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KG-Visual: A Tool for Visualizing RDF Knowledge Graphs

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Metadata and Semantic Research (MTSR 2021)

Abstract

RDF Knowledge graphs are semantic networks to infer information from data based on RDF triples using SPARQL queries. Querying RDF Knowledge graphs using visualization allows different views of the graph and provides more insights. A new visualization tool, KG-Visual is developed in this paper using Python dashboard, JavaScript and RDF libraries. This tool tackles the limitations of existing tools by providing a customizable and reliable visualization for RDF knowledge graphs. In addition to the essential functionalities such as search, drag and drop nodes, zoom-in and zoom-out over a knowledge graph, the tool holds the capability to run SPARQL queries and visualize the results on the knowledge graph, which makes this open-source tool a potential candidate amongst most RDF visualization tools.

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Notes

  1. 1.

    https://github.com/Devanshika/RDF-SPARQL-Visualization.

  2. 2.

    https://neo4j.com/product/bloom/.

  3. 3.

    https://visjs.github.io/vis-network/docs/network/physics.html.

  4. 4.

    https://github.com/Devanshika/RDF-SPARQL-Visualization/blob/master/data.ttl.

  5. 5.

    http://data.novascotia.ca.

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Acknowledgement

The work conducted in the study has been funded by NSERC (Natural Sciences and Engineering Research Council) Discovery Grant (RGPIN-2020-05869).

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Correspondence to Devanshika Ghosh .

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Ghosh, D., Rajabi, E. (2022). KG-Visual: A Tool for Visualizing RDF Knowledge Graphs. In: Garoufallou, E., Ovalle-Perandones, MA., Vlachidis, A. (eds) Metadata and Semantic Research. MTSR 2021. Communications in Computer and Information Science, vol 1537. Springer, Cham. https://doi.org/10.1007/978-3-030-98876-0_11

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  • DOI: https://doi.org/10.1007/978-3-030-98876-0_11

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-98875-3

  • Online ISBN: 978-3-030-98876-0

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