Because every place worth going can be found on a topo map.
The common question in the readings for this week was how to deal with too much data. This is a more and more common problem in our information society, especially in the field of security where critical information is often hidden beneath piles of random noise. Our natural abilities to visually identify patterns is ideally suited toward this problem, but we still need to find a way to present the data in a usable format. To do so requires culling large data sets down to the critical elements, and, as in most cases with visual analytics, results in rather complex figures with steep learning curves.
Computers and computing networks are, as usual, prime candidates for this sort of visualization, given the immense amount of data available to the visualizer. The paper we read only begins to touch upon the many many ways visual analytics are currently being used in network security. In fact there is an entire manyeyes-esque site, secviz.org, which represents a substantial community devoted to the subject. Having spent a fair bit of time working through some of the visualizations, I’ve realized I should have been a comp sci major. As it is, though, it’s all over my head: Like I said, steep learning curve.
A little more accessible, but arguably more complex, is the case of visualizing videos. The paper on the subject was one of my favorite we’ve come across so far. The problem of creating (relatively) simple two dimensional representations of complex four dimensional data is staggeringly difficult and I found their approach surprisingly usable. My intuition was supported by their user study, the existence of which, of course, warmed my heart. However, I was underwhelmed by the success rates for identification in the various conditions. However clever their representation of the data, if it doesn’t reliably communicate what’s going on in the video, then what good is it?
The one part which got me really excited, however, were the examples using real video. The clarity of the bag and box being left and taken as demonstrated in the visualization, where they may have been obscured in the video itself, is a powerful tool.
