Extending SPARQL for data analytic tasks

author: Julian Dolby, IBM Thomas J. Watson Research Center
published: Nov. 10, 2016,   recorded: October 2016,   views: 1218


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SPARQL has many nice features for accessing data integrated across different data sources, which is an important step in any data analysis task. We report on the use of SPARQL for two real data analytic use cases from the healthcare and life sciences domains, which exposed certain weaknesses in the current specification of SPARQL, specifically when the data being integrated is most conveniently accessed via RESTful services and in formats beyond RDF, such as XML. We therefore extended SPARQL with generalized service, constructs for accessing services beyond the SPARQL endpoints supported by service. For efficiency, our constructs support posting data, which is also not supported by service. We provide an open source implementation of this SPARQL endpoint in an RDF store called Quetzal, and evaluate its use in the two data analytic scenarios over real datasets.

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