Spark as described on the Spark website:
The web is not only growing in sheer size, but it also grows in how much it is interconnected. Where once the Web was a set of more or less separated sites, today sites are more and more being connected. More and more data is being offered on the Web in a way that can be further processed, and more and more sites and applications are using external data. More and more mashups are created, where data from different sources is integrated and displayed with novel visualisations.
This MediaWiki extension, unsurprisingly titled Spark, adds a <spark> tag to MediaWiki which is equivalent to <div class=”spark”> as described in the spark library documentation. All parameters (except the class=”spark” one) can just be copied over between spark divs in web pages, and the <spark> tag in MediaWiki. It is currently at version 0.1, which is a beta release. It includes a still experimental version of the Spark library, so you should probably not use this extension on production websites just yet. The Spark people are looking for developers to help out, so if you want to play around with SPARQL a bit, like I basically did with this extension, be sure to poke them 🙂
The extension required MediaWiki 1.17 or above (as it makes use of the new Resource Loader) and PHP 5.2 or later.
- The current Spark (MediaWiki extension) release (zip)
- svn co http://svn.wikimedia.org/svnroot/mediawiki/tags/extensions/Spark/REL_0_1 (tag for 0.1, including Spark lib trunk)
- svn co http://svn.wikimedia.org/svnroot/mediawiki/trunk/extensions/Spark (trunk, including Spark lib trunk)
- svn co http://rdf-spark.googlecode.com/svn/trunk/src/ (Spark lib trunk)
Right now you can embed mashups with SPARQL queries that get their data from some SPARQL endpoint. This opens up a whole bunch of possibilities, but is a bit silly when you are running your own Semantic MediaWiki instance and want to visualize structured data stored by it using Spark. A possible addition to the Spark MediaWiki extension therefore is having support for Spark as a so called SMW result format. For this translation from the SMW ask query language to SPARQL is needed, which is some work. I might implement this at some future point, but have several other things I want to poke at, so it won’t be soonish 🙂