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Querying the Web of Data with SPARQL-LD

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Research and Advanced Technology for Digital Libraries (TPDL 2016)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9819))

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Abstract

A constantly increasing number of data providers publish their data on the Web in the RDF format as Linked Data. SPARQL is the standard query language for retrieving and manipulating RDF data. However, the majority of SPARQL implementations requires the data to be available in advance (in main memory or in a repository), not exploiting thereby the real-time and dynamic nature of Linked Data. In this paper we present SPARQL-LD, an extension of SPARQL 1.1 Federated Query that allows to directly fetch and query RDF data from any Web source. Using SPARQL-LD, one can even query a dataset coming from the partial results of a query (i.e., discovered at query execution time), or RDF data that is dynamically created by Web Services. Such a functionality motivates Web publishers to adopt the Linked Data principles and enrich their digital contents and services with RDF, since their data is made directly accessible and exploitable via SPARQL (without needing to set up and maintain an endpoint). In this paper, we showcase the benefits offered by SPARQL-LD through an example related to the Europeana digital library, we report experimental results that demonstrate the feasibility of SPARQL-LD, and we introduce optimizations that improve its efficiency.

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Notes

  1. 1.

    http://europeana.ontotext.com/sparql.

  2. 2.

    https://github.com/fafalios/sparql-ld.

  3. 3.

    http://users.ics.forth.gr/~fafalios/sparql-ld-endpoint.

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Acknowledgements

This work was partially supported by the BlueBRIDGE project (H2020 Research Infrastructures, 2015–2018, Project No: 675680).

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Correspondence to Yannis Tzitzikas .

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Fafalios, P., Yannakis, T., Tzitzikas, Y. (2016). Querying the Web of Data with SPARQL-LD. In: Fuhr, N., Kovács, L., Risse, T., Nejdl, W. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2016. Lecture Notes in Computer Science(), vol 9819. Springer, Cham. https://doi.org/10.1007/978-3-319-43997-6_14

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  • DOI: https://doi.org/10.1007/978-3-319-43997-6_14

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