Misuse of the rainbow color scheme to visualize scientific data

Fabio Crameri, Grace Shephard, and Philip Heron in Nature discuss the drawbacks of using the rainbow color scheme to visualize data and more readable alternatives:

The accurate representation of data is essential in science communication. However, colour maps that visually distort data through uneven colour gradients or are unreadable to those with colour-vision deficiency remain prevalent in science. These include, but are not limited to, rainbow-like and red–green colour maps. Here, we present a simple guide for the scientific use of colour. We show how scientifically derived colour maps report true data variations, reduce complexity, and are accessible for people with colour-vision deficiencies. We highlight ways for the scientific community to identify and prevent the misuse of colour in science, and call for a proactive step away from colour misuse among the community, publishers, and the press.

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Alternatives to the rainbow color scale

Oh. It’s that time of year already. Time to hate on the rainbow color scale, which is still prevalent but equally less useful than alternatives. Matt Hall provides (scientific!) reasons for looking to scales that don’t include the full spectrum and some solutions.

We know what kind of colourmaps are good for interpretation: those that increase linearly and monotonically in brightness, with no jumps or stripes of luminance. I’ve linked to lots of places where you can read about these — see the end of the post. You already know one perceptual colourmap: the humble Greyscale. But there are lots of others, so let’s start with one of them.

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