This spring, I taught a new Freshman Seminar at Princeton ( FRS 154) called “Weird Data,” a CDH course sponsored by the Center for Statistics and Machine Learning. The goal of the course was to provide a wide-ranging introduction to the world of data in all its forms, ideas, and, well, weirdness. A key idea in this semester-long exploration was that data is not a single thing, nor is it usually as simple as we might assume.
The phrase “Data Cuisine” comes from a group of designers in Europe. They coined this phrase to describe a workshop that brings data viz folks together with chefs to explore new, embodied ways of representing data. One member of the group, Moritz Stefaner gave a presentation on the process (watch the presentation here).
I had been wanting to try the workshop in classroom for a while, but it had proved tricky to translate into an undergraduate humanities course. The workshops in Europe used a lot of scientific and economic data. They had access to full kitchens and trained cooks, with plenty of time and ingredients to try out new ideas. We wouldn’t have any of that in a classroom. But maybe we could try! I went to the grocery to look for foods that would have some kind of distribution of colors, tastes, and sizes. That wound up including condiments (mustard, ketchup, BBQ sauce) and candy (jelly beans, Starburst, Peeps, Fun Dip).
We began by reading a bunch of essays on “data.” We tried to teach ourselves how to question not just the data but the categories themselves. Who determines the categories, and what are the consequences? Rather than simply adopt the data viz practices so common in corporate environments, we took inspiration from what Giorgia Lupi calls “data humanism.” How does the representation of data shape what we see, how we think, and how we exist in the world? Do we always have to contort ourselves to correspond to data? Or can quantitative displays respond to the messiness of our lives, cultures, and identities? The course covered many approaches to these questions.