The clever coders over at the Simile Project (MIT) have released a new tool called “Exhibit” for visualizing and enabling dynamic interaction with data. And it’s easier to use! Like their Timeline widget, which I used to time plot the references in my dissertation, you only need basic HTML skills and some data to look at and it is relatively easy to code something up. Simple examples and the required files to roll-your-own data visualziations are provided on their Simile Widgets website. Nice.

I have just got my copy of Stephen Few’s new book “Now You See it”, which I had bought from Amazon without even cracking the cover for a preview and I have to say it’s a very impressive effort. Following on from Few’s previous excellent books Designing Information Dashboards and Show Me the Numbers, this new book carries on his excellent work on data representation and quantitative presentation. Even better, the new book makes specific recommendations regarding user interaction with interfaces. Best of all, it provides a practical methodology for grappling with data representation problems, something which has been sorely lacking in the literature (e.g., the work of Tufte). Go. Buy. Now.

In the thick soup of information in everyday life, I’m often swimming in the flotsam of crap graphics and misleading diagrams. A recent edition of the Times of London (22 Apr 09, p. 3) provides not one, but two classic examples in a single graphic sidebar. In discussing the recent £3B profits of the biggest UK supermarket Tesco, the graphic uses a histogram to illustrate the number of Tesco stores worldwide. Normally, a straightforward info graphic, but in this case, one of the values is substantially larger than all of the others. The result is the histogram contains several similarly-sized bars and one outlier that exceeds the available space. To solve this layout problem, some clever designer has slashed the end of the bar as a visual indication that some of it has been snipped out. This technique works fine in situations such as circuit diagrams, where the main task of the reader is to understand connections, and not the area or proximity of components. However, the main function of bars in a histogram is to provide a visual aid for comparison of the relative sizes of the values encoded (number of Tesco stores). The differences among the values can be perceived pre-attentively - they are apprehended all-at-once, without having to make a calculation or even to compare the bars. This “built-in” capability of our visual perception and as such, are extremely powerful for organising and presenting information. By snipping out the missing portion of the top bar, a false perception is created about the true relative sizes of the quantities that have been encoded. A better solution would have been to avoid this entirely, to choose adifferent layout such as a landscape orientation for the callout graphic, or to simply list the numbers as a table.

The second faux pas in this graphical car crash is an illustration of Tesco’s regional sales, using four adjacent circles. These circles are extremely problematic. Several studies have shown that we are very poor at accurately discriminating the relative areas of circles, often falling victim to quite a large error.

These two examples illustrate a common mistake in diagrammatic representation: poor graphical encoding.

I recently saw this very interesting post about the incomprehensibly large 2008 Bailout package that the US governement is currently wrangling. The post makes an attempt to represent the bailout as an information graphic and unfortunately, the author has used an insidious pie chart to do so.

I hate pie charts. There, I’ve said it. As an alternative, here’s a much improved representation of the same graphic. This histogram is a much simpler representation, which doesn’t suffer the same problems that multicolored pie charts present (poor judgement of irregular areas, and comparison of areas that do not have a common origin or terminus). In the revised version, the focus is on the content, rather than the colors. Easy comparisons can be made and the relative sizes of these quantities can be compared with less likelyhood of error or misjudgment.