I'm very pleased to announce that O'Reilly will make the second, expanded edition of my book Learning SPARQL available sometime in late June or early July. The early release "raw and unedited" version should be available this week.
I've updated the book to account for the final version of the SPARQL 1.1 specs, but the main additions are four new chapters:
Query Efficiency and Debugging: Things to keep in mind that can help your queries run more efficiently as you work with growing volumes of data.
Working with SPARQL Query Result Formats: How your applications can take advantage of the XML, JSON, CSV, and TSV formats defined by the W3C for SPARQL processors to return query results.
RDF Schema, OWL, and Inferencing: How SPARQL can take advantage of the metadata that RDF Schemas, OWL ontologies, and SPARQL rules can add to you data.
A SPARQL Cookbook: A set of SPARQL queries and update requests that can be useful in a wide variety of situations.
I've also expanded the Application Development chapter quite a bit.
Preliminary reviewers have especially liked the cookbook chapter, and I learned a great deal researching, writing, and having the query efficiency chapter tech reviewed. I'm eager for others to see all the new chapters.
I've also made some corrections, improved the index, and many passive sentences were converted to the active voice (or rather, I converted many passive sentences...).
Having a lot more to it, the new edition will cost a little more, but if you bought an electronic version of the first edition, you can get the second edition in the same format for 40% off. At this week's semtech conference in San Francisco, I'll have some moo cards that give you 40% of the printed book or 50% off the ebook, so if you see me just ask for one.
I joke about the book's 23% reduction in mentions of the semantic web (and incremental reduction in mentions of "linked data"), as contrasted with the page count going up 53%, because of my recent belief that SPARQL and other RDF-related technologies can be sold on their own merits instead of being sold as the implementation of a vision that people must first buy into. Let people select the technology that they feel is best—even if it has a strange name like Hadoop or MongoDB or SPARQL—to implement the visionary buzzphrase that is getting their project funded, whether it's "Big Data" or "Semantic Web" or whatever new buzzphrase will be hot two years from now and first noticed by Gartner two years after that. I think SPARQL and the associated standards have a huge amount to offer all of these new visions of ways to do more with data and metadata.
Please add any comments to this Google+ post.