Cognitive processing/interpretation of data visualizations techniques Does anyone know of research which investigates the effectiveness (understandability?) of different visualization techniques? 
For example, how quickly do people understand one form of visualization over another? Does interactivity with the visualization help people recall the data? Anything along those lines. An example of visualizations might be: scatter plots, graphs, timelines, maps, interactive interfaces (like Parallel Coordinates) etc.
I'm particularly interested in research within a lay-person population.
 A: Cleveland reports on a lot of this research in his 1994 book The Elements of Graphing Data (2nd ed). It is very readable and extremely useful.
A: This subject matter is often discussed under the discipline of HCI (human-computer interaction) which has it's own journal.
There is a lot of great work being done on this at Stanford under Jeffrey Heer (the creator of protovis and prefuse amongst other things) and in the Stanford Human-Computer Interaction Group.  As an example, read the "Sizing the Horizon: The Effects of Chart Size and Layering on the Graphical Perception of Time Series Visualizations" paper.  The material on the CS147: Introduction to Human-Computer Interaction Design and cs448b Data Visualization homepages may also be of interest.
You can also look at the projects list in the CMU HCI Institute.
A: Couple of thoughts:


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*I think Bertin's Semiology of Graphics is a classic position in this area.

*As Rob pointed out, Cleveland has done some interesting work in the area, example here.

*Some examples of poor design from Stephen Few. 

*Recently I stumbled upon interesting [and quite provocative, especially for Tufte / Cleveland fanatics as myself ;] piece of research from Human-Computer Interaction Lab at the University of Saskatchewan about usefulness of junk.
A: Stephen Kosslyn studies human visual processing, and has written a book called Graph Design for the Eye and Mind. There's useful stuff in there, but he also suggests funny things sometimes. For example, he suggests truncating the y-axis on bar graphs at some point, so that they don't really start at 0, which seems a to be a deep sin to me.
A: Specifically on color and perception, I liked the papers below by Bergman, Rogowitz and Treinish.  


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*Why Should Engineers and Scientists Be Worried About Color?

*A Rule-based Tool for Assisting Colormap Selection

*How NOT to Lie with Visualization

*Lloyd Treinish's home page  (for links to related work)

