In The Subtleties of Color, Robert Simmons gives us a crash course on color theory for data visualization. Providing examples from his own work as Lead Data Visualizer and Information Designer at NASA, Simmons sheds light on perceptual issues with traditional color choices and provides solutions for semantically resonant visualizations.
The article provides a brief overview of human perception of color, highlighting that the RGB (red green blue) color space is ill suited to the human eye since we inherently perceive these three colors at differing levels of brightness. Instead, Simmons recommends the use of lightness, hue, and saturation in the CIE or L*C*h color space, which provide consistent perceived changes across a palette.
Simmons goes on to provide color solutions for three types of data defined by Cynthia Brewer: sequential (continuous), divergent (including a break point), and qualitative (categorical/nominal). Here he also highlights the historic use of color by cartographers, noting that some of the best examples of color use in data visualization have emerged from this field.
Bringing all of these points together, the article concludes by discussing semantically resonant or ‘intuitive’ choices that align with pre-attentive processing, or the unconscious perceptions made by the human eye and brain before additional interpretation takes place. Here the article provides example maps and visualizations, as well as resources and open source tools available to readers for their own visualization work.
Having worked briefly in the city planning field and struggling with color choice for maps on many occasions, I found Simmon’s discussion on the subtleties of color incredibly useful and relevant. While open source tools like Color Brewer are helpful in providing pre-selected ‘safe’ palettes, I have never fully understood the reasoning behind these palette color choices and why some work better for particular data types or visualization methods. Reading this article felt like putting a magnifying glass up to something that I’ve been trying to read for a long time from afar.
It was also exciting to hear Simmons talk about mapping and spatial data in his presentation version of the article. I appreciated his willingness to push back on traditional color choices and imagine new standards in fields that have longstanding traditions and often longstanding disagreement with the idea that ‘aesthetics matter’ and ‘attractive things work better’. I like the idea that these choices are scientific, not just based on individual taste. Beyond their semantic resonance, I often found Simmon’s color choices more visually pleasing that the counter examples he provided. I’m curious to know what others think about this - did you all prefer his choices based on pure ‘taste’ and do you think that ‘taste’ always aligns with semantic resonance? Are things that are easier to understand naturally perceived as more beautiful?