Stop using ‘rainbow’ maps — it doesn’t do your data justice

The choice of color to represent information in scientific images is a fundamental part of communicating findings. However, a number of color palettes that are widely used to display critical scientific results are not only dangerously misleading, but also unreadable to a proportion of the population.

For decades, scientists have been pushing for a lasting change to remove such palettes from public consumption, but the battle over universal accessibility in science communication rages on.

A color map is a palette of multiple different colors that assign values to regions on a plot. An example of a misleading color map is rainbow, which generally starts with blue for low values, then passing through cyan, green, yellow, orange, and finally red for high values. This color combination is neither diverging, which would allow us to visually perceive a central value, nor sequential, which would make organizing values from low to high intuitive.

Color brings life to data

Using color bar graphs can allow scientists to transform their collected data into something meaningful to be shared widely. This could be the first direct impression of a black hole, the mapping of votes cast in political elections, the planning of an expensive rover route on Martian topography, the essential communication of climate change or the critical diagnosis of heart disease.