Estimated reading time: 3 minutes

Summary

Colours need to be accessible
There are tools that can help you evaluate your colour choices and make your visualisations more inclusive

Once you have decided to use colour, taken into account established practices, physical conditions, cultural significance and aesthetics, and from there selected a colour scale or palette that suits your purposes, there is one more detail to consider: accessibility.

Let's take the rainbow scale, or jet scale, as an example. Below is an image that uses a rainbow-coloured palette to represent variations in topographic information on a volcano:

Visualisation of volcano eruption data, using a rainbow colour palette.

Visualisation of topographic information on the Maungawhau volcano, using a rainbow colour palette. Data source: R Core Team (2022). Topographic Information on Auckland's Maunga Whau Volcano. R Foundation for Statistical Computing. Dataset. https://www.R-project.org/.

Using palettes such as the rainbow/jet color scale has long been popular in scientific communication. However, arguments against this practice are becoming more vocal, mostly because of concerns around accessibility, distortion and misrepresentation of data, and the difficulties of logically describing quantity using colour. Because of this, modern applications of, and alternatives to, this famous multicolour palette have been proposed.

Seeing colour differently

In order for your visualisation to be as effective as possible, it is important that the colours you've chosen, or rather the differences between the colours you've chosen, are distinguishable and adequately perceived. It is also necessary to take into account those viewers who perceive colour differently.

There are several variants of so-called defective colour vision. Depending on which variant is present, different colours may be perceived either very differently or not at all. If you want to get a better understanding of how differently colour might be perceived, try for example Coblis, an online tool that simulates different colour vision deficiencies.

Let's use our rainbow-coloured visualisation on volcano data as an example. Below are three simulations in Coblis of what the very same image might look like for persons with colour vision deficiency (keep in mind, however, that we all have a unique way of perceiving colour and that simulation tools are only simulations; they do not produce a definitive representation of how your audience will perceive your image in real life).

Someone with protanopia, i.e. red-blind colour vision deficiency, might perceive the volcano data visualisation like this:

Coblis simulation of how a person with protanopia might perceive a rainbow-coloured visualisation of volcano data.

Someone with deuteranopia; i.e. green-blind colour vision deficiency; might perceive it like this:

Coblis simulation of how a person with deuteranopia might perceive a rainbow-coloured visualisation of volcano data.

Someone with tritanopia, i.e. blue-blind colour vision deficiency, might instead perceive it like this:

Coblis simulation of how a person with tritanopia might perceive a rainbow-coloured visualisation of volcano data.

When comparing these simulation images with the original, the contours and size of some areas appear less clear in the simulations. Hence, when using the rainbow colour scale, parts of your data might not be accurately represented for some of your viewers.

Contrast

Contrast is another important aspect of accessibility. The World Wide Web Consortium (W3C) has developed recommendations for contrast limits meant to ensure digital accessibility in browser-based material.

There are many tools available that will allow you to test the contrast between two colours, such as coloured text against a coloured background. These will then tell you if and how well the combination meets the W3C guidelines.

Below are some tools (in no particular order) that might help you make more inclusive choices regarding colour and text size:

Color Contrast Checker Analyzer Tool by Adobe
Colour Contrast Analyzer (CCA) by TPGi
Contrast Checker by the WebAIM organization
Contrast Ratio by Lea Verou
Colour Contrast Checker by Alex Clapperton

Recommended reading

On colour blindness and data visualisation:

Lisa Charlotte Muth,

Part 1: How your colorblind and colorweak readers see your colors
Part 2: What to consider when visualizing data for colorblind readers
Part 3: What’s it like to be colorblind

In the next module, Accessible visualisation, you will learn more about how to make your visualisation as accessible as possible.