This semester, I took a course at Marymount on Data Visualization. The focus of the course – which included both teachers and students in the same classroom – was on using the Processing programming language as a means of pulling in, parsing and representing data.
The course was note, by any stretch of the imagination, easy. Our facilitator, Annelie Berner, challenged us by putting the learning in our own hands. If we asked a question, the answer we got was usually “Well, how would you deal with it?” This required us to think about the implications of what we were doing, and how best to resolve the issue.
More importantly, the course challenged all of us to look at data in new ways. No longer were we representing data with a scatter plot. Data could be represented with images, sounds or videos. And no longer did data need to be represented in an 8 1/2 x 11 format. Data could be two dimensional or three dimensional, and if you included time, four dimensional.
For my final project, I originally wanted to represent severe weather events on a map based on Twitter reports. The problem I soon rant into was that the data just wasn’t there. So I went back to the beginning of our course, where we pulled data from the Guardian UK site. I found the entry/exit data by week for all of the London Undergound stations. Using TileMill, I was able to visualize the data with larger red circles meaning more entries and exits.
I then overlaid on this the locations of pubs in London. In the CBO, there were more pubs near the more heavily traveled Tube stations. But as you got further away from the CBO, pubs were actually located further away from the Tube stations. Actually, if you look at the graphic below, the further you got away from CBO London, the more likely the pub locations were to be in between the Tube lines!