Color Cycle Survey

The survey is now closed. It was accessible from December 2018 through December 2020. Results are available in a pre-print and a GitHub repository.

A color cycle is an ordered set of colors used for plotting categorical data for visualization. Unfortunately, most existing color cycles are not colorblind-friendly. This is an issue since a significant fraction of those viewing a particular plot may be colorblind, especially in fields with diversity shortcomings. This survey was conceived out of frustration with this status quo, in particular with the default color cycle of the Matplotlib plotting library widely use in physics. The technical aspect of this can be resolved by enforcing minimum perceptual distances between colors, both for normal color vision and for various types of simulated color vision deficiencies, a technique that was also used by an earlier effort that created a colorblind-friendly color cycle picker.

The above mentioned technique was used to randomly generate 10 000 color sets each of six, eight, and ten color sets, which have minimum perceptual and lightness distances enforced; full deuteranopia, protanopia, and tritanopia simulations were used. However, this leaves the aesthetic aspect, which is where this survey came in. The goal of this survey was to crowd-source the information needed to generate aesthetically-pleasing color cycles that are also colorblind-friendly. Randomly generated color sets and cycles, which have a minimum perceptual distance enforced between colors, were presented for the user to choose the most pleasing one. These data were then used to train a model to generate aesthetically-pleasing color cycles. Additionally, once anonymized, the collected data was released under a permissive license.

This survey was a project by Matthew Petroff.