Why I’m Teaching Data Viz for Sociology
I’m teaching a course for VCU’s digital sociology Master’s degree program this semester. One of the things I’ve asked the participants to do is explain why they’re taking this course. I’m hoping that will help me customize what we’re going to do in the course.
Since I asked the participants to document why they were taking this course, I figured the least I could do is create a similar post explaining why I agreed to shepherd this course and why I made some of these initial choices.
I’m approaching the concept of data visualization pretty broadly. The course is broken into two main components. The first portion is looking at their own portfolio and how they might think it through in terms of data visualization1 and then moving on to broader/deeper applications of data visualization (connected to their personal research). Part of the reason I want to start with the portfolio is that the data is personal and it’s easier to get a feel for how real/accurate any visualizations you make are. We’ll also be able to establish a decent foundation of web literacy, design, accessibility, etc. prior to applying them to more sophisticated visualizations. Essentially, it’s about starting out on more familiar ground before venturing out into increasing complexity.
The second section will focus on figuring out a set of tools and concepts that will directly apply to things the student wants to do. A chunk of this will be looking at and trying out things with various tools and then thinking through the results– both the final data visualization and the process of creating it. There’s some balance of tool cost, author time/effort, the final product’s closeness to your dreams, the tool’s lifespan, etc. that ought to be part of one’s pattern of analysis.2
But I wandered a bit,3 why’d I agree to do this? Teaching a class is actually a financial negative for me. It is absolutely not worth the time it takes to do it compared to what I can make building websites or consulting or editing video. At the root of this particular adventure is the same thing that keeps me entertained in my current job. This looks like a chance to take a deeper dive into data visualization but one driven and constrained by sociology. That’s fun stuff. I think that the audience sought by public sociology, and digital sociology in particular, is ripe for things like interactive explanations. I think that the same people who are attracted to a degree in digital sociology will be interested in pushing the envelope in what’s possible with interactive data visualizations. I hope to help show what’s on the edge of possibilities right now while still grounding things in the desire to reach a diverse audience and to create understanding (or maybe come to new understandings).
There’s also the drive to get into a set of tools. I need to take a fairly wide look around on a regular basis as the tools and frameworks4 are changing so fast and getting increasingly powerful. I hadn’t looked at Tableau in a while and then I saw this parakeets example. Crazy stuff. Keshif continues to improve. R and D3 beckon on the programming side of things and I’ve been revisiting explorable explanations, datasketch.es, basic functions of particular data visualization types, minimalism, Feltron Reports, all kinds of good stuff.
It’s also worth running a class every so often. Can I practice what I believe? Can I do it in a way that’s acceptable to people who are probably used to pretty typical courses?5
Outside this course, I think the knowledge I gain will be useful and I’m going to try to use the course to create content that’s applicable to most people looking to pursue this work.
1 . . . and of course workflows.
2 There’s a bit more to this and it might be worth some more effort to sketch it out with some actual articulation. So this is a footnote saying that I should write better blog posts with actual complete thoughts in them.
3 If I were fancier I’d have digressed.
4 Is everything just a tool?