New media theorist Lev Manovich just released a new text, titled What is Visualization? [manovich.net]. One might first wonder if such a question is not too... obvious, but in the light of the contentious discussion about the tension between artistic and scientific representations of data, and whether data art should be called visualization at all, it is always worth covering the basics.
The text is quite substantial, so you might want to wait for some quiet time to dive into it. The main arguments in the text focus around distinguishing information visualization, scientific visualization and information design. In addition, Lev proposes a new term, "media visualization", for those visual representations that do not reduce data into topology and geometry, but instead uses techniques to reorganize data into a new visual representation that preserves its original form. In other words, if the data consists of text, images or video, the resulting (media) visualization also shows the text, images and video, or samples of it, in some way or form.
Examples of media visualization include tag clouds, Ben Rubin and Mark Hansen's Listening Post, Brendan Dawes' Cinema Redux, and Ben Fry's Preservation of Selected Traces. These projects highlight patterns in the data without reducing it by mapping data values into abstract graphical elements, or summarizing it through statistics and statistical graphics. Instead, such visualizations preserve the original visual form of the data, or sample it when it is too large or numerous.
For those with little time, I took out following bits:
"For some researchers, information visualization is distinct from scientific visualization in that the latter uses numerical data while the former uses non-numeric data such as text and networks of relations."
I originally thought the conceptual difference was that data/information visualization deals with 'abstract' data, that is data that has no physical presence in reality and requires a visual metaphor to be perceived, let alone understood. Scientific visualization, in turn, deals with physical reality and its visual simulation.
Well, let's skip this misunderstanding, and continue to the real bits...
"Information design starts with the data that already has a clear structure, and its goal is to express this structure visually. ... A different way to express this is to say that information design works with information, while information visualization works with data. "
"In my view, the practice of information visualization .... relied on two key principles. The first principle is reduction. Infovis uses graphical primitives such as points, strait lines, curves, and simple geometric shapes to stand in for objects and relations between them - regardless of whether these are people, their social relations, stock prices, income of nations, unemployment statistics, or anything else. ... (The second principle is the use of...) spatial variables (position, size, shape, and more recently curvature of lines and movement) to represent key differences in the data and reveal most important patterns and relations."
"However, it seems to longer adequately describe certain new visualization techniques and projects developed since the middle of the 1990s. ... Tag cloud exemplifies a broad method that can be called media visualization: creating new visual representations from the actual visual media objects, or their parts. Rather than representing text, images, video or other media though new visual signs such as points or rectangles, media visualizations build new representations out of the original media. Images remain images; text remains text. ... we can also call this method direct visualization, or visualization without reduction. In direct visualization, the data is reorganized into a new visual representation that preserves its original form. Usually, this does involve some data transformation such as changing data size. "