That said, my exposure to the field originally came through my work developing interactive scientific visualizations for educational purposes (teaching principles of physics and biology to undergrads and high school students), the design of which focused primarily on supporting informal learning rather than, or in addition to, “focused episodes of work” (to borrow a term from Pousman, et al.). Though these educational tools were often used to help solve specific problems, we were more concerned with making them approachable to non-experts and promoting a casual exploratory usage model. As I began to study information visualization, most of my encounters with it have come through the internet, and though I’ve read most of the “bible” texts of the field that are clearly representative of the “computer science” approach, the “live,” publicly available, high-profile examples of infovis that you typically see on the net would generally be characterized as “casual infovis,” or “information aesthetics,” or “data art,” or whatever you want to call it. This would include systems and tools like Many Eyes, the Baby Name Voyager, the ubiquitous work of design firms like Stamen Design, the various visual web search tools like TouchGraph, art projects like wefeelfine.org, probably some business intelligence related visualizations like the Map of the Market, and even advertising-related infovis like the now defunct Coca-Cola WorldChill visualization (there are of course many more examples, these are just the ones I can think of off the top of my head). So, going in to the conference, my impression was that visualizations like these, regardless of the quality of their implementation, represented a legitimate area of study within the field of “information visualization.”As it turns out, though, it appears that most of these examples probably wouldn’t be considered “information visualization” by the “information visualization” community represented by the InfoVis conference, presumably because, for the most part, they aren’t designed as tools with which you do rigorous analytic work. I saw a lot of evidence for this (which I’ll get to below), but it was most explicitly stated by Stephen Few in his capstone presentation: Stephen pointed to these kinds of examples on the web (in addition to some that I agreed were legitimately horrifying) as presenting a “primitive,” misleading view of what “information visualization” is, and suggested that it was the job of the conference attendees to be “model thinkers and communicators” that “take up residence in the real world” to show the “outsiders” what infovis is really all about. And this was framed as one of the more progressive viewpoints on visualization at InfoVis.
Seth J. Gillespie, PhD
Seth is a proven Information Technology Leader known for his ability to guide companies successfully through large, complex internet-scale Data Center infrastructure deployments positivity impacting millions of customers worldwide. Seth is a skilled and capable manager who cuts through ambiguity, embodies energy, delivers innovative results and fosters high levels of excellence within his teams.
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