From the post:
SindiceTech today released SparQLed, the SindiceTech Assisted SPARQL Editor, as an open source project. SindiceTech, a spinoff company from the DERI Institute, commercializes large-scale, Big Data infrastructures for enterprises dealing with semantic data. It has roots in the semantic web index Sindice, which lets users collect, search, and query semantically marked-up web data (see our story here).
SparQLed also is one of the components of the commercial Sindice Suite for helping large enterprises build private linked data clouds. It is designed to give users all the help they need to write SPARQL queries to extract information from interconnected datasets.
“SPARQL is exciting but it’s difficult to develop and work with,” says Giovanni Tummarello, who led the efforts around the Sindice search and analysis engine and is founder and CEO of SindiceTech.
Maybe we have become spoiled by search engines that always return results, even bad ones:
With SQL, the advantage lies in having a schema which users can look at and understand how to write a query. RDF, on the other hand, has the advantage of providing great power and freedom, because information in RDF can be interconnected freely. But, Tummarello says, “with RDF there is no schema because there is all sorts of information from everywhere.” Without knowing which properties are available specifically for a certain URI and in what context, users can wind up writing queries that return no results and get frustrated by the constant iterating needed to achieve their ends.
I am not encouraged by a features list that promises:
Less ZERO-result queries