Guidelines
Suggest edit

Use color hue instead of shape to encode nominal categories

For category differentiation in color-capable static charts with categorical data, prefer color hue encoding on marks to improve fidelity and mitigate weak group separation for readers identifying categories.

  • purpose:refine
  • basis:empirical
  • data:categorical
  • quality:fidelity
  • lever:encoding
  • channel:color-hue:use
  • channel:shape:avoid

advice

Hue encoding for category identity

Encode the nominal field with color hue instead of shape when distinct colors are available. For example, distinguish groups by different hues rather than by changing point or mark shapes for the same categorical field.

reason

Why hue works better than shape here

Nominal data needs readers to tell categories apart without implying order. Distinct hues provide a stronger nominal encoding than shape for that job.

Mechanism: Color hue separates categories more effectively than shape for the same nominal field.

Evidence: The collated knowledge records Mackinlay’s nominal effectiveness ranking as positionX = positionY > color-hue > texture > color-saturation > shape > length > angle > orientation > area, so color hue is the stronger encoding choice over shape for nominal data (Zeng & Battle, 2023; Mackinlay, 1986).

context

Use when the output can show color

  • User Goal: Distinguish categories accurately.
  • Data: One categorical field with no intrinsic order is being assigned to a visual channel.
  • Chart Setting: A static 2D chart with marks is being designed, and the output medium can show color.
  • Success Criterion: Readers can tell categories apart directly from the marks.

exceptions

Do not use when color is unavailable

Break it when: The output medium is monochrome or cannot reliably show color. Why: This guideline depends on color hue being available as the encoding channel.

costs

Costs of moving the field to hue

Sacrifice: Hue uses the color channel. Risk: If color is unavailable, the rule cannot be applied directly. Mitigation: Use another nominal channel only after color has been ruled out by the medium.

mistakes

Common failure around this choice

Mistake: Distinguish the main categories only with shapes when distinct hues are available. Why it fails: It leaves the nominal field on a lower-ranked channel than hue.

check

Check the encoding decision directly

Failure Sign: Readers must inspect mark shapes to tell categories apart. Quick Check: Recolor the same categories with distinct hues and see whether the grouping can be read without inspecting shapes. Stronger Test: If the hue version expresses the same grouping, keep hue and simplify the shapes.

fix

Fix the channel assignment

  • Map the categorical field to distinct hues.
  • Return marks to a common shape when shape no longer carries the grouping.
  • If color is not available, move the grouping to another nominal channel rather than leaving the design dependent on hue.

References

Mackinlay, J. (1986). Automating the design of graphical presentations of relational information. ACM Transactions on Graphics, 5(2), 110–141. https://doi.org/10.1145/22949.22950
Zeng, Z., & Battle, L. (2023). A Review and Collation of Graphical Perception Knowledge for Visualization Recommendation. Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3544548.3581349