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    This study introduces a novel dynamic color assignment method for hierarchical data, optimizing color choices for better data visualization and exploration. The approach ensures discriminable and harmonic colors across all levels of data hierarchy.

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    Area of Science:

    • Computer Science
    • Data Visualization
    • Information Visualization

    Background:

    • Effective data visualization relies on discriminable and harmonic color assignments for class labels and spatial distribution.
    • Increasing numbers of classes pose challenges for simultaneous high-quality color assignment in data exploration.
    • Existing methods struggle with dynamic color assignment aligned to hierarchical data structures.

    Purpose of the Study:

    • To develop a dynamic color assignment method for hierarchical data that addresses limitations of current approaches.
    • To generate high-quality color assignments that are simultaneously discriminable, harmonic, and spatially aware.
    • To ensure consistency and clarity across hierarchical levels through parent-guided color assignment.

    Main Methods:

    • Formulated dynamic color assignment as a multi-objective optimization problem.
    • Simultaneously optimized for color discriminability, color harmony, and spatial distribution at each hierarchical level.
    • Employed parent class colors to guide child class color assignment, ensuring cross-level consistency.

    Main Results:

    • Demonstrated the effectiveness of the proposed method in generating dynamic color assignments for hierarchical data.
    • Quantitative experiments validated the quality and utility of the generated color assignments.
    • A user study confirmed the method's ability to enhance data exploration and visualization.

    Conclusions:

    • The developed dynamic color assignment method effectively addresses the challenges of visualizing hierarchical data.
    • The approach promotes improved data exploration through consistent and clear hierarchical colorings.
    • This method offers a significant advancement in the field of information visualization for complex datasets.