONSTRUCT keyword provides a way to create new triples. Developers can also use CONSTRUCT to identify triples to be deleted. I also believe it would have been useful to mention that Jena API (arguably the API most used by the developers building Semantic Web applications) already directly implements inserts and deletes and this implementation is being used in the upcoming SPARQL 2.0 spec. Perhaps, this was not known at the time certain chapters of the book were written.

-The cursory of SPARQL is disappointing. SPARQL mastery is as important to the developer working with the Semantic Web data as SQL mastery is to the developer working with the relational data.

-The blank node example of address raised a concern that the imprecise language used in describing the motivations for using the blank node does not make it clear that a blank nodes can never be referenced across graphs.

In conclusion, the book does a good job covering a broad range of topics in a very concrete, down-to-earth way. It directly addresses some of the key misconceptions about the Semantic Web standards. For example, it makes it very clear that RDF is a data model and RDF/XML is simply one serialization of it. The depth of coverage is insufficient and uneven impacting the book's effectiveness for developers. Some choices of the areas authors decided to focus on are questionable. For example, I would have preferred to see less coverage of Freebase and more of SPARQL. I am also left wondering how much of a peer review the book had received prior to publication. An even modestly rigorous review process would probably have caught the most notable errors, imprecisions and omissions and resulted in a stronger book.

Awesome book for using RDF / Triple Store models in the real world - 2009-09-27
Reviewer Rating:
So much written about the Semantic Web is theoretical, often verging on esoteric. Programming the Semantic Web crosses the gap from theory to practice: it's a book for real-world developers trying to bring products to market.

I fortuitously discovered this book just as our company embarked on the design of a new product, one that needed to store massive amounts of structured, but sparse, data culled from a variety of sources. Since most developers are trained solely in relational database structures, our initial inclination was to use a sharded relational data model to ensure we'd be able to get new developers up-to-speed and meet our deadline. Programming the Semantic Web provided a clear explanation of the limits of relational data models for this kind of data, and contained a great walk-thru of how an RDF-based model offered a multitude of benefits. In fact, using a triple store has reduced our development time dramatically. The book's balanced discussion of the myriad of toolkits and RDF Stores available also helped us get off the ground selecting the right platform quickly.

Programming the Semantic Web is now required reading for all developers joining our project team. Using the ideas and models described in the book, we've made our system more scalable, more flexible, and dramatically accelerated our development cycles.

excellent overview of semantic data - 2009-09-25
Reviewer Rating:
There aren't many other books that a programmer can buy hoping to actually learn how to build real systems based on semantic data. Rather then get bogged down in the academic backing behind semantic data this book sidesteps a the idealistic principles of semantic data to instead focus on getting things done, and what the actual advantages to representing your data as a semantic graph are. As such, it explains how to actually accomplish real, concrete tasks using real technologies - and explains how to do this using simple, but realistic examples, and realistic code.

Planet Earth - 2009-11-04
Reviewer Rating:
This is the first book I have read on the semantic web that does not give me feeling that I am in outer space. It is also one of the few books that honestly appraises the current, usable state of the semantic web. It is clearly written and took me a day to read (without working the examples). In the beginning, it starts with a pure triples system built from the ground up, rather than plunging the reader into the standard technologies, which are levels of abstraction above triples and may not be essential. The reader is left with the impression that he is the one who chooses to use the technologies introduced. It is also the only book that mentions how RDF evolved. It contains many example programs using existing data sources (e.g. freebase). There is a two page introduction by Jim Hendler, one of the top figures in the semantic web and co-author of "The Semantic Web for the Working Ontologist" (also, a good companion book).

The main view of this book is the semantic web as extension, modification, and very major improvement, to relational systems. It also discusses the pure AI approach. I does not get into other uses of the semantic web, such as text retrieval or approaches such as topic maps.

The large majority of this book is in Python, the easiest and probably the best designed of modern languages. It has a few examples in JavaScript and Java. Readers are encouraged to implement the examples in other languages, if they are inclined to.

Physicists and chemists are required to run experiments to prove their assertions. Many other sciences have emulated aspects of physics to acquire the mantle. The semantic web does not ask for "experiments" although it is about semantics and, therefore, about something to be discovered. This book starts in that direction.

Several ways to implement semantic web applications are explored - 2009-10-13
Reviewer Rating:
Toby Segaran, et.al.'s PROGRAMMING THE SEMANTIC WEB tells how to use graph data to build solid, flexible applications - applications in which machines can find, share and combine data on the Web. Several ways to implement semantic web applications are explored in a guide that covers different pieces of semantic technology and how to use it to solve real problems.

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