Harvard has something call the J-term or J-semester. Fall classes end in early-mid December and the spring semester doesn't start until late January, but graduate students are still on campus during this very generous break for the undergrads. So, we have something called J-term, or J-semester, and these two-three of January are a period where graduate students and post-docs basically get to offer courses and workshops to each other. It's actually awesome as a concept. We get to take advantage of empty classrooms to try out new teaching methods or materials, fill up those resumes with workshop experience, and learn something new in a concentrated amount of time.

My second year here I took a J-term workshop about data visualization. It wasn't really couched as 'data visualization,' though. It was more like 'Best Practices for Scientific Figures'. It covered CRAP and Gestalt Principles, chart junk, and how to use different color schemes for different data types. It was extremely useful, but I didn't really think about 'how best to visualize things' again for a while.

Fast-forward to summer 2020 and I'm participating in the annual Bok Teaching Conference, remotely from my glorious back-porch (which, coincidently, is where I'm typing this). The theme of this conference was, as you can probably guess, 'Teaching Via Zoom.' I'm in a workshop, for what I honestly don't remember, but as part of our introductions in the breakout rooms we had to describe the classes for which we were going to be TFing (TF = teaching fellow - Harvard's version of TA). I was there for Deep Sea Biology, but then another participant started describing a class that was all about making figures and charts and she showed some insane examples. I was captivated. They looked impressive and I wanted to know how to make them! I enrolled as soon as I could in CS 171: Intro to Data Visualization.

CS 171 quickly became one of my top 5 favorite classes I've ever taken. (I don't really have them rank-ordered, though, because I like them all for different things.) There is something immensely gratifying about data visualization, making something either from scratch or from a template and making it your own, and telling a story. It combined my two favorite parts of academia, science communication and making things, and I loved it.

About every week, we had two major assignments: a lab, which was supposed to a bite-sized project designed to introduce us to some concept or method or practice, and a homework assignment, which combined that new something with almost everything we had learned to date. This started rather simplistically with CRAP and Gestalt principles (hi again, good to see you) and making a basic html page, but quickly ramped up through static visualizations, static visualizations with filtering via a drop down menu, visualizations with tooltips, visualizations that updated each other, and all of the above.

Most of these assignments are described in brief over in the repo read-me, so I won't duplicate those efforts here. But the end-of-semester project, Space Monkeys, is described in another project. Definitely recommend checking it out.