Because every place worth going can be found on a topo map.
The papers this week reminded me of why I hated freshman bio. The vast amount of classification data is the sort of thing that is usually learned through extensive rote memorization which must be constantly updated as genetic family trees are arranged and rearrange in the presence of new data. In short, this is a topic that my natural instinct tells me to run away from as fast as I possibly can. In terms of biology, much of what didn’t go over my head in this weeks readings fell on willfully ignorant ears, but I will do my best to touch upon the graphical issues that were touched upon.
A theme we’ve touched upon again and again is how to deal with a huge amount of data without losing breadth in order to spot trends, or depth, in order to examine specifics. We’ve seen a number of of ways to deal with this, including multiple dimensions, complex representations with colors and shapes, and multiple representations. Dynamic zoom is a particularly useful tool, and is used to great effect in TreeJuxtaposer. It brings up the interesting problem, however, of maintaining context of the data while using the zoom. The combination of dynamic scaling and the use of color is particularly effective in both highlighting the needed information and keeping the sense of overall place in the hierarchy.
Mizbee was one of the more beautiful visualizations we’ve looked at so far. I found the way it dealt with multiple matching to be surprisingly elegant and intuitive for something that is really incredibly complex. That said, I am too actively bio-phobe to figure out exactly what the goal or takeaway of all these colorful wheel lines actually is. I look forward to someone giving me the idiots guide to genetic markers one of these days. Until then I’ll appreciate these for the pretty mandalas they are.
Mizbee, however, is a perfect example of a great visualization that I have absolutely no interest in. Not because of its subject matter, since it could be used for various data, but because, despite its elegance it is fundamentally non-intuitive. I’m interested in visualization as argument and visualization as communication. A different, and often contradictory, goal is to divine new relationships in existing data, in other words, visual analytics. Though I can appreciate the latter from an aesthetic level, these sorts of tools usually have high barriers to entry in the form of a steep learning curve. I am much more concerned, personally, with visualization as argumentation, and argumentation should be clear and accessible if it is to be successful.
