The Process of Familiarity: An Interview with Nicholas Rougeux
By: Jason Forrest
Tags: Data Humanism, Interviews, Data Science, Data Visualization, Art

JF: Can you give us an example of how a mistake or pushing a new idea has fundamentally changed how you looked at a project?

NR: The best mistake that had the most impact was what lead to creating Between the Words, a poster series based on the punctuation of literary classics. In playing around with regular expressions (patterns that help extract text from other text) for another project, I accidentally removed everything but punctuation from a string of text. I thought this looked interesting and tried it with a larger set of text like The Time Machine by H.G. Wells (the full text of which is on Project Gubenberg) and thought it was interesting enough to create a poster series around the idea. I played around with a few ways to include all the punctuation on a poster and landed on using a spiral with each chapter marked. I completed the entire project over the course of a weekend and posted it online with a tweet, not expecting the attention it was about to get.

“Between the Words”, detail of Alice’s Adventures in Wonderland

Thanks to a couple of well-known people in the data visualization community retweeting about it, the project gained a lot of attention and really opened my eyes to the appeal that classical works of art have for many people. Not bad for a weekend project!

JF: How do you select a project or focus on a particular skill or approach you’re interested in learning? Is there anything you’re specifically not interested in? How do you know you’ve found something that sparks your curiosity?

NR: I like to keep an open mind for anything that may cross my path. In a broad sense, sciences and the arts capture my interest the most but if something doesn’t fit under those large umbrellas, I won’t dismiss it out of hand. Lots of things spark my curiosity but I tend to be drawn to items that have some underlying structure that I might be able to tease out to create something new from it.

“Illustrations of the Natural Orders of Plants” Likenesses poster (link)

“Byrne’s Euclid” detailed poster of every geometric illustration (link)

The ‘likenesses’ between the plants Twining illustrated is a good example of this. While there are plenty of diagrams of plant genealogies, to my knowledge, no one documented the specific ones Twining described. I felt this added a new unseen dimension to her work. The poster I created containing all of Byrne’s diagrams is another simpler example. To my knowledge, no one had extracted out all of his illustrations into a single view before. Considering how colorful and varied they are, I thought this would look really fun. Surprisingly, so did many other people! Another more abstract example is my Literary Constellations project where I created constellations based on the parts of speech of first sentences of chapters of classic short stories.

JF: Your “Color Palettes of The New Yorker” project has an explicit design subject matter focus that you then explore with data. What did you learn from a project like that, and can you explain how you might “learn differently” when you apply that kind of data exploration to an art/design project?

NR: That project was the result of me being really determined to do something with a large set of color data. I’ll admit the end product is not as interesting as the process leading up to it where I came up with several dozen experiments in visualizing the data. I learned from all the experiments that trying out different ideas — no matter how abstract they are — can be fascinating and can help on future projects. In devising the methods to produce the images, I learned a lot of new techniques and tools that I can use to experiment with other data to possibly gain more insights. Some of them almost made into a third poster for Twining’s illustrations too (and still might one day).