Sit Back and Relax with Casual Information Visualization
Zachary Pousman et al. write in their paper Casual Information Visualization: Depictions of Data in Everyday Life
Information visualization has often focused on providing deep insight for expert user populations and on techniques for amplifying cognition through complicated interactive visual models. This paper proposes a new subdomain for infovis research that complements the focus on analytic tasks and expert use. Instead of work-related and analytically driven infovis, we propose Casual Information Visualization (or Casual Infovis) as a complement to more traditional infovis domains. Traditional infovis systems, techniques, and methods do not easily lend themselves to the broad range of user populations, from expert to novices, or from work tasks to more everyday situations.
At the paper's roots, it goes onto cover the edge cases in infovis -- ambient, social, and artistic infovis. The three are perhaps not what we consider traditional infovis in that we're not going to sit down with them for a couple of hours to gain some kind of insight. Instead, ambient, social, and artistic viz are displayed constantly and the casual observer gets something other than analytic insight. Causual infovis draws upon awareness, social, and reflective insight. I won't go into the details of each type of insight. You can just read the paper.
Catering to a Wider Audience
This paper brings up some good points about traditional information visualization and how the edge cases of infovis (ambient, social, and artistic) pose different design problems -- mostly which come from trying to display information in a way that everyone can understand.
My one criticism is that the authors don't seem to place much faith in the user. The authors mention that users may not be experts in understanding complicated graphs and charts (which is kind of true), so casual infovis can only show a small number of attributes. I like to think though that instead of dumbing down the vis, we should work on improving data literacy and in turn, should expect the user to grow more accustomed to more complex visualization.