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Lifting Tabular Data to RDF: A Survey

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Book cover Metadata and Semantic Research (MTSR 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1355))

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Abstract

Tabular data formats (e.g. CSV and spreadsheets) combine ease of use, versatility and compatibility with information management systems. Despite their numerous advantages, these formats typically rely on column headers and out-of-band agreement to convey semantics. There is clearly a large gap with respect to the Semantic Web, which uses RDF as a graph-based data model, while relying on ontologies for well-defined semantics. Several systems have been developed to close this gap, supporting the conversion of tabular data to RDF. This study is a survey of these systems, which have been analyzed and compared. We identified commonalities and differences among them, discussed different approaches and derived useful insights on the task.

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Notes

  1. 1.

    https://rml.io/specs/rml/.

  2. 2.

    https://labs.sparna.fr/skos-play/convert.

  3. 3.

    https://jena.apache.org/documentation/fuseki2/.

  4. 4.

    https://art.uniroma2.it/sheet2rdf/documentation/heuristics.jsf.

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Authors and Affiliations

  1. Department of Enterprise Engineering, University of Rome Tor Vergata, via del Politecnico 1, 00133, Roma, Italy

    Manuel Fiorelli & Armando Stellato

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  1. Manuel Fiorelli
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  2. Armando Stellato
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Correspondence to Manuel Fiorelli .

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Editors and Affiliations

  1. International Hellenic University, Thessaloniki, Greece

    Emmanouel Garoufallou

  2. Complutense University of Madrid, Madrid, Spain

    María-Antonia Ovalle-Perandones

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Fiorelli, M., Stellato, A. (2021). Lifting Tabular Data to RDF: A Survey. In: Garoufallou, E., Ovalle-Perandones, MA. (eds) Metadata and Semantic Research. MTSR 2020. Communications in Computer and Information Science, vol 1355. Springer, Cham. https://doi.org/10.1007/978-3-030-71903-6_9

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  • DOI: https://doi.org/10.1007/978-3-030-71903-6_9

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  • Online ISBN: 978-3-030-71903-6

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