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    We developed Tree Colors, a method mapping tree structures to perceptually balanced colors. This open-source tool aids in visualizing hierarchical data and revealing tree structures in various statistical graphics.

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    Area of Science:

    • Data visualization
    • Perceptual color modeling
    • Statistical graphics

    Background:

    • Categorical data often form classification trees in statistical graphics.
    • Effective visualization of hierarchical data is crucial for data analysis.
    • Existing color mapping methods may not optimally represent tree structures.

    Purpose of the Study:

    • To introduce and detail the Tree Colors method for mapping tree structures to the Hue-Chroma-Luminance color model.
    • To investigate the impact of various parameters on generated color schemes.
    • To evaluate the utility of Tree Colors for visualizing hierarchical and non-hierarchical data.

    Main Methods:

    • Developed a novel method, Tree Colors, mapping tree structures to the Hue-Chroma-Luminance (HCL) color space.
    • Detailed the effects of tunable parameters on resulting color schemes.
    • Provided a free and open-source implementation with default parameter settings.
    • Conducted a user study with participants from a national statistical institute to evaluate the method.

    Main Results:

    • The Tree Colors method effectively maps tree structures to perceptually balanced colors.
    • User study indicates Tree Colors improve node-link diagrams.
    • The method is also effective in revealing underlying tree structures in non-hierarchical visualizations.
    • Parameter tuning allows for customization of color schemes.

    Conclusions:

    • Tree Colors offers a valuable tool for enhancing the visualization of hierarchical data.
    • The method demonstrates utility beyond traditional node-link diagrams, aiding in structure discovery.
    • The open-source implementation promotes accessibility and adoption in statistical graphics.
    • Perceptually balanced color mapping is key for effective data representation.