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Towards a Quality Approach to Hierarchical Color Maps

Tobias Mertz, Jörn Kohlhammer

TL;DR

The paper tackles the challenge of evaluating and designing hierarchical color maps, arguing that standard one- and two-dimensional color-map rules do not directly apply. It adopts the HCL color space and analyzes several hierarchical color-map approaches, with Tree Colors as a central example, to translate design rules into hierarchical contexts and to consider top-down versus bottom-up analysis. The contributions include translating color-map design rules to hierarchical maps, outlining how analysis focus affects design decisions, and proposing adjustments to Tree Colors to improve quality under various conditions, thereby laying groundwork for objective quality criteria and future quantitative benchmarking. The work provides guidance for designing hierarchical color maps and highlights the need for benchmarks and additional rule translations to support broader applicability and evaluation across diverse hierarchies.

Abstract

To improve the perception of hierarchical structures in data sets, several color map generation algorithms have been proposed to take this structure into account. But the design of hierarchical color maps elicits different requirements to those of color maps for tabular data. Within this paper, we make an initial effort to put design rules from the color map literature into the context of hierarchical color maps. We investigate the impact of several design decisions and provide recommendations for various analysis scenarios. Thus, we lay the foundation for objective quality criteria to evaluate hierarchical color maps.

Towards a Quality Approach to Hierarchical Color Maps

TL;DR

The paper tackles the challenge of evaluating and designing hierarchical color maps, arguing that standard one- and two-dimensional color-map rules do not directly apply. It adopts the HCL color space and analyzes several hierarchical color-map approaches, with Tree Colors as a central example, to translate design rules into hierarchical contexts and to consider top-down versus bottom-up analysis. The contributions include translating color-map design rules to hierarchical maps, outlining how analysis focus affects design decisions, and proposing adjustments to Tree Colors to improve quality under various conditions, thereby laying groundwork for objective quality criteria and future quantitative benchmarking. The work provides guidance for designing hierarchical color maps and highlights the need for benchmarks and additional rule translations to support broader applicability and evaluation across diverse hierarchies.

Abstract

To improve the perception of hierarchical structures in data sets, several color map generation algorithms have been proposed to take this structure into account. But the design of hierarchical color maps elicits different requirements to those of color maps for tabular data. Within this paper, we make an initial effort to put design rules from the color map literature into the context of hierarchical color maps. We investigate the impact of several design decisions and provide recommendations for various analysis scenarios. Thus, we lay the foundation for objective quality criteria to evaluate hierarchical color maps.
Paper Structure (14 sections, 2 figures, 1 table)

This paper contains 14 sections, 2 figures, 1 table.

Table of Contents

  1. Introduction
  2. The HCL Color Space
  3. Related Work
  4. Color Map Quality
  5. Hierarchical Color Maps
  6. Quality Considerations
  7. Order
  8. Discriminative Power
  9. Uniformity
  10. Equal Visual Importance
  11. Background Sensitivity
  12. Device Independence
  13. Observations
  14. Conclusion

Figures (2)

  • Figure 1: Comparison of even (a) and proportional (b) hue split variants in imbalanced hierarchies. Sizes of arc segments indicate the range of hues assigned to each node.
  • Figure 2: Comparison of global (a) and local (b) interpolation variants for chroma and luminance in imbalanced hierarchies. Interpolation factors of individual nodes are written inside the nodes and encoded by their vertical position.