Guidelines
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Test the palette with a color-vision simulator

For charts that rely on color differences, use color-vision simulation on the chosen palette to improve accessibility and mitigate undetected color collisions for readers with color-vision deficiency.

  • purpose:refine
  • basis:heuristic
  • quality:accessibility
  • lever:encoding
  • needs:color-vision-deficiency
  • polish:palette

advice

Simulate color-vision deficiencies

Test the palette with a color-vision simulator before publishing. For example, preview the same colors under different types of colorblindness and revise color pairs that collapse together.

reason

Why simulation is necessary

A palette can look distinct to the designer and still fail for readers with color-vision deficiencies. Simulation exposes those collisions before the chart is published.

Mechanism: Viewing the palette through color-vision simulations shows whether readers who perceive color differently can still distinguish the encoded differences.

Evidence: The post recommends checking whether chosen colors can be distinguished by colorblind people and lists simulators that show how colors appear for different types of colorblindness (https://www.datawrapper.de/blog/colorguide">Muth, 2018).

context

Use when color differences carry meaning

  • User Goal: Keep color-coded distinctions readable for more readers.
  • Task: Validate whether series, categories, or value steps remain separable.
  • Data: Any data encoded with multiple meaningful colors.
  • Chart Setting: The chart depends on color differences to communicate distinctions.
  • Audience: Readers may include people with different types of color-vision deficiency.
  • Success Criterion: The encoded colors remain distinguishable in simulation.

exceptions

Do not use when color is not carrying the distinction

Break it when: The chart does not rely on color differences for interpretation. Why: There are no meaningful color distinctions to validate.

costs

Tradeoffs of simulation review

Sacrifice: You add a review step to the palette workflow.
Risk: A palette that looks fine in normal vision may merge in simulated views.
Mitigation: Run the simulation while choosing colors, not only at the end.

mistakes

Common misuse of accessible palettes

Mistake: Judging the palette only in normal vision. Why it fails: It hides color collisions that some readers will experience.

check

Check whether colors collapse in simulation

Failure Sign: Two or more encoded colors become hard to tell apart in the simulation.
Quick Check: Run the palette through one color-vision simulator.
Stronger Test: Check the palette under multiple simulated types of colorblindness.

fix

Fix color collisions

  • Replace colors that merge under simulation.
  • Increase separation between colors that become similar.
  • Re-run the simulator after each palette revision.

References

Muth, L. C. (2018). Your friendly guide to colors in data visualisation. https://www.datawrapper.de/blog/colorguide