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European Semantic Web Conference

ESWC 2022: The Semantic Web pp 200–216Cite as

Never Mind the Semantic Gap: Modular, Lazy and Safe Loading of RDF Data

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Part of the Lecture Notes in Computer Science book series (LNCS,volume 13261)

Abstract

Any attempt at a tight integration between semantic technologies and object oriented programming will invariably stumble over the gap between the two underlying object models. We illustrate how this semantic gap manifests from the point of view of data retrieval with SPARQL. We present a novel mechanism to load data from RDF knowledge graphs into object-oriented languages that gives static guarantees about the data access and modularly integrates the mapping between the program and the RDF view with the class definition in the program. This allows us to preserve the separation of concerns between the class system of RDF (geared towards domain modeling and data), and that of the program (geared towards typing and code reuse). Loading of RDF can be performed lazily, when required by the program, based on query-futures – subqueries that are only evaluated if and when the data is accessed. We formulate a Liskov principle for the mapping queries to characterize when they respect the subclass relation. Moreover, we provide tool support to detect when the user-provided mapping would cause the loading mechanisms to result in data structures that manifest the semantic gap.

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  • DOI: 10.1007/978-3-031-06981-9_12
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Fig. 1.
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Fig. 3.

Notes

  1. 1.

    We assume that we can reorder the cycle so that the potential backwards edge is always as index 1. We remind that the anchor variable is always the first answer variable of a link query, so the concatenation is indeed well-defined.

  2. 2.

    We refrain from introducing (a) expressions for resolved futures and (b) lazy loading of the result list. Both is standard and orthogonal to lazy loading within one result.

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Acknowledgments

This work was supported by the RCN via PeTWIN (294600). The authors thank Dirk Walther for motivating this work and the anonymous reviewers for the constructive feedback.

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Authors and Affiliations

  1. Department of Informatics, University of Oslo, Oslo, Norway

    Eduard Kamburjan, Vidar Norstein Klungre & Martin Giese

Authors
  1. Eduard Kamburjan
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  2. Vidar Norstein Klungre
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  3. Martin Giese
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Corresponding author

Correspondence to Eduard Kamburjan .

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Editors and Affiliations

  1. University of Amsterdam, Amsterdam, Noord-Holland, The Netherlands

    Paul Groth

  2. Universidad Simón Bolívar, Leibniz Information Centre for Science and Technology, Hannover, Niedersachsen, Germany

    Maria-Esther Vidal

  3. Institut Polytechnique de Paris "DIG", Télécom ParisTech, Palaiseau, France

    Fabian Suchanek

  4. University of Southern California, Marina del Rey, CA, USA

    Pedro Szekley

  5. IBM Research - Thomas J. Watson Research, Yorktown Heights, NY, USA

    Pavan Kapanipathi

  6. LaSIGE, Fac de Ciencias,Edif C6, Pis0 3, Universidade de Lisboa, Lisbon, Portugal

    Dr. Catia Pesquita

  7. University of Nantes, Nantes, France

    Hala Skaf-Molli

  8. Aalto University, Espoo, Finland

    Minna Tamper

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Kamburjan, E., Klungre, V.N., Giese, M. (2022). Never Mind the Semantic Gap: Modular, Lazy and Safe Loading of RDF Data. In: , et al. The Semantic Web. ESWC 2022. Lecture Notes in Computer Science, vol 13261. Springer, Cham. https://doi.org/10.1007/978-3-031-06981-9_12

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  • DOI: https://doi.org/10.1007/978-3-031-06981-9_12

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