Criticism

The first episode of season 4 of Mad Men opens with Don Draper being interviewed by a journalist. He doesn't tell him anything that's of interest and then dodges the question Who is Don Draper? by claiming that he was taught as a child not to talk about himself. Scientists do an equally terrible job at communication, and for many of the same reasons. Cornelia Dean's book Am I Making Myself Clear? offers fascinating insights into both journalism and science, and provides concrete ideas for how to do better.

Information graphics (infographics) have gotten a bad rep lately because of a sudden wave of badly designed, uninformative graphics. But when they are done right, infographics can be both highly informative and enjoyable to look at and discover. Here are a few recent examples to demonstrate that.

Is visualization art? Are video games art? Is programming art? Is art art? You can discuss these questions at length, but without concrete criteria, they end up being academic exercises rather than leading to some kind of conclusion. One criterion, which I believe to be suited especially well for visualization, is the sublime. Art is sublime, visualization is not. Hence, visualization is not art.

There is almost universal agreement that any extraneous elements in a chart or visualization, elements that do not represent numbers, are detrimental to understanding the data. A paper that was presented at CHI recently described a study to figure out just how bad all this chart junk really was. As it turns out, it's actually rather helpful.

Visualization is not a very clearly defined field. There are many variations, ways of doing it, and ideas around it. That is valuable, because it keeps the field moving and brings in fresh ideas. But it also brings with it people who like using visualization's tools and talk about visualization, but what they are doing is something else. We need to start calling these things what they are: a cargo cult of visualization.

Terrible charts seem to be in season. Rarely have I come across so many incredibly bad charts in such a short time: information graphics that don't actually depict data, distorted representations, useless color schemes, and the worst pie chart ever.

For some time now there has been some discussion about finding a new terminology for the Data Visualization field. The intention is to find names that reflects the two main different directions that are seen today on Dataviz: visual data analysis and data driven aesthetics images. The concern is that Data Visualization might lose its ‘serious’ role as an analytic tool by including works that, without doubt, praise aesthetics before clarity.