Jer Thorp, Data Artist in Residence at the New York Times and creative coder extraordinaire, explains the process behind his latest piece for Popular Science in a recent article. The task at hand was to visually represent the complete archive of their publication. The final piece is anchored by a kind of molecular chain – decade clusters in turn contain year clusters. Every atom in these year clusters is a single issue of the magazine, and is shaded with colours extracted from the issue covers via a colour clustering routine. The size of the issue-atoms is determined by the number of words in each issue.
Picking out interesting words from all of the available choices (pretty much the entire dictionary) was a tricky part of the process. I built a custom tool in Processing that pre-visualized the frequency plots of each word so that I could go through many, many possibilities and identify the ones that would be interesting to include in the final graphic. This is a really common approach for me to take – building small tools during the process of a project that help me solve specific problems. For this visualization, I actually ended up writing 4 tools in Processing – only one of which contributed visually to the final result.
It’s excellent to get a glimpse at how such complex yet elegant solutions come together and what decisions were taken along the way. See the related set on Flickr to visually follow the development of the graphic. This isn’t Jer’s first process documentation and if you are not familiar with his work, I strongly recommend to have a look.
Jer Thorp is a software artist, writer, and educator. He is a contributing editor for Wired UK. He is currently Data Artist in Residence at the New York Times.