The Week in Vis 08 (Mon, Oct 22 – Fri, Oct 26): Color and Graphical Perception

by Mike Gleicher on October 19, 2018

Class Meetings
  • Mon, Oct 22 – Lecture:Color and Experiments
  • Wed, Oct 24 – ICE:Glyph Design (Paris Apartments)
  • Fri, Oct 26 – No Class
Week Deadlines

Last week, we talked about perception generally, and looked at design. This week, we’ll focus on a specific aspect of perception (color) which has all kinds of implications for design.

You may want to look at this week’s learning goals Learning Goals 8: Week 8 – Color and Graphical Perception.

Readings (due Mon, Oct 22 – preferably before class)

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 2015 Color Readings)

We’ll also use this as an opportunity to re-visit being empirical about our recommendations for visual encodings: the idea of using perception (both principles as well as experimental methodologies) to inform our choices (this is called “graphical perception”).

Color

  1. Maureen Stone. Expert Color Choices for Presenting Data. Web Resource.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 Visual Thinking for Design) (Ware-4-Color.pdf 2.8mb)
  3. Map Color and Other Channels (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. Breaking that rule (and using it effectively) is a more advanced topic. Most uses of rainbows are ineffective.

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

Graphical Perception (required)

The key reading was Cleveland and McGill “Graphical Perception and Graphical Methods for Analyzing Scientific Data” (ClevelandMcGill85.pdf 1.3mb), which was already a reading in Week 4 (encodings) – so that’s optional. Heer&Bostock “Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design” was optional for that week.

While I’d like you to read both of these, two papers in addition to everything above may get to be a little much. You don’t need to read these papers in detail – skim over them to get the basic ideas and results. But also read through one of them to get a feeling for the methodology and analysis. Reading both papers is optional.

  1. Assessing Effects of Task and Data Distribution on the Effectiveness of Visual Encodings. Younghoon Kim, Jeffrey Heer. Computer Graphics Forum (Proc. EuroVis), 2018 (web page with PDF)I chose this one (instead of Heer and Bostock) because it is very recent, and gets at the interaction between task, data, and encodings.
  2. 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…

  • Color and Information (Tufte’s Chapter 5 of Envisioning Information) (2-EI-5-ColorandInformation-small.pdf 4.3mb)Tufte is famously anti-color, except when he isn’t.
  • Chapter 10, Principles of Color (Slocum-principles_of_color_cropped.pdf 8.9mb), from Thematic Cartography and Geographic Visualization, 2nd edition by Slocum et. al.This is from a cartography (map making) textbook – but it’s a great intro since it gets into some of the technical issues of reproduction.
  • Chapter 5, The Perception of Color (perception-of-color.pdf 19.5mb), from Sensing and Perception (a psychology of perception book).As you might expect, a Psychology textbook will give you even more about the science of color. It’s probably more of the perceptual science than you want, unless you’re a perceptual science researcher in which case you may have read it already.
  • Here are some postings from a design blog that give a nice tutorial that is a little more design oriented:

Graphical Perception (optional)

This was a reading in week 4, looking at it again is optional.

  • Crowdsourcing Graphical Perception: Using Mechanical Turk to Assess Visualization Design. Jeffrey Heer, Michael Bostock ACM Human Factors in Computing Systems (CHI), 203–212, 2010 PDF (607.4 KB) | Best Paper NomineeI mentioned this paper before as a modern version of Cleveland and McGill. It’s interesting to look at these things and think of how the perceptual system causes the effects that we see. Could you predict the results of these experiments based on perception facts?

    It’s also interesting to contrast the experiments we do in visualization to those done by perceptual psychologists (who have different goals).

For something different, here are some papers that show why it is important to use color correctly:

  • Borkin, M. A., Gajos, K. Z., Peters, A., Mitsouras, D., Melchionna, S., Rybicki, F. J., … Pfister, H. (2011). Evaluation of artery visualizations for heart disease diagnosis. IEEE Transactions on Visualization and Computer Graphics, 17(12), 2479–88. (pdf) (doi)

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