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

Papier de démoInternational audienceRDF aims at being the universal abstract data model for structureddata on the Web. While there is effort to convert data in RDF, the vast majorityof data available on the Web does not conform to RDF. Indeed, exposing datain 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 ofthese 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 transformationlanguage (SPARQL-Generate), an extension of SPARQL for querying notonly RDF datasets but also documents in arbitrary formats. Its implementation ontop of Apache Jena currently covers use cases from related work and more, andenables to query and transform web documents in XML, JSON, CSV, HTML,CBOR, and plain text with regular expressions