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Hierarchical Sankey Diagram: Design and Evaluation

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Advances in Visual Computing (ISVC 2021)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 13018))

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Abstract

We present the hierarchical Sankey diagram that aims to augment the original Sankey diagram by enabling users to examine inflow links and levels of detail through four different variants. We provide the details of our design along with results on a student course performance dataset. Finally, the effectiveness of the four variants for the hierarchical Sankey diagram is evaluated via a user study.

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Acknowledgments

This research was supported in part by the U.S. National Science Foundation through grants IIS-1455886, DUE-1833129, IIS-1955395, IIS-2101696, and OAC-2104158. The authors would like to thank the anonymous reviewers for their helpful comments.

Author information

Authors and Affiliations

  1. University of Notre Dame, Notre Dame, USA

    William P. Porter, Conor P. Murphy, Dane R. Williams, Brendan J. O’Handley & Chaoli Wang

Authors
  1. William P. Porter
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  2. Conor P. Murphy
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  3. Dane R. Williams
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  4. Brendan J. O’Handley
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  5. Chaoli Wang
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Corresponding author

Correspondence to William P. Porter .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, NV, USA

    George Bebis

  2. University of Texas at Arlington, Arlington, TX, USA

    Vassilis Athitsos

  3. University of South Carolina, Columbia, SC, USA

    Tong Yan

  4. City University of Hong Kong, Kowloon, Hong Kong

    Manfred Lau

  5. School of Engineering and Computing, University of Durham, Durham, Durham, UK

    Frederick Li

  6. Airbnb, New York, NY, USA

    Conglei Shi

  7. Peking University, Beijing, China

    Xiaoru Yuan

  8. Purdue University, West Lafayette, IN, USA

    Christos Mousas

  9. IST, School of Modeling, Simulation, and Training, Orlando, FL, USA

    Gerd Bruder

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Cite this paper

Porter, W.P., Murphy, C.P., Williams, D.R., O’Handley, B.J., Wang, C. (2021). Hierarchical Sankey Diagram: Design and Evaluation. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2021. Lecture Notes in Computer Science(), vol 13018. Springer, Cham. https://doi.org/10.1007/978-3-030-90436-4_31

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  • DOI: https://doi.org/10.1007/978-3-030-90436-4_31

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-90435-7

  • Online ISBN: 978-3-030-90436-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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