When I reviewed The Grammar of Graphics, Harlan Harris pointed me to Kosslyn’s book Graph Design for the Eye and Mind. I’ve since read it and can recommend it highly, although the two books have quite different goals. Unlike Wilkinson’s book, which provides a framework encompassing all the graphics that are possible, Kosslyn’s book summarizes perceptual research on what makes graphics actually readable.
In other words, this is something of the graphics equivalent to Strunk and White’s The Elements of Style, except that Kosslyn’s grounded in actual psychology research rather than personal preferences. This is a good book to keep at your desk for quickly checking whether your most recent graphic follows his advice.
Kosslyn is targeting the communicator-of-results, not the pure statistician (churning out graphs for experts’ data exploration) or the data artist (playing with data-inspired, more-pretty-than-meaningful visual effects). In contrast to Tukey’s remark that a good statistical graphic “forces us to notice what we never expected to see,” Kosslyn’s focus is clear communication of what the analyst has already notices.
For present purposes I would say that a good graph forces the reader to see the information the designer wanted to convey. This is the difference between graphics for data analysis and graphics for communication.
Kosslyn also respects aesthetics but does not focus on them:
Making a display attractive is the task of the designer […] But these properties should not obscure the message of the graph, and that’s where this book comes in.
So Kosslyn presents his 8 “psychological principles of effective graphics” (for details, see Chopeta Lyons’ review or pages 4-12 of Kosslyn’s Clear and to the Point). Then he illustrates the principles with clear examples and back them up with research citations, for each of several common graph types as well as for labels, axes, etc. in general. I particularly like all the paired “Don’t” and “Do” examples, showing both what to avoid and how to fix it. Most of the book is fairly easy reading and solid advice. Although much of it is common sense, it’s useful as a quick checkup of the graphs you’re creating, especially as it’s so well laid-out.
Bonus: Unlike many other recent data visualization books, Kosslyn does not completely disavow pie charts. Rather, he gives solid advice on the situations where they are appropriate, and on how to use them well in those cases.
If you want to dig even deeper, Colin Ware’s Information Visualization is a very detailed but readable reference on the psychological and neural research that underpins Kosslyn’s advice.
The rest of this post is a list of notes-to-self about details I want to remember or references to keep handy… Bolded notes are things I plan to read about further. Continue reading