People often speak of the “art and science” of data visualization without explanation, as if their meaning is obvious. In fact, it isn’t. What is the function of art in data visualization? Art might serve a role, but if it does, an explanation is needed.
Several years ago when I was talking with Nancy Duarte, author of the books Slide:ology, Resonate, and Illuminate, I said that my work didn’t involve art. She quickly rose to my defense and said, “I disagree!” She assumed that I was admitting a deficiency in my work, but that wasn’t my intention. I was simply saying that my work is rooted entirely in science. I’m not an artist. I’m not trying to be an artist. I love art, but it isn’t what I do.
What do people mean when they talk about the art of data visualization? When they juxtapose the words art and science, they are usually using art as a synonym for creativity. I take issue with this, however, because it suggests that science lacks creativity, which is hardly the case. Good science requires a great deal of creativity. When I say that my work doesn’t involve art, I’m certainly not saying that it isn’t creative.
In the context of data visualization, we ought to use the term “art” with caution. Speaking of data visualization as art can excuse a great deal of nonsense—ineffective design—as the realm of artistic license.
Let’s be clear about something else. When I say that my work in data visualization doesn’t involve art, I am not denying the role of aesthetics. Art is not the exclusive realm of aesthetics. I care about aesthetics in data visualization because they play a role in making graphics effective. An ugly visualization is not inviting, nor does it promote the comfortable emotional state that helps to open one’s mind to information. My understanding of aesthetics and the ways that graphics can be made to please the eye is based on science. Apart from science, like everyone, I have a built-in sense of aesthetics that automatically influences my responses to things. However, the knowledge of aesthetics that primarily influences my work in data visualization—what works and what doesn’t—has emerged from scientific research (for example, from the Gestalt School).
If we’re going to talk about the art of data visualization, let’s do so clearly and meaningfully. Until someone describes the role of art in a way that makes sense to me, I’ll continue to describe my work as exclusively informed by science—both formal research and my own empirical observations.