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 (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