Meet Datanami 2021 Person to Watch Mike Bostock
If you’ve ever wondered how best to present a particular piece of data using a visualization, then you’ve entered Mike Bostock’s world. From the New York Times to his latest startup, Observable, Bostock has been pushing the state of the art for data visualizations. We recently caught up with Bostock, who is one of the Datanami People to Watch for 2021.
Datanami: How did you become interested in data visualization? What was your first inkling that you could make a career of this?
My first serious foray into visualization was at Google, where I worked with Melody (my future Observable cofounder) on a team responsible for evaluating search experiments. Engineers would invent tweaks to ranking; our job was to provide a quantitative, comprehensive view of how these tweaks would affect the overall user experience. Often changes targeted a specific class of query (say, natural language questions) but might have unintended effects on other queries. Our metrics would score experiments from 1 to 5, the idea being that a high score would clear a change to land. Yet when an experiment scored poorly, engineers would often question the metrics’ accuracy. Visualization became a way to surface more evaluation data — as opposed to black box metrics — so we could make better informed, more accurate decisions.
Luminaries would often visit Google, so I also had the privilege of seeing Edward Tufte and Tamara Munzner (and others) speak. This opened my eyes to information visualization as a formal practice, and eventually led to me going back to school, to Stanford. At that point I suppose it was my career.
Datanami: You founded Observable with Melody Meckfessel in 2016 after working in the graphics department at The New York Times. How did your experience with journalism at the NYT inform your mission at Observable?
Bostock: My time at The New York Times reaffirmed my belief that visualization is a powerful medium for communicating insights to any audience — it’s not just for scientists, statisticians, quants, etc. Perhaps my favorite graphic from that era was “512 Paths to the White House” (in collaboration with Shan Carter, who now leads design at Observable); I love how this graphic provides a “macro” view of all possible outcomes of the 2012 presidential election. Talking heads love to pore over obscure what-if scenarios, regardless of their improbability; our graphic was a counterpoint that let you see everything at once and get a better sense of what might happen.
Shan Carter and I also built a system, Preview, that allowed everyone in the graphics department to see in real-time what everyone else was making; like a GitHub for graphics, you could see not only the live in-development graphic, but all previous versions and branches. Shan and I (and later, Jennifer Daniel) were based in San Francisco, and Preview dramatically improved our ability to collaborate with the rest of the department on Eighth Avenue. This notion of bringing transparency, openness, and collaboration to data analysis and visualization is central to Observable’s vision.
Working on published graphics also convinced me that data visualization was still too hard, too expensive, and despite its potential for discovery and communication, underutilized. So Melody and I founded Observable with the goal of making visualization more approachable and more practicable — without giving up its essential creativity and expressiveness. We call this “lowering the floor without lowering the ceiling.”
Datanami: What is the most non-intuitive thing about data visualization that you can tell our readers? What continually surprises you about the nature of your work?
Bostock: There’s a tendency to assume that visualization is a superpower — a magical lens that somehow reveals every nuance of data by virtue of making it visible. In reality a visualization must be designed with a specific question in mind (or perhaps a small set of related questions), similar to a statistical test, and it answers only that question. Furthermore, a visualization is not an agnostic or impartial view of data, as its design strongly influences interpretation. And data itself has bias! This all suggests that care must be taken when designing visualizations — we can’t simply “splat” data to the screen — and when reading them. The effect of design may be revealed by redesigning, a form of critique that is facilitated by Observable’s fork button. (Though see Viégas & Wattenberg’s “Design and Redesign” for risks and guidelines on doing this fairly and constructively.)
Another underappreciated quality of visualization, I think, is the difference between exploratory and explanatory visualization. Exploratory graphics you make for yourself to find new insights in data. Explanatory graphics in contrast communicate some known insight to an audience. The goal of exploratory visualization is primarily speed: how quickly can you construct a view that answers your question? You can afford to cut corners when you’re the intended reader, as you already have context. Whereas you must provide explicit context for an explanatory graphic. A good explanatory graphic should know what it’s trying to say, and say it. Explanatory graphics can include exploratory elements, for example allowing the reader to “see themselves” in the data, but ideally these shouldn’t detract from the primary message. Don’t make the reader work for insight; that’s your job as the editor.
Datanami: Outside of the professional sphere, what can you share about yourself that your colleagues might be surprised to learn – any unique hobbies or stories?
Bostock: Back in the pre-pandemic days (“the before time”), I would commute daily from Marin to Observable’s downtown San Francisco office by bike, which was about 17 miles each way (with a nice climb at the end). I absolutely loved it. It’s so much less stressful than being stuck in a car in traffic. And getting to see the Golden Gate Bridge in all sorts of weather and light was awe-inspiring. I’d often stop to admire the view, say of the towers poking out of the fog, or a massive container ship sliding off into the sunset. If you can, ditch your car in favor of walking or biking. Sadly these days I rarely leave the house… Hopefully I’ll be back in the saddle again soon.
Bostock is one of 12 Datanami People to Watch for 2021. You can read the interviews with the other honorees at this link.