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International Conference on Theory and Practice of Digital Libraries

TPDL 2017: Research and Advanced Technology for Digital Libraries pp 328–341Cite as

Integration of Scholarly Communication Metadata Using Knowledge Graphs

Part of the Lecture Notes in Computer Science book series (LNISA,volume 10450)

Abstract

Important questions about the scientific community, e.g., what authors are the experts in a certain field, or are actively engaged in international collaborations, can be answered using publicly available datasets. However, data required to answer such questions is often scattered over multiple isolated datasets. Recently, the Knowledge Graph (KG) concept has been identified as a means for interweaving heterogeneous datasets and enhancing answer completeness and soundness. We present a pipeline for creating high quality knowledge graphs that comprise data collected from multiple isolated structured datasets. As proof of concept, we illustrate the different steps in the construction of a knowledge graph in the domain of scholarly communication metadata (SCM-KG). Particularly, we demonstrate the benefits of exploiting semantic web technology to reconcile data about authors, papers, and conferences. We conducted an experimental study on an SCM-KG that merges scientific research metadata from the DBLP bibliographic source and the Microsoft Academic Graph. The observed results provide evidence that queries are processed more effectively on top of the SCM-KG than over the isolated datasets, while execution time is not negatively affected.

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  • DOI: 10.1007/978-3-319-67008-9_26
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Fig. 1.
Fig. 2.
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Notes

  1. 1.

    http://dblp.l3s.de/dblp++.php, accessed on 10 April 2017.

  2. 2.

    https://academicgraphwe.blob.core.windows.net/graph-2016-02-05 accessed on 10 April 2017.

  3. 3.

    http://www.sparontologies.net/.

  4. 4.

    http://www.scholarlydata.org.

  5. 5.

    http://opencitations.net/.

  6. 6.

    http://lod.openaire.eu.

  7. 7.

    https://scrapy.org, accessed on 5 April 2017.

  8. 8.

    SWRC: http://ontoware.org/swrc, FOAF: http://xmlns.com/foaf/spec/.

  9. 9.

    Here, a “molecule” refers to a set of one node in the knowledge graph and the immediate links to its neighbors.

  10. 10.

    The integrated WWW dataset has 346,480 triples including the “same as” links between matched instances.

  11. 11.

    http://dblp.l3s.de/d2r/sparql.

  12. 12.

    In the process of linking articles by an author, true positives (TP) are articles whose metadata exist in both DBLP and MAG and their instances are correctly linked in the matching step.

  13. 13.

    http://afshn.com/re/scmkg.html, accessed on 5 April 2017.

  14. 14.

    http://afshn.com/re/oscoss.html.

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Acknowledgments

This work has been partially funded by the European Commission under grant agreements 643410 (OpenAIRE2020) and 644564 (BigDataEurope), and the DFG under grant agreement AU 340/9-1 (OSCOSS).

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Authors and Affiliations

  1. Smart Data Analytics (SDA), University of Bonn, Bonn, Germany

    Afshin Sadeghi & Christoph Lange

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

    Christoph Lange & Maria-Esther Vidal

  3. Computer Science, Leibniz University of Hannover, Hannover, Germany

    Sören Auer

  4. TIB Leibniz Information Center for Science and Technology, Hannover, Germany

    Sören Auer

Authors
  1. Afshin Sadeghi
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  2. Christoph Lange
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  3. Maria-Esther Vidal
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  4. Sören Auer
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Corresponding author

Correspondence to Afshin Sadeghi .

Editor information

Editors and Affiliations

  1. Faculteit der Geesteswetenschappen, Universiteit van Amsterdam , Amsterdam, The Netherlands

    Jaap Kamps

  2. Library & Information Center, University of Patras , Patras, Greece

    Dr. Giannis Tsakonas

  3. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Prof. Yannis Manolopoulos

  4. Civil Engineering, University of Thrace , Kimmeria, Greece

    Lazaros Iliadis

  5. Informatics, Ionian University , Kerkyra, Greece

    Ioannis Karydis

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Sadeghi, A., Lange, C., Vidal, ME., Auer, S. (2017). Integration of Scholarly Communication Metadata Using Knowledge Graphs. In: Kamps, J., Tsakonas, G., Manolopoulos, Y., Iliadis, L., Karydis, I. (eds) Research and Advanced Technology for Digital Libraries. TPDL 2017. Lecture Notes in Computer Science(), vol 10450. Springer, Cham. https://doi.org/10.1007/978-3-319-67008-9_26

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  • DOI: https://doi.org/10.1007/978-3-319-67008-9_26

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