Readings 11: Color

in All Readings

Color is a surprisingly complex topic - and the complexities of perception and display have real impact on how we use it for Vis. There is some redundancy in these readings, but it’s hard for me to choose which ones are best. It’s probably OK to see it multiple ways. This is actually less reading than I’ve given in the past for the topic (see 2017 Color Readings). And there are so many recent and useful things…

  1. Maureen Stone. Expert Color Choices for Presenting Data. (Stone-ColorChoices.pdf 0.3mb) (originally a web article).

    Maureen really is an expert on color. This is a good review of the basics, and then gets into why it’s important to get it right, and how to do it.

  2. Color (Chapter 4 of Ware’s Visual Thinking for Design) (Ware-4-Color.pdf 2.8mb)

  3. Map Color and Other Channels (Chapter 10 from Munzner’s Visualization Analysis & Design) (Munzner-10-MapColor.pdf 0.4mb)

    Color is really 10-10.3, 10.4 talks about other channels. It’s a good reminder.

  4. Borland, D., & Taylor, R. (2007). Rainbow Color Map (Still) Considered Harmful. IEEE Computer Graphics and Applications, 27(2), 14–17. (rainbow-still-considered-harmful.pdf 0.7mb) (doi)

    The rainbow color map is still used (10 years after this paper). Understanding why you shouldn’t use it is a good way to check your understanding of color ramp design. However, there are lots of reasons you should use it (or a variant of it) that are discussed in more modern papers. The key point is to understand the issues.

    A more recent paper (Bujack et. al - optional below) gets at this in a more mathematical way, but it is overkill for class purposes.

  5. Danielle Albers Szafir. “ Modeling Color Difference for Visualization Design.” IEEE Transactions on Visualization and Computer Graphics, 2018. In the Proceedings of the 2017 IEEE VIS Conference. (best paper award winner).

    This paper is really practical in that it shows how color science and modeling and be used to tell us what will and won’t work in visualization. It shows the value in careful experimentation and modeling. It’s a good fit because it focuses on color. And she’s my former student.

Color: Optional

We’ll talk about Color Brewer in class, but if you want to know the science about it:

  • Cynthia Brewer. Color Use Guidelines for Data Representation. Proceedings of the Section on Statistical Graphics, American Statistical Association, Alexandria VA. pp. 55-60. (web) (Brewer_1999_Color-Use-Guidelines-ASAproc.pdf 1.5mb)

    The actual paper isn’t so important - it’s the guidelines she used in creating Color Brewer, which also tells us how to use it. What is more important is to actually check out ColorBrewer which is a web tool that gives you color maps. Understand how to pick color maps with it, and try to get a sense of why they are good.

    The irony is that this, one of the most important papers about color, wasn’t printed in color!

If you want a little more of how color science and vis come together.

  • Bujack, R., Turton, T. L., Samsel, F., Ware, C., Rogers, D. H., & Ahrens, J. (2017). The Good, the Bad, and the Ugly: A Theoretical Framework for the Assessment of Continuous Colormaps. IEEE Transactions on Visualization and Computer Graphics, 24(1 (Proceedings SciVis)). (doi)

    This paper does a serious, deep dive into figuring out what makes a good or bad color ramp and making the intuitions mathematical. You can play with their tool for assessing color ramps.

In case you want a few other perspectives on color…