Sit Back and Relax with Casual Information Visualization

Posted to Data Art  |  Nathan Yau

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.

Ambient Orb

Tableau Machine

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.


  • Thanks for mentioning my paper! I hadn’t see this so I’ll just leave a quick comment for posterity (yeah right, posterity on the web).

    Just as a side note, I totally agree with Nathan that designers should be striving not just to present data in a simple way, but also to raise the level of infographic literacy (graphicacy) amongst the general populace. Both approaches are valuable and needed. I’d point the interested reader or infographics activist to projects like World Visualization Day, which aims to bring visualization to the masses and to show people the power of understanding data through (interactive) visualizations.

  • I’m always happy to mention things that are interesting.


Where People Run in Major Cities

There are many exercise apps that allow you to keep …

One Dataset, Visualized 25 Ways

“Let the data speak” they say. But what happens when the data rambles on and on?

How You Will Die

So far we’ve seen when you will die and how other people tend to die. Now let’s put the two together to see how and when you will die, given your sex, race, and age.

Shifting Incomes for American Jobs

For various occupations, the difference between the person who makes the most and the one who makes the least can be significant.