(reading due Tuesday, February 9th – please post comments before 7am)
One big question we’ll need to ask with anything we do with visualization is: is it any good?
There are many different ways to assess this. In fact, you can ask this question from the different perspectives on visualization (domain science, visualization/CS science, design). I’ve chosen 3 readings that come at evaluation from these different directions:
- Tamara Munzner. A Nested Model for Visualization Design and Validation. Infovis 2009 (project page with pdf)
Of course, we can’t talk about “what is good” without consulting Tufte for his strong opinions. (not that he isn’t going to make his opinions clear). This “chapter” is kindof split into one on good and one on bad.
- Edward Tufte. The Fundamental Principles of Analytical Design. in Beautiful Evidence. (protected pdf). In hindsight, this Tufte chapter is actually much better in the “how” to make a good visualization, and trying to distill the general principles, than many of the others we’ve read. But its Tufte, so its still full of his opinions on “what is good.”
- Edward Tufte. Corruption in Evidence Presentations. in Beautiful Evidence. (protected pdf)
Finally, Chris North at Virginia Tech has been doing some very interesting work on trying to quantify how much “insight” visualizations generate. I recommend reading the actual journal article with the details of the experiments, but the short magazine article might be a good enough taste of the ideas. (Update: I actually recommend reading the shorter “Visualization Viewpoints” article, since it gives a better overview of the basic ideas. If you’re interested, you can go read the longer journal article that details a specific experiment.)
- Purvi Saraiya, Chris North, Karen Duca, “An Insight-based Methodology for Evaluating Bioinformatics Visualizations”, IEEE Transactions on Visualization and Computer Graphics, 11(4): 443-456, (July 2005). [pdf]
- Chris North, “Visualization Viewpoints: Toward Measuring Visualization Insight”, IEEE Computer Graphics & Applications, 26(3): 6-9, May/June 2006. [pdf]
Everyone should read all 3 of these. (well, at least 1 chapter of Tufte and at least one of the Chris North papers).
In the comments, share your thoughts on how these different ways to look at evaluation (well, Munzner actually gives several – but I am lumping them together) might relate and help you think about creating visualizations and/or visualization research yourself. What do you think is important for your perspective (e.g. your domain)?
If you have experience in another domain where there are ideas of how things are evaluated, how might these ideas relate to how visualization is evaluated?
Everyone in class must contribute at least one “top level” comment answering the questions above, and preferably add some replies to others to “start up” the class conversation on evaluation.