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A Human-Friendly Query Generation Frontend for a Scientific Events Knowledge Graph

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Digital Libraries for Open Knowledge (TPDL 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11799))

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Abstract

Recently, semantic data have become more distributed. Available datasets should serve non-technical as well as technical audience. This is also the case with our EVENTSKG dataset, a comprehensive knowledge graph about scientific events, which serves the entire scientific and library community. A common way to query such data is via SPARQL queries. Non-technical users, however, have difficulties with writing SPARQL queries, because it is a time-consuming and error-prone task, and it requires some expert knowledge. This opens the way to natural language interfaces to tackle this problem by making semantic data more accessible to a wider audience, i.e., not restricted to experts. In this work, we present SPARQL-AG, a human-Friendly front-end that automatically generates and executes SPARQL queries for querying EVENTSKG. SPARQL-AG helps potential semantic data consumers, including non-experts and experts, by generating SPARQL queries, ranging from simple to complex ones, using an interactive web interface. The eminent feature of SPARQL-AG is that users neither need to know the schema of the knowledge graph being queried nor to learn the SPARQL syntax, as SPARQL-AG offers them a familiar and intuitive interface for query generation and execution. It maintains separate clients to query three public SPARQL endpoints when asking for particular entities. The service is publicly available online and has been extensively tested.

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Notes

  1. 1.

    https://dbpedia.org/sparql.

  2. 2.

    http://kddste.sda.tech/SEOontology/sparql.

  3. 3.

    http://kddste.sda.tech/sparql.

  4. 4.

    https://www.drupal.org/.

  5. 5.

    https://www.uniprot.org/.

  6. 6.

    http://wifo5-03.informatik.uni-mannheim.de/bizer/rdfapi/index.html.

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Acknowledgement

This work was co-funded by the European Research Council for the project ScienceGRAPH (Grant agreement ID: 819536).

Author information

Authors and Affiliations

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

    Said Fathalla & 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, Hannover, 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. Christoph Lange
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  3. Sören Auer
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Corresponding author

Correspondence to Said Fathalla .

Editor information

Editors and Affiliations

  1. University of La Rochelle, La Rochelle, France

    Antoine Doucet

  2. VU University Amsterdam, Amsterdam, The Netherlands

    Antoine Isaac

  3. Linnaeus University, Växjö, Sweden

    Koraljka Golub

  4. OsloMet – Oslo Metropolitan University, Oslo, Norway

    Trond Aalberg

  5. Kyoto University, Kyoto, Japan

    Adam Jatowt

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Fathalla, S., Lange, C., Auer, S. (2019). A Human-Friendly Query Generation Frontend for a Scientific Events Knowledge Graph. In: Doucet, A., Isaac, A., Golub, K., Aalberg, T., Jatowt, A. (eds) Digital Libraries for Open Knowledge. TPDL 2019. Lecture Notes in Computer Science(), vol 11799. Springer, Cham. https://doi.org/10.1007/978-3-030-30760-8_18

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  • DOI: https://doi.org/10.1007/978-3-030-30760-8_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-30759-2

  • Online ISBN: 978-3-030-30760-8

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