While it’s common practice at Pixo to check color contrast for optimal readability, we don’t always prioritize comparing each color’s distinction from one another. But color distinction becomes a high priority when designing data visualizations, which rely on the variations between color to represent different categories of information.
Designers might strive to make this color distinction clear for viewers who perceive colors in a similar way, yet this “one size fits all” approach doesn’t take into account all color vision experiences.
To create truly inclusive software, we need to ensure our color palettes are designed for all types of viewers.
Prevalence of Color Blindness
According to the National Eye Institute, there are three main types of color blindness: red-green, blue-yellow, and total color blindness. The most common type is red-green color blindness (protanomaly, protanopia, deuteranomaly, deuteranopia). Blue-yellow and complete color blindness are rarer (tritanomaly, tritanopia, cone monochromacy, achromatopsia).
As many as 8% of men and 0.5% of women with Northern European ancestry have the common form of red-green color blindness.
For a particular data visualization project at Pixo, I turned to the web in search of some existing color palettes for data visualization that were distinct enough for all types of color vision experiences. Overall the options were disappointing and not always visually complementary.