Colour pallets and scientific plotting
I sometimes envy the creative plots I see in papers, theses, or presentations. I do not think it is the unhealthy kind, but rather about growing in how I express my science more creatively. Maybe envy is not the correct term. I appreciate that person more for putting time and effort into small things that many would say are not important.
The starting point for making such plots/figures/visualisations is to make a deliberate choice about everything — colour palette, placement, font, labelling, projection, and, most importantly, what to present and what not to present. I learned this from my supervisor during our monthly review meetings. This can also be broadened to “taste” in an informal sense, or to an aesthetic sense more formally.
Research in any domain is inherently complex; presenting it simply is essential. Simple, not in a condescending way, but simple in a sense that leads the reader to discover the thing and leave with a satisfaction of discovering something new. That’s how I understand it at the moment.
I think of it like navigating a new station or airport, only with signage (no language). A well-planned, thought-out planner would place signs at intuitive, predictable locations. So anyone can orient and determine where someone has to go. Something similar applies to communicating research findings; everything should be present, yet it should not be overwhelming, just enough to communicate an idea. I am not sure if it is a good analogy.
One starting point I leaned on early in the meetings was to use colour palettes properly (admittedly, I knew this earlier but never realised its importance). There are two choices: (i) default to your programming language or plotting library, or (ii) a deliberate and informed choice. Like in The Road Less Travelled, the second one makes all the difference.
This is one of those things: once you start seeing it, you start finding it everywhere. After that interaction with my supervisor, I spent some time reading and learning about the use of colour maps. It’s like the 80-20 rule. A small, deliberate decision can drastically improve the quality of a figure. Things to remember
- Do not use the default colour maps (eg. jet or rainbow equivalent)
- Four classes of colour maps - (i) diverging, (ii) multi-sequential, (iii) cyclic and (iv) sequential
- Three types of colour maps - (i) categorical, (ii) discrete and (iii) continuous
- Remember a major chunk of the population is colour blind (of some kind), so please be mindful of it, especially when presenting at conferences.
Please check the article titled “The misuse of colour in science communication” in Nature Communications by Fabio Carmerie, Grace Shephard and Philip Heron for more information. They also provide a convenient flowchart for determining the appropriate colourmap choice.
This will take many iterations, so starting early is important. One can take inspiration by observing how others do it. For instance, reading on cartographic, graphic design, or typesetting principles may be rewarding.
I will keep updating from time to time when I learn something new or see something inspiring. Until next time…
— post edit and publish on 14-08-2026 —
Reference
- Crameri, F., Shephard, G.E. & Heron, P.J. The misuse of colour in science communication. Nat Commun 11, 5444 (2020). https://doi.org/10.1038/s41467-020-19160-7