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SPARQLVis: An Interactive Visualization Tool for Knowledge Graphs

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Web and Big Data (APWeb-WAIM 2018)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 10987))

Abstract

With the rapid development of knowledge graphs, an increasingly large volume of RDF graph data has been published on the Web. However, those data cannot be well consumed because most users have no background knowledge about SPARQL, a structural query language for RDF database. To increase the availability of knowledge graphs, we developed an interactive visualization tool for multiple SPARQL endpoints. We as well introduced advanced features like pattern matching and property path query to enhance its functionality.

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References

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (61572353), the Natural Science Foundation of Tianjin (17JCYBJC15400), and the National Training Programs of Innovation and Entrepreneurship for Undergraduates (201710056091).

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Authors and Affiliations

  1. School of Computer Science and Technology, Tianjin University, Tianjin, China

    Chaozhou Yang, Xin Wang, Qiang Xu & Weixi Li

  2. Tianjin Key Laboratory of Cognitive Computing and Application, Tianjin, China

    Chaozhou Yang, Xin Wang, Qiang Xu & Weixi Li

Authors
  1. Chaozhou Yang
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  2. Xin Wang
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  3. Qiang Xu
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  4. Weixi Li
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Corresponding author

Correspondence to Xin Wang .

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Editors and Affiliations

  1. South China University of Technology, Guangzhou, China

    Yi Cai

  2. Nagoya University, Nagoya, Japan

    Yoshiharu Ishikawa

  3. Hong Kong Baptist University, Kowloon Tong, Hong Kong, China

    Jianliang Xu

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Yang, C., Wang, X., Xu, Q., Li, W. (2018). SPARQLVis: An Interactive Visualization Tool for Knowledge Graphs. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10987. Springer, Cham. https://doi.org/10.1007/978-3-319-96890-2_41

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  • DOI: https://doi.org/10.1007/978-3-319-96890-2_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-96889-6

  • Online ISBN: 978-3-319-96890-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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