Why I Do What I Do

The last few months have been so busy that I haven't written as much on this blog as I would otherwise like. Everything is going very well, but I've added a few things to my plate and I often consider my good fortune to be able to include so many valuable activities in my life in addition to my rewarding "day" job, my great family and incredible wife, and my good health. Especially with the world facing so many challenges today, we have to model being good to each other and that's something that I try to do every minute of every day.

Since May 2021, I've been an adjunct professor in the graduate data analytics and visualization program of the Maryland Institute College of Art, one of the country's oldest art schools which has more recently developed programs to take advantage of the nexus between art and design, analytics, and insight generation. So far, I've taught courses in data storytelling and industry case studies, which have opened my eyes to how the profession is developing and what people new to it want to know. It's also influenced my own work in data visualization, both on my own time and in my regular work. I'd like to share those insights here.

Inclusion

This is the big takeaway that I have from the last few months. Coming out of the Black Lives Matter protests and first thinking about the kinds of examples I wanted to discuss in my teaching, it became important to make sure that the examples I chose didn't only come from my own experiences. This led me to learn as much as I could about W.E.B. DuBois's data portraits of Black America at the turn of the 20th century, and also to study the accomplishments of the Black Aces, the set of Black 20-game winners in the major leagues that the late Mudcat Grant profiled in his book of the same name.

Inclusive data design is a big theme in the course that I'm teaching right now, and in my work as a data visualization advocate at NIH, my team and I think a fair amount about accessibility -- a related concept about designing specifically for people with disabilities. I've come to admire the work of Kat Holmes, a user experience designer at companies like Microsoft and Google whose book Mismatch explains a great deal about how to approach inclusion in design; specifically, the notion that a disability is not a medical condition, but a mismatch between human interactions. Mismatches can be temporary or permanent; and they can be physical but also emotional or experience-based. So "designing for all" comes to mean designing for many types of people, with many experiences, to exclude as few as possible.

Antiracism

When the country was still mired in the pandemic and the BLM protests were still fresh in memory, I read Ibram Kendi's book How To Be an Antiracist. The book offers a stark contrast between racist behavior and antiracist behavior, and assumes that someone is either one or the other. It resonated with me a lot, because growing up Jewish, I was raised to have a strong sense of social justice and a firm belief that all people were created equal, especially bearing in mind the prejudice that has affected the Jewish community throughout history -- even if the people around me sometimes showed unconsciously, or even consciously, that they couldn't live up to the aspiration. At first glance, Kendi's argument sounds a bit harsh -- knowing that there are many gradations of human behavior but in another, it provides a clear call to us to go beyond saying that we are "not racist", but to find ways to combat racism actively and to therefore be antiracist. 

This has informed my work in a couple of different ways. Firstly, I'm much less tolerant of racism where it exists. I'm aware that I have benefitted from racism, and sexism, as a White male person in ways that I did not ask, and that I do not approve of, but those privileges unfortunately exist. And I see my role as a teacher and advocate of data visualization, in part, as showing how data and visuals can help show how we can combat conscious and unconscious bias.

Earlier this year, Baseball Reference and SABR released The Negro Leagues are Major Leagues: Essays and Research for Overdue Recognition, which celebrates the elevation of the Negro Leagues, as they were called when they provided a professional league for Black ballplayers otherwise excluded from professional baseball, to the status of major leagues. Inspired by the book, I downloaded team and league data from all leagues for the seasons between 1920 and 1948 (often thought of as the "golden years" of Negro League baseball) from Stathead and created a visualization showing winning percentages, offensive data, and pitching metrics between the various leagues. (See the screenshot below, and the link to the interactive visualization is here.)

The major takeaway from this analysis is that the level of play in what was then called the Negro leagues was just as good as that which was seen in the White major leagues. This made for some great conversation with the Almost Cooperstown podcast, with whom I've been doing some other collaborations that you will hear more about this spring.

I've used my skills as a data visualizer not only in looking at professional baseball statistics, but also to elevate the accomplishments of the Tuskegee Airmen, the first all-Black fighter group in what became the United States Air Force, which fought with great distinction in World War II. (This is the image at the top of this blog entry, and you can also click here to see the interactive visualization on Tableau Public.)

Creativity

Teaching data visualization at an art school is something that I tremendously enjoy, and while the students I teach are not painters or sculptors, they have chosen the program because they value the aesthetics and creativity that, along with sound analytics and insight, are at the core of data visualization. It's a reminder that we don't simply visualize data for visualization's sake, but we do so because we are trying to teach, or improve an experience or area of business, or to expand the historical record, and we do it visually and artfully because human beings are inherently visual. (And even for those people whose sight is limited, sonification offers a way to render information in a way that delights the senses, as this sonified data file from NASA's Chandra X-ray observatory makes clear.)

For my work, that means taking every opportunity that I can to create works that are aesthetically pleasing, not only as data visualizations but also as creative pieces themselves. I've painted directly on vintage baseball cards, which are the major part of this blog, but I've also made paintings on canvas to go with data visualizations, and I've also recently made a painting of Ukrainian president Volodymyr Zelensky to memorialize this particular time in history.

Taken together, these three elements make up a statement of what I believe.

I believe that when we create or otherwise bring something into the world, the thing that we create is for everyone -- whether that is our intended objective or not.

I believe that we as a society need to embrace antiracist principles and, wherever possible, to present our work in an antiracist context.

I believe that creativity -- in all its forms -- is the highest form of human endeavor, and that every single human being is capable of creating in some form.

I realize that some of the sentiments I'm expressing here may be somewhat contentious, and even political in nature. However, I see them as extending beyond politics, and in my role as a teacher, advocate, and practitioner of data visualization, I think a focus on accessibility, diversity, and inclusion is a way that we can make sure that everyone can point to the practice of creating things and say, "yes, that's for me."

I'll be showing more here: more card art, visualizations, and other work--and I hope that you will engage in discussion about why you do what you do.