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LODChain: Strengthen the Connectivity of Your RDF Dataset to the Rest LOD Cloud

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The Semantic Web – ISWC 2022 (ISWC 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13489))

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Abstract

It is not an easy task for a data owner to publish a dataset as Linked Data with connections to existing datasets since there are too many datasets, thus it is hard to find the related ones, to download them and to check their content (let alone to apply entity matching over them). However, the connections with other datasets are important for discoverability, browsing, and querying in general. To alleviate this problem in this paper we introduce LODChain, a service that can help a provider to strengthen the connections between his/her dataset and the rest of datasets. LODChain finds the common entities, schema elements and triples among the dataset at hand and hundreds of LOD Datasets and through equivalence reasoning it suggests to the user various inferred connections, as well as related datasets. In addition, it detects erroneous mappings, and offers various content-based dataset discovery services, for enabling the enrichment of datasets’ content. The key difference with the existing approaches is that they are metadata-based, while what we propose is data-based. We present an implementation of LODChain, and we report various experimental results over real and synthetic datasets.

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Acknowledgments

This work has received funding from the European Union’s Horizon 2020 coordination and support action 4CH (Grant agreement No 101004468).

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Authors and Affiliations

  1. Institute of Computer Science - FORTH-ICS, Heraklion, Greece

    Michalis Mountantonakis & Yannis Tzitzikas

  2. Computer Science Department, University of Crete, Heraklion, Greece

    Michalis Mountantonakis & Yannis Tzitzikas

Authors
  1. Michalis Mountantonakis
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  2. Yannis Tzitzikas
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Corresponding author

Correspondence to Michalis Mountantonakis .

Editor information

Editors and Affiliations

  1. University of Manchester, Manchester, UK

    Ulrike Sattler

  2. University of Chile, Santiago, Chile

    Aidan Hogan

  3. University of Cape Town, Cape Town, South Africa

    Maria Keet

  4. University of Bologna, Bologna, Italy

    Valentina Presutti

  5. Universidade Federal do Espírito Santo, Vitória, Brazil

    João Paulo A. Almeida

  6. National Institute of Informatics, Tokyo, Japan

    Hideaki Takeda

  7. Orange, Belfort, France

    Pierre Monnin

  8. Sapienza University of Rome, Rome, Italy

    Giuseppe Pirrò

  9. University of Bari, Bari, Italy

    Claudia d’Amato

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Mountantonakis, M., Tzitzikas, Y. (2022). LODChain: Strengthen the Connectivity of Your RDF Dataset to the Rest LOD Cloud. In: Sattler, U., et al. The Semantic Web – ISWC 2022. ISWC 2022. Lecture Notes in Computer Science, vol 13489. Springer, Cham. https://doi.org/10.1007/978-3-031-19433-7_31

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  • DOI: https://doi.org/10.1007/978-3-031-19433-7_31

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  • Online ISBN: 978-3-031-19433-7

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