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manovich_media_visualization.jpg
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.

In addition, Lev Manovich describes 3 visualization projects developed in his lab: ImagePlot, VisualSense and HiperView.

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. "

4 COMMENTS

media visualization, interesting.
What is the "original visual form" of the data. Numbers and text are visualization techniques so...
Original visual form can only mean, visual form of some data that is intrinsically visual. Like, i dont know, stereographic photos, or something.
I need to read this

Fri 29 Oct 2010 at 4:24 AM
Jörgen Abrahamsson

Put in simpler words, text stays text, images stays as images. When the data is more abstract, I guess no media visualization is possible.

Fri 29 Oct 2010 at 5:38 AM

My point was that text and numbers are visualization techniques and not data. If I write the number 4 or the word 'four' or makes this mark: **** Its all the same(but different, and having different uses)
The same goes for text. The idea is the data, what form it takes is a matter of technique, visual or other.
This is kind of important. Many people think that an excel spreadsheet is the 'real' data and a graph less so.

Fri 29 Oct 2010 at 6:53 PM
Jörgen Abrahamsson

My own summary of the article:

-----------
Lev Manovich
What is Visualization?

The article proposes that the practice of information visualisation (infovis) from its beginnings in the second part of the eighteenth century until today 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. The second principle is the use of spatial variables (position, size, shape and, more recently, movement) to represent key differences in the data and reveal patterns and relations. Following this analysis, I discuss a more recent visualisation method which we can call ‘direct visualisation’ (or ‘media visualisation’): creating new visual representations from the actual visual media objects (images, video) or their parts. The article analyses the well-known examples of artistic visualisations that use this method: Listening Post (Ben Rubin and Mark Hansen, 2001), Cinema Redux (Brendan Dawes, 2004), and Preservation of Selected Traces (Ben Fry, 2009). I further suggest that media visualization method is particularly relevant for humanities, media studies and cultural institutions. Using the actual visual artefacts in visualisation as opposed to representing them by graphical primitives helps the researcher to understand meaning and/or cause behind the patterns she may observe, as well as discover additional patterns. To illustrate this idea, I present the examples of projects created in my lab at UCSD (softwarestudies.com). Founded in 2007, the lab works on techniques and software to allow interactive exploration of large sets of visual cultural data using direct visualisation approach and supervisualisation systems such as 215 megapixel HIPerSpace. The examples of our work are visualisations of 4553 covers of every issue of Time magazine published between 1923 and 2009; visualisations of all pages of every issue of Science and Popular Science magazines published between 1872 and 1922; and a set of visualisations of 1 million pages on Manga series.

Thu 18 Nov 2010 at 4:18 AM
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