Visuale

It's when staring at images like these that I think the best visualizations ever are those offered by the nature.

[from NASA Visible Earth, click on the images for details]

It's amazing to see how informative and beautiful aerial and satellite images are. I try to mentally compare the process of producing visualizations of abstract data (i.e., information visualizations) with that of producing representations of real world object, as these pictures above are.

It's incredible how much more subtle and beautiful these images are compared to those obtained from information visualizations, which have regular grids, well segmented areas, few details, less sense of visual continuity and uniformity.

And yet, at the same time, it's crazy how much more effort it's required to design a visualization and how much more uncertainty there is in it. It looks like the mental and imaginative effort required to a visualization designer is much more because the number of free parameters to set is very large. Design decisions can really differentiate between a good and a bad visualization, and thus much more responsibility is given to the visualization producer.

These few considerations make me recall of a recurring debate on what's the difference between "scientific visualization" and "information visualization". I don't care too much about the terminological debate, nor am I in favor of a neat distinction between the two (quite some people went over it already). However, for the purpose of this post I think it's very interesting to re-propose here what Tamara Munzner once had to say in a panel (pdf link to the panel content) hosted by Vis'03 about the topic:

"Although there are still many definitions of infovis floating around, I think we have begun to converge on the answer that the dividing line is whether the spatialization is given or chosen."

"... The central design problem of an infovis system is the choice of how to assign spatial position, which is by far the strongest of the perceptual cues. Our grappling with this huge space of possibilities has led to a strong emphasis on abstraction, visual metaphors, design principles, and evaluation."

Pushing things to the very extreme, the result is: we visualization designers put much more effort to build things that are thousands of time less beautiful than what? A simple picture.

I've already touched the topic of visualizations able to expose human dynamics in a recent post about the F-shaped pattern of web reading behavior.

Here is TimeLine, a new and different example. TimeLine captures video streams an visualizes them in a way that it is possible to review your past minutes, hours, days, or weeks and detect behavioral patterns.

In the GroupLab @ University of Calgary's words, where it was conceived:

TimeLine was originally conceived to work as part of a media space, where people would use it to reveal their collaborator's events and activities over time, ostensibly to gauge their availability. It may also be useful for surveillance, for monitoring, and as an interactive art installation.

The technique is inspired by slit-scan photography a way to achieve blurriness or deformity exposing the film to only small fragments of the scene, with long exposures and panning. Video slicing extracts only a scan line from the video at a constant rate and add it to a queue of frames, as illustrated here below:

[source Nunes, M., Greenberg, S., Carpendale, S. and Gutwin, C. (2007) What Did I Miss? Visualizing the Past through Video Traces. Report 2007-855-07, Dept. Computer Science, University of Calgary, Calgary, Alberta, Canada. March. 21 pages.]

Frames at different intervals are used in the minute, hour, day, week view, selecting the video slices carrying more information.

What is really interesting, in my opinion, is the set of interactive techniques provided with the tool. They permit to effectively explore the past and detect interesting behavior. The main techniques are:

• Move slit position: the user can change the position of the video from which the slice is taken. Moving the slice in the real-time video window, it is possible to focus on alternative positions and all the views get instantly updated.
• Scrubbing: dragging the mouse over a video, it is possible to replay the scans at high rates back and forth, thus allowing for the detection and analysis of certain patterns (e.g., a person entering the room).
• Details of the past: selecting areas in the coarser views, it is possible to load past slices and review them at a higher resolution.

All these techniques are really hard to explain with words. I would also say that the entire system is hard to describe without seeing it in action. I highly suggest you to watch the video to understand how effective it can be. In fact, it is so effective that it raises serious privacy concerns, as deeply discussed by the authors.

Once again I think this is the kind of "experimental" visualization that can really open new perspectives. It is completely different from the standard data-feature mapping scheme of information visualization but still, I would say, it is a very good example of visualization. Information is continuously flowing in the system, and the visual abstraction is based on capturing pictures ... quite far from the more traditional "load a static dataset and explore" mindset of infovis.

Related Works:

	A library of slitscans can be found at Informal Catalogue of Slit-Scan Video Artworks as well as exploring the Flickr's tag "slitscan"
	Lastclock
	Artifacts of the presence era