InfoVis vs. i|e

People have set out varying hopes and interpretations for the term “Information Aesthetics,” and they mostly differ from what this organization was created to support; that’s one of the reasons we chose the less-used “American” spelling of the word. This note is the first of a few that try to better define the boundaries of our particular spotlight—perhaps closer in spirit to the original coinage by Scha and Bod (1993) (which itself seems related to some interesting work quantifying Aesthetic Judgement and Arousal due to the complexity of forms in a 1973 paper of that name by Gerda Smits—this is not a new area of study).

The Scha/Bod/Smits focus is closer to i|e’s more scientifically-inspired approach than most who use the “ae“ spelling: discussions largely making technological, cultural, and media-theoretical references. (Rather than “scientifically-inspired approach”: I should say our engineering- and humanities-inspired approach—strange bedfellows, hm?) Here, as always, I shall try to build tools to help segment and navigate this territory rather than list examples or wax prosaic with almost meaningful cultural generalizations. The i|e focus does differ from these explorations, though: here we will sometimes address levels of abstraction more coarsely-grained the visual information encoding addressed by the fascinating papers above.

The field of Information Visualization (familiarly “InfoVis“) has existed for almost two decades as a named discipline (a splinter from the “Scientific Visualization“ community) and arguably in practice since William Playfair’s invention of the bar chart in the late 1700s. [editorial note: these ideas come off the top of my head, and I welcome corrections -Brad]

Our i|e spotlight will look among InfoVis inventions for examples of how clarity can enhance the esthetic experience of a work, and perhaps how an esthetic engagement can enhance absorption of information. But the work in the two main academic conferences defining the field (IEEE InfoVis and Europe’s Information Visualization) seems rarely as personally moving as the average painting in a museum (an admittedly un-tool-like criterion—one that needs to be better delineated in another post), and sometimes doesn’t even meet all the criteria I apply to good InfoVis work.

So a first task, perhaps easier than defining what moves someone in a museum or other esthetic context, is to define some criteria by which we can distinguish different types of images as good or bad InfoVis. I will not shrink from these value judgements, hoping to expose my own biases for the rest of the community to endorse or correct. We need some firm and testable statements, though, to get traction in the slippery mire of this multiply-defined area, so I’m taking the risk of setting down some initial ideas in that direction: a set of tests by which we can determine the success of a particular image or method.

It’s my impression that things that present themselves as information visualization are rarely useful or satisfying, and an entertaining task might be to see what percentage of images or methods at a marvelous site like Visual Complexity meets the minimum test: is it readable. (As a justification for being judgmental, I’d suggest that if someone holds out their work to be information visualization, it’s perfectly valid to judge them on their own implied criteria. In the InfoVis tests note I try to make some of those criteria explicit.

After we decimate the field with real InfoVis tests and general clarity, we’ll narrow the spotlight further with ideas from the humanities—another post and another whole approach. It is my hope that intersecting these two approaches will leave a dozen or two works that meet the criteria of both sides, synergizing in a way that will be inspirational to those of us who want to both understand and feel our ways through the world.