When people talk about semantic web or linked data success stories, they usually talk about the big, well-known projects such as those at BestBuy, the BBC, NASA, life sciences companies, the whole vocabulary and taxonomy management industry, and the growing use of DBpedia by a range of companies. I’ve always found that a company’s job postings provide interesting clues about their potential technology directions, and the increasing references to SPARQL in these postings is another…

That fact that RDF expresses everything using the same simple three-part data structure has usually been a great strength, but in the case of ordered lists (or RDF collections) it’s pretty messy. The specification defines a LISP-like way of using triples to identify, for each position in a list, what the first member is and what list has the rest of them after that. When saying “and here are the rest” for every member of the list, you don’t want to have to come up with a…

The recent publication of RDF 1.1 specifications fifteen years and three days after RDF 1.0 became a Recommendation has not added many new features to RDF, although it has made a few new syntaxes official, and there were no new documents about the SPARQL query language. The new Recommendations did clean up a few odds and ends, and one bit of cleanup officially removes an annoying impediment to straightforward querying of strings.

Ubuntu has a utility called Tracker that makes it easy to search your hard disk, a bit like the old Google Desktop with a few extra features. One extra feature ranks among the coolest SPARQL applications I’ve ever seen: the ability to execute SPARQL queries against data extracted from files on your hard disk.

In the typical classification of NoSQL databases, the “graph” category is one that was not covered in the “NoSQL Databases for RDF: An Empirical Evaluation” paper that I described in my last blog entry. (Several were “column-oriented” databases, which I always thought sounded like triple stores—the “table” part of they way people describe these always sounded to me like a stretched metaphor designed to appeal to relational database developers.) A…

A little over a year ago, in a blog entry titled SPARQL and Big Data (and NoSQL), I wrote this:

Google once developed a simple environment called Google App Inventor for easy development of native Android apps. After they announced that they would discontinue support and open source it in 2011, the MIT Center for Mobile learning picked it up, so it’s now the MIT App Inventor. (Its Wikipedia page has a nice summary of its history.) I played with it a bit and found it pretty easy to build apps for my phone, even an app that used an RDFS model to drive a user interface. My simple…