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Flexible RDF generation from RDF and heterogeneous data sources with SPARQL-Generate

Abstract : RDF aims at being the universal abstract data model for structured data on the Web. While there is effort to convert data in RDF, the vast majority of data available on the Web does not conform to RDF. Indeed, exposing data in RDF, either natively or through wrappers, can be very costly. In this context, transformation or mapping languages that define generation of RDF from non- RDF data represent an efficient solution. Furthermore, the declarative aspect of these solutions makes them easy to adapt to any change in the input data model, or in the output knowledge model. This paper introduces a novel such transformation language (SPARQL-Generate), an extension of SPARQL for querying not only RDF datasets but also documents in arbitrary formats. Its implementation on top of Apache Jena currently covers use cases from related work and more, and enables to query and transform web documents in XML, JSON, CSV, HTML, CBOR, and plain text with regular expressions.
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https://hal-emse.ccsd.cnrs.fr/emse-01417238
Contributor : Florent Breuil <>
Submitted on : Thursday, December 15, 2016 - 2:33:38 PM
Last modification on : Wednesday, June 24, 2020 - 4:19:10 PM

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Maxime Lefrançois, Antoine Zimmermann, Noorani Bakerally. Flexible RDF generation from RDF and heterogeneous data sources with SPARQL-Generate. 20th International Conference on Knowledge Engineering and Knowledge Management, Nov 2016, Bologne, Italy. pp.Pages 131-135, ⟨10.1007/978-3-319-58694-6_16⟩. ⟨emse-01417238⟩

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