Originally uploaded by sintixerr
On the subject of these “data visualizations as art”, I’ve been trying to better articulate why I think they’re art and how I’m trying to evolve my process.
What it comes down to is that there seems to be two pieces to developing the visualizations:
- Choosing the right structure and things to measure about the text or data…what makes sense to compare to what. How do you reduce the noise and non-dependent variables? Each type of text you’re measuring and each circumstance has different relationships. There is a lot of science to this part, but it’s not completely predicatable. There is art.
- How do you visually best enhance and needle out the important details, contrast between points, etc so that they can be “seen” in the noise that doesnt matter? This is all art. Understanding how color, shape, contrast, etc all work together and how to use all of those to present a dense amount of information without being overwhelming is tricky and depends on the skill of the one creating it…
It’s my belief that playing to what we understand as people’s abilities to process and comprehend aesthetics in art involves exactly the same techniques and takes advantage of the same aspects of peoples brains/senses as good visual data analysis. So, if you’re doing data analysis, you start out figuring out #1, and then move to #2 based on #1.
What I was trying to do with these stimulus images – and the last of my security visualizations – was start out with concepts of what I’d like for #2 (how they would “feel”) and then figure out what I needed to do in #1 (massage the data) to get there…while still remaining true to the underlying information.
Next up (and once I learn more Objective C), I’m going to try and read in the stimulus bill to Quartz Composer and combine my recent interactive/music visualizations with the Bill. We’ll see if that goes anywhere interesting. :)
Also, Artomatic returns to DC this year. I very well may be displaying this stuff there when it comes around. This or the music/webcam visualizations.