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A Task-Based View on the Visual Analysis of Eye-Tracking Data

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Book cover Eye Tracking and Visualization (ETVIS 2015)

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Abstract

The visual analysis of eye movement data has become an emerging field of research leading to many new visualization techniques in recent years. These techniques provide insight beyond what is facilitated by traditional attention maps and gaze plots, providing important means to support statistical analysis and hypothesis building. There is no single “all-in-one” visualization to solve all possible analysis tasks. In fact, the appropriate choice of a visualization technique depends on the type of data and analysis task. We provide a taxonomy of analysis tasks that is derived from literature research of visualization techniques and embedded in our pipeline model of eye-tracking visualization. Our task taxonomy is linked to references to representative visualization techniques and, therefore, it is a basis for choosing appropriate methods of visual analysis. We also elaborate on how far statistical analysis with eye-tracking metrics can be enriched by suitable visualization and visual analytics techniques to improve the extraction of knowledge during the analysis process.

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Acknowledgements

This work was partially supported by the German Research Foundation (DFG) within the Cluster of Excellence in Simulation Technology (EXC 310) at the University of Stuttgart. This work was supported in part by EU in projects datAcron (grant agreement 687591) and VaVeL (grant agreement 688380).

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Authors and Affiliations

  1. University of Stuttgart, Allmandring 19, 70569, Stuttgart, Germany

    Kuno Kurzhals, Michael Burch & Daniel Weiskopf

  2. University of Stuttgart, Universitätsstr. 38, 70569, Stuttgart, Germany

    Tanja Blascheck

  3. Fraunhofer Institute IAIS, Schloss Birlinghoven, 53757, Sankt Augustin, Germany

    Gennady Andrienko & Natalia Andrienko

  4. City University London, London EC1V OHB, London, UK

    Gennady Andrienko

Authors
  1. Kuno Kurzhals
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  2. Michael Burch
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  4. Gennady Andrienko
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  5. Natalia Andrienko
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  6. Daniel Weiskopf
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Corresponding author

Correspondence to Kuno Kurzhals .

Editor information

Editors and Affiliations

  1. VISUS, University of Stuttgart, Stuttgart, Germany

    Michael Burch

  2. Max Planck Institute for Biological Cybernetics, Tübingen, Germany

    Lewis Chuang

  3. SIAT, Simon Fraser University, Surrey, British Columbia, Canada

    Brian Fisher

  4. VIS, University of Stuttgart, Stuttgart, Germany

    Albrecht Schmidt

  5. VISUS, University of Stuttgart, Stuttgart, Germany

    Daniel Weiskopf

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Kurzhals, K., Burch, M., Blascheck, T., Andrienko, G., Andrienko, N., Weiskopf, D. (2017). A Task-Based View on the Visual Analysis of Eye-Tracking Data. In: Burch, M., Chuang, L., Fisher, B., Schmidt, A., Weiskopf, D. (eds) Eye Tracking and Visualization. ETVIS 2015. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-47024-5_1

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