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Exploring Tabular Data Through Networks

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Advances in Information Retrieval (ECIR 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13982))

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Abstract

Representing and visualizing data as networks is a widely spread approach to analyzing highly connected data in domains such as medicine, social sciences, and information retrieval. Investigating data as networks requires pre-processing, retrieval or filtering, conversion of data into networks, and application of various network analysis approaches. These processes are usually complex and hard to perform without some programming knowledge and resources. To the best of our knowledge, most solutions attempting to make these functionalities accessible to users focus on particular processes in isolation without exploring how these processes could be further abstracted or combined in a real-world application to assist users in their data exploration and knowledge extraction journey. Furthermore, most applications focusing on such approaches tend to be closed-source. This paper introduces a solution that combines the approaches above as part of Collaboration Spotting X (CSX), an open-source network-based visual analytics tool for retrieving, modeling, and exploring or analyzing data as networks. It abstracts the concepts above through the use of multiple interactive visualizations. In addition to being an easily accessible open-source platform for data exploration and analysis, CSX can also serve as a real-world evaluation platform for researchers in related computer science areas who wish to test their solutions and approaches to machine learning, visualizations, interactions, and more in a real-world system.

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Notes

  1. 1.

    https://github.com/aleksbobic/csx.

  2. 2.

    https://youtu.be/TwSA6nVkdec.

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Authors and Affiliations

  1. IPT Department, CERN, Geneva, Switzerland

    Aleksandar Bobic & Jean-Marie Le Goff

  2. CoDiS Lab ISDS, Graz University of Technology, Graz, Austria

    Aleksandar Bobic & Christian Gütl

Authors
  1. Aleksandar Bobic
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  2. Jean-Marie Le Goff
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  3. Christian Gütl
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Corresponding author

Correspondence to Aleksandar Bobic .

Editor information

Editors and Affiliations

  1. University of Amsterdam, Amsterdam, The Netherlands

    Jaap Kamps

  2. Université Grenoble-Alpes, Saint-Martin-d’Hères, France

    Lorraine Goeuriot

  3. Università della Svizzera Italiana, Lugano, Switzerland

    Fabio Crestani

  4. University of Copenhagen, Copenhagen, Denmark

    Maria Maistro

  5. University of Tsukuba, Ibaraki, Japan

    Hideo Joho

  6. Dublin City University, Dublin, Ireland

    Brian Davis

  7. Dublin City University, Dublin, Ireland

    Cathal Gurrin

  8. Universität Regensburg, Regensburg, Germany

    Udo Kruschwitz

  9. Dublin City University, Dublin, Ireland

    Annalina Caputo

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Bobic, A., Le Goff, JM., Gütl, C. (2023). Exploring Tabular Data Through Networks. In: Kamps, J., et al. Advances in Information Retrieval. ECIR 2023. Lecture Notes in Computer Science, vol 13982. Springer, Cham. https://doi.org/10.1007/978-3-031-28241-6_13

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  • DOI: https://doi.org/10.1007/978-3-031-28241-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-28240-9

  • Online ISBN: 978-3-031-28241-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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