Elegant Figures was interesting from both the perspective of a color theory fan as well as the perspective of someone interested in examining the differences between the arts and sciences industries as they currently exist. It was curious to hear the design choices advocated for by visual experts in the sciences, versus knowing from experience what challenges present creative professionals. The industries can learn a lot from each other, which has excitingly been happening more and more in the last decade.
The design world would have quite the opposite problem of the pervasive rainbow pattern - often you see designers going too off the rails or not bothering to stick with sensible defaults. In scientific visualization, it would seem that amateurish palettes are born from a lack of imagination whereas in design, it would seem that amateur palettes are born from overexcitement. The common ground, it would seem, is that bad palette choices are those made thoughtlessly.
You see this in other industries as well, and I would be interested in studying the negative effects of information communication on bad color choices made in business, UX, and media. This raises the question: should color choices be more standardized? In the algorithm developed by Stanford’s Visualization Group, they aim to choose semantically-resonant colors for specific data visualizations. Would this help improve communication, or limit designers? It would be great to be able to generate palettes based on semantically-resonant keywords across industries, but also be able to break it when needed, as Simmons’ described in his “perfect palette tool” (Part 5). This would take a vast indexing of visually relevant keywords across themes in multiple industries, but could be aided by machine learning language and imaging processes. I personally be interested in exploring how we could use color to express political affiliations and bias to examine the use of color from a media literacy perspective.