Colour might be the most discussed topic in data visualisation. This is due to colours being at the crossroads of aesthetics, cognitive science, culture and accessibility (see the Accessibility module) of data visualisation. Another reason for colour being a hot topic is that it is a hard topic to give advice about: coming up with “the best” color palette is simply not possible: too many elements play a role in the encoding and perception of colours.
What is possible, though, is trying to get a good understanding of what colours are, of what factors play a role in the perception of colours, and of what you should take into account when choosing colour palettes for data visualisation. What can also help is knowing about tools that can help picking colours a little easier.
Because colour is such a broad topic, this part of the training is split up into 3 modules:
Technically, colour is what our brains perceive when light of different wave lengths hits our retina, and the signal is sent through the optic nerve.
For a more practical and data visualisation focused approach to colour, you could say that colours are the proportions of different tints of ink that we print on paper, or the proportions of different kind of light that we let screens emit to represent data marks on a visualisation. The way to describe the proportions of “pure” colours needed to produce a certain color is what the first part of this module is all about.
The second part of this module is about combining colours. Some color combinations feel much more harmonious than others, and you’ll learn why that is the case. Luckily many tools exist to help you pick these colour harmonies.
Because colours are often used in data visualisation to discern between groups and categories, colour combinations also need to be “different enough” to be used effectively in data visualisation. And maybe most importantly: the colours used must be different enough from the background they are used on. So colour contrasts are an important part of this module too.
Finally you’ll learn that colours are not neutral: many colours are associated with objects, feelings and ideologies. These associations and connotations are not universal: they are culturally determined. Something important to keep in mind when designing visualisations for an international audience.
Humans use words to describe colours. We have words like “red”, “orange”, “purple” and “pink” to describe colours. And we even have words to describe different tints of the same color, like “light pink”, “hot pink”, “deep pink” and “salmon”. But these words do not map one on one to exact tints and hues: people use these words to describe slightly different colours.
In what follows, different systems to exactly describe colours are outlined, together with their application:
RGB stands for Red Green Blue, the primary colors in the so called additive color model. Where the primary colors overlap in the additive model, you get secondary colors. And where all 3 primary colors overlap, you get white.
Source: commons.wikimedia.org/wiki/File:AdditiveColor.svg, public domain
