Find the story in the data, or find the data to tell the story?
Dataset selection as a creative constraint
In a way, this is the silliest question. If you’re a professional data practitioner and your main work with data happens during the course of your 9-to-5, then the point is moot. The data are assigned to you. Depending on your industry (and your luck), the work datasets may be fascinating. Or not.
If you have — or make — the luxury of time for extracurricular data visualization, my question might be meaningful to you.
I’m a consultant, so I choose which clients to work with, narrowing down the domains my datasets can come from, but some types of data are as inevitable as death and taxes. Like transactional data, for example.
Setting aside a large portion of reality, let’s assume I have full control of a project.
Sometimes — mostly when I do what I call in my head “activizm” — I have a topic in mind that I want to viz about. Like the cost of housing in the city where I live. Or the gender wage gap in data visualization. Or the pace of the warming of the planet. Or, my favorite to date, the frequency and nature of the protests about the war in Gaza on college campuses.
Sometimes I have a hot take I want to back up with facts. (Facts! Ha!)
Most often, I’m reading something. I get curious about an aspect of it. I hunt down or create a dataset. (Creating datasets is my favorite form of “productive” procrastination.)
I relish the research process. I love gathering links and documents, creating Google Sheets out of chaos, and pulling together every data point related to my topic.
I also enjoy exercises in freedom-as-discipline/discipline-as-freedom, like imposing an arbitrary constraint on myself to inspire new creative ideas. Recently, I challenged myself to create a mobile view in Tableau. I’m learning d3.js, so the constraint there is really my abilities, but it’s also enjoyable.
Freedom to a dancer means discipline. That is what technique is for — liberation. — Martha Graham, American dancer and choreographer
To harken back to the title of this post, my process leans towards find-the-story-in-the-data. The Tableau Iron Viz qualifier is really a find-the-data-to-tell-the-story situation (and possibly also a cram-the-story-into-the-boundaries-of-the-theme situation). So if I don’t like the theme, ADHD Brain be like 💤💤💤
This year’s theme, “Viz what you love,” feels good for where I am in my dataviz trajectory. I’ve been grinding away at consulting work to pay the bills, and getting a bit tired and uninspired in the process. So I cut back my workload for a bit to Iron Viz. (Which I know is an incredible privilege.) When considering the theme, I was reminded of all the people, places, subjects, and things I do love. And from there I had a topic, but I needed data. It’s been fun finding the data to tell the story and to change up my process a little.
