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Programming the Semantic Web 1st Edition

4.3 out of 5 stars 18 customer reviews
ISBN-13: 978-0596153816
ISBN-10: 0596153813
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Book Description

Build Flexible Applications with Graph Data

About the Author

Toby Segaran is the author of "Programming Collective Intelligence", a very popular O'Reilly title. He was the founder of Incellico, a biotech software company later acquired by Genstruct. He currently holds the title of Data Magnate at Metaweb Technologies and is a frequent speaker at technology conferences.

Colin Evans combines machine learning and semantic analysis into a deadly one-two punch against information entropy and noisy data. The results of his efforts appear as millions of facts in Freebase. Prior to joining Metaweb, Colin helped users organize their world through his work on the IRIS semantic desktop project at SRI.

Jamie Taylor started one of the first ISPs in San Francisco while developing an Internet laboratory for studying economic equilibria. His goal was to get a better connection at home. He finally got a real job as CTO at DETERMINE Software (now a part of Selectica) helping create order in the unstructured world of Enterprise contract management. He is now helping to organize the world's structured information at Metaweb where he oversees data operations.


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Product Details

  • Paperback: 302 pages
  • Publisher: O'Reilly Media; 1 edition (July 24, 2009)
  • Language: English
  • ISBN-10: 0596153813
  • ISBN-13: 978-0596153816
  • Product Dimensions: 7 x 0.7 x 9.2 inches
  • Shipping Weight: 15.2 ounces (View shipping rates and policies)
  • Average Customer Review: 4.3 out of 5 stars  See all reviews (18 customer reviews)
  • Amazon Best Sellers Rank: #814,276 in Books (See Top 100 in Books)

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Customer Reviews

Top Customer Reviews

Format: Paperback
The semantic web. We have all heard about it, the buzz, the hype, and the excitement. Much of it seems well founded once you look deeper into the idea of organizing and making data available in a way that machines can find it, share it, and combine it in new ways that were not considered or even thought of when the data was being collected. This can yield amazing results and discoveries, but to do it, we need to move beyond theory and into practice. That is what this book is about.

Programming the Semantic Web starts with a clear and practical introduction to the idea of the semantic web that will give any web developer the background necessary to comprehend the potential and usefulness of the concept. This is not a book for complete novices as it does anticipate that the reader will have previous experience with programming for the web, including the concepts of relational databases, familiarity with HTML and XML and perhaps a little RDF, and it would be useful to have some knowledge of Python and/or other computer programming languages.

The first part of the book, about 20% of the text, is dedicated to a discussion of what semantics are, how they can be used to express meaning, and why they have the potential to make data storage easily searchable and allow the discovery of new connections that were not considered during the design or collection stages. We learn here how semantic modeling can be expanded with far less pain than a traditional relational database format, allowing the administrator to adjust interfaces and searches quickly in response to the needs of users.

In Part II, the book discusses the practical technological foundations necessary to begin using RDF and other formats to store data in semantic fashion and make it useful.
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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.
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Format: Paperback
Note: this review is based on a pre-release copy of the book.

When I first encountered RDF years ago, I wrote it off. It seemed unlikely that it would get much use. But the recent arrival of collections of so-called 'semantic' data via organizations like Freebase, has made me rethink that position. Of course, figuring out how to make use of this data is another proposition, but Programming the Semantic Web serves as a solid introduction and survey of the tools and techniques necessary to make it into something worth your effort.

I can say that after reading this book, I finally get the concept of semantic data and the relationships it defines. The book begins by walking through the building of a basic triple-store (that is, a data store full of triples -- if you don't know what they are, you should read the book). This and the ensuing discussion of the graph structures built from these triples leads into an introduction to RDF. In this context, it really starts to make sense.

The examples in this book are quite useful and not too abstract. For instance, one of the examples shows how to take legacy data from an RDBMS and generate an RDF graph, going from implicit to explicit semantics. Another uses a programmatic version of the popular 'Six Degrees of Kevin Bacon' trivia game to show how you can use a semantic database of movie data to find the shortest path between two given actors (one, clearly, being the ever-popular Kevin Bacon). The final example in the book shows in brief how you might build a system for managing job listings for various companies. The example is thorough and reasonably complex, but still manages to cover a lot of ground, including integration with libraries for visualizing the data.
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