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Flexible RDF Generation from RDF and Heterogeneous Data Sources with SPARQL-Generate

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Knowledge Engineering and Knowledge Management (EKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10180))

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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.

This paper has been partly funded by the ITEA2 12004 SEAS (Smart Energy Aware Systems) project, the ANR 14-CE24-0029 OpenSensingCity project, and a research contract with ENGIE R&D.

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Notes

  1. 1.

    A lot of hardcoded transformation are available for many formats – https://www.w3.org/wiki/ConverterToRdf.

  2. 2.

    Prefixes are omitted to save space.

  3. 3.

    http://w3id.org/sparql-generate/tests-reports.html.

  4. 4.

    https://github.com/thesmartenergy/sparql-generate.

References

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  2. Das, S., Sundara, S., Cyganiak, R.: R2RML: RDB to RDF Mapping Language. W3C Recommendation (2012). http://www.w3.org/TR/2012/REC-r2rml-20120927/

  3. Dimou, A., Sande, M.V., Colpaert, P., Verborgh, R., Mannens, E., Van de Walle, R.: RML: a generic language for integrated RDF mappings of heterogeneous data. In: Proceedings of the Workshop on Linked Data on the Web (LDOW 2014) (2014)

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  4. Lefrançois, M., Zimmermann, A.: Supporting arbitrary custom datatypes in RDF and SPARQL. In: Sack, H., Blomqvist, E., d’Aquin, M., Ghidini, C., Ponzetto, S.P., Lange, C. (eds.) ESWC 2016. LNCS, vol. 9678, pp. 371–386. Springer, Cham (2016). doi:10.1007/978-3-319-34129-3_23

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  5. Polleres, A., Krennwallner, T., Lopes, N., Kopecký, J., Decker, S.: XSPARQL Language Specification. W3C Member Submission. http://www.w3.org/Submission/2009/SUBM-xsparql-language-specification-20090120/

  6. Tandy, J., Herman, I., Kellogg, G.: Generating RDF from Tabular Data on the Web. W3C Recommendation. http://www.w3.org/TR/2015/REC-csv2rdf-20151217/

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Author information

Authors and Affiliations

  1. Univ. Lyon MINES Saint-Étienne, CNRS, Laboratoire Hubert Curien UMR 5516, 42023, Saint-Étienne, France

    Maxime Lefrançois, Antoine Zimmermann & Noorani Bakerally

Authors
  1. Maxime Lefrançois
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  2. Antoine Zimmermann
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  3. Noorani Bakerally
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Corresponding author

Correspondence to Maxime Lefrançois .

Editor information

Editors and Affiliations

  1. University of Bologna , Bologna, Italy

    Paolo Ciancarini

  2. University of Bologna , Bologna, Italy

    Francesco Poggi

  3. Stanford University , Palo Alto, California, USA

    Matthew Horridge

  4. Lancaster University , Lancaster, United Kingdom

    Jun Zhao

  5. Garvan Institute of Medical Research , Darlinghurst, New South Wales, Australia

    Tudor Groza

  6. Universidad Politecnica de Madrid , Boadilla del Monte, Spain

    Mari Carmen Suarez-Figueroa

  7. The Open University , Milton Keynes, United Kingdom

    Mathieu d'Aquin

  8. STLab ISTC-CNR , Rome, Italy

    Valentina Presutti

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Lefrançois, M., Zimmermann, A., Bakerally, N. (2017). Flexible RDF Generation from RDF and Heterogeneous Data Sources with SPARQL-Generate. In: Ciancarini, P., et al. Knowledge Engineering and Knowledge Management. EKAW 2016. Lecture Notes in Computer Science(), vol 10180. Springer, Cham. https://doi.org/10.1007/978-3-319-58694-6_16

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  • DOI: https://doi.org/10.1007/978-3-319-58694-6_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-58693-9

  • Online ISBN: 978-3-319-58694-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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