TraVIS: A User Trace Analyzer to Support User-Centered Design of Visual Analytics Solutions

Visual Analytics (VA) has become a paramount discipline in supporting data analysis in many scientific domains, empowering the human user with automatic capabilities while keeping the lead in the analysis. At the same time, designing an effective VA solution is not a simple task, requiring its adaptation to the problem at hand and the intended user of the system. In this scenario, the User-Centered Design (UCD) methodology provides the framework to incorporate user needs into the design of a VA solution. On the other hand, its implementation mainly relies on qualitative feedback, with the designer missing tools supporting her in quantitatively reporting the user feedback and using it to hypothesize and test the successive changes to the VA solution. To overcome this limitation, we propose TraVIS, a Visual Analytics solution allowing the loading of a web-based VA system, collecting user traces, and analyzing them with respect to the system at hand. In this process, the designer can leverage the collected traces and relate them to the tasks the VA solution supports and how those can be achieved. Using TraVIS, the designer can identify ineffective interaction paths, analyze the user traces support to task completion, hypothesize corrections to the design, and evaluate the effect of changes. We evaluated TraVIS through experimentation with 11 VA systems from literature, a use case, and user evaluation with five experts. Results show the benefits that TraVIS provides in terms of identifying design problems and efficient support for UCD.

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Publication Details

Journal
IEEE Transactions on Visualization and Computer Graphics
Published
2025-03-17
DOI
https://doi.org/10.1109/tvcg.2025.3546863
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
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article

TraVIS: A User Trace Analyzer to Support User-Centered Design of Visual Analytics Solutions

Marco Angelini, Dario Benvenuti, Tiziana Catarci, Alexandra Plexousaki et al.
IEEE Transactions on Visualization and Computer Graphics
Data Visualization and Analytics
article

TraVIS: A User Trace Analyzer to Support User-Centered Design of Visual Analytics Solutions

Marco Angelini, Dario Benvenuti, Tiziana Catarci, Alexandra Plexousaki, Matteo Filosa, Matteo Di Stadio, Francesco Bovi
article en

Abstract

Visual Analytics (VA) has become a paramount discipline in supporting data analysis in many scientific domains, empowering the human user with automatic capabilities while keeping the lead in the analysis. At the same time, designing an effective VA solution is not a simple task, requiring its adaptation to the problem at hand and the intended user of the system. In this scenario, the User-Centered Design (UCD) methodology provides the framework to incorporate user needs into the design of a VA solution. On the other hand, its implementation mainly relies on qualitative feedback, with the designer missing tools supporting her in quantitatively reporting the user feedback and using it to hypothesize and test the successive changes to the VA solution. To overcome this limitation, we propose TraVIS, a Visual Analytics solution allowing the loading of a web-based VA system, collecting user traces, and analyzing them with respect to the system at hand. In this process, the designer can leverage the collected traces and relate them to the tasks the VA solution supports and how those can be achieved. Using TraVIS, the designer can identify ineffective interaction paths, analyze the user traces support to task completion, hypothesize corrections to the design, and evaluate the effect of changes. We evaluated TraVIS through experimentation with 11 VA systems from literature, a use case, and user evaluation with five experts. Results show the benefits that TraVIS provides in terms of identifying design problems and efficient support for UCD.

IEEE Transactions on Visualization and Computer GraphicsVol. 31(10)
University of Crete (GR), FORTH Institute of Computer Science (GR), Link Campus University (IT), Sapienza University of Rome (IT)
Openalex Percentile: Top 96%
Data Visualization and Analytics
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