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SJoin: A Semantic Join Operator to Integrate Heterogeneous RDF Graphs

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Database and Expert Systems Applications (DEXA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10438))

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Abstract

Semi-structured data models like the Resource Description Framework (RDF), naturally allow for modeling the same real-world entity in various ways. For example, different RDF vocabularies enable the definition of various RDF graphs representing the same drug in Bio2RDF or Drugbank. Albeit semantically equivalent, these RDF graphs may be syntactically different, i.e., they have distinctive graph structure or entity identifiers and properties. Existing data-driven integration approaches only consider syntactic matching criteria or similarity measures to solve the problem of integrating RDF graphs. However, syntactic-based approaches are unable to semantically integrate heterogeneous RDF graphs. We devise SJoin, a semantic similarity join operator to solve the problem of matching semantically equivalent RDF graphs, i.e., syntactically different graphs corresponding to the same real-world entity. Two physical implementations are proposed for SJoin which follow blocking or non-blocking data processing strategies, i.e., RDF graphs can be merged in a batch or incrementally. We empirically evaluate the effectiveness and efficiency of the SJoin physical operators with respect to baseline similarity join algorithms. Experimental results suggest that SJoin outperforms baseline approaches, i.e., non-blocking SJoin incrementally produces results faster, while the blocking SJoin accurately matches all semantically equivalent RDF graphs.

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Notes

  1. 1.

    http://data.un.org/.

  2. 2.

    http://stats.lod2.eu/.

  3. 3.

    Prefixes are as specified on http://prefix.cc/.

  4. 4.

    https://github.com/RDF-Molecules/Test-DataSets/tree/master/DBpedia-People/20160819.

  5. 5.

    https://github.com/RDF-Molecules/Test-DataSets/tree/master/DBpedia-WikiData/operators_evaluation.

  6. 6.

    https://github.com/RDF-Molecules/operators/tree/master/mFuhsion.

  7. 7.

    https://github.com/RDF-Molecules/operators/tree/master/baseline_ops.

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Acknowledgments

Mikhail Galkin is supported by the project Open Budgets (GA 645833). This work is also funded in part by the European Union under the Horizon 2020 Framework Program for the project BigDataEurope (GA 644564), and the German Ministry of Education and Research with grant no. 13N13627 (LiDaKra).

Author information

Authors and Affiliations

  1. Enterprise Information Systems (EIS), University of Bonn, Bonn, Germany

    Mikhail Galkin, Diego Collarana & Sören Auer

  2. Fraunhofer Institute for Intelligent Analysis and Information Systems (IAIS), Sankt Augustin, Germany

    Mikhail Galkin, Diego Collarana, Maria-Esther Vidal & Sören Auer

  3. FZI Research Center for Information Technology, Karlsruhe, Germany

    Ignacio Traverso-Ribón

  4. Universidad Simón Bolívar, Caracas, Venezuela

    Maria-Esther Vidal

  5. ITMO University, Saint Petersburg, Russia

    Mikhail Galkin

Authors
  1. Mikhail Galkin
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  2. Diego Collarana
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  3. Ignacio Traverso-Ribón
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  4. Maria-Esther Vidal
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  5. Sören Auer
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Corresponding author

Correspondence to Mikhail Galkin .

Editor information

Editors and Affiliations

  1. University of Lyon, Villeurbanne, France

    Djamal Benslimane

  2. University of Milan, Milan, Italy

    Ernesto Damiani

  3. University of Michigan, Dearborn, Michigan, USA

    William I. Grosky

  4. Paul Sabatier University, Toulouse, France

    Abdelkader Hameurlain

  5. Wright State University, Dayton, Ohio, USA

    Amit Sheth

  6. Johannes Kepler University, Linz, Austria

    Roland R. Wagner

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Galkin, M., Collarana, D., Traverso-Ribón, I., Vidal, ME., Auer, S. (2017). SJoin: A Semantic Join Operator to Integrate Heterogeneous RDF Graphs. In: Benslimane, D., Damiani, E., Grosky, W., Hameurlain, A., Sheth, A., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2017. Lecture Notes in Computer Science(), vol 10438. Springer, Cham. https://doi.org/10.1007/978-3-319-64468-4_16

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  • DOI: https://doi.org/10.1007/978-3-319-64468-4_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-64467-7

  • Online ISBN: 978-3-319-64468-4

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