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Towards a Knowledge Graph Representing Research Findings by Semantifying Survey Articles

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Research and Advanced Technology for Digital Libraries (TPDL 2017)

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

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Abstract

Despite significant advances in technology, the way how research is done and especially communicated has not changed much. We have the vision that ultimately researchers will work on a common knowledge base comprising comprehensive descriptions of their research, thus making research contributions transparent and comparable. The current approach for structuring, systematizing and comparing research results is via survey or review articles. In this article, we describe how surveys for research fields can be represented in a semantic way, resulting in a knowledge graph that describes the individual research problems, approaches, implementations and evaluations in a structured and comparable way. We present a comprehensive ontology for capturing the content of survey articles. We discuss possible applications and present an evaluation of our approach with the retrospective, exemplary semantification of a survey. We demonstrate the utility of the resulting knowledge graph by using it to answer queries about the different research contributions covered by the survey and evaluate how well the query answers serve readers’ information needs, in comparison to having them extract the same information from reading a survey paper.

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Notes

  1. 1.

    http://lod.springer.com/.

  2. 2.

    http://data.semanticweb.org/.

  3. 3.

    http://www.scholarlydata.org/dumps/.

  4. 4.

    http://openresearch.org; prefix (or).

  5. 5.

    Linked Open Vocabularies: http://lov.okfn.org/dataset/lov/vocabs.

  6. 6.

    Dublin Core Metadata Initiative: http://dublincore.org/.

  7. 7.

    Namespace look-up tool for RDF developers: http://prefix.cc/.

  8. 8.

    http://openresearch.org/ANAPSID:_An_Adaptive_Query_Processing_Engine_for_ SPARQL_Endpoints.

  9. 9.

    https://goo.gl/eZC4UL.

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Acknowledgments

This work has been supported by the H2020 project no. 645833 (OpenBudgets.eu). The authors would like to thank Prof. Maria-Esther Vidal and Afshin Sadeghi for their support. We also appreciate the help of all participants of the evaluation. This work was conducted using the Protégé resource, which is supported by grant GM10331601 from the National Institute of General Medical Sciences of the United States National Institutes of Health.

Author information

Authors and Affiliations

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

    Said Fathalla, Sahar Vahdati & Christoph Lange

  2. Fraunhofer IAIS, Sankt Augustin, Germany

    Christoph Lange

  3. Faculty of Science, Alexandria University, Alexandria, Egypt

    Said Fathalla

  4. Computer Science, Leibniz University of Hannover, Hanover, Germany

    Sören Auer

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

    Sören Auer

Authors
  1. Said Fathalla
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  2. Sahar Vahdati
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  3. Sören Auer
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  4. Christoph Lange
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Corresponding author

Correspondence to Said Fathalla .

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

    Giannis Tsakonas

  3. Aristotle University of Thessaloniki , Thessaloniki, Greece

    Yannis Manolopoulos

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

    Lazaros Iliadis

  5. Informatics, Ionian University , Kerkyra, Greece

    Ioannis Karydis

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Fathalla, S., Vahdati, S., Auer, S., Lange, C. (2017). Towards a Knowledge Graph Representing Research Findings by Semantifying Survey Articles. 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_25

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  • DOI: https://doi.org/10.1007/978-3-319-67008-9_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67007-2

  • Online ISBN: 978-3-319-67008-9

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