Does Art Play a Role in Data Visualization?
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.
Take care,
10 Comments on “Does Art Play a Role in Data Visualization?”
Hi Stephen
I think we should find an agreement on the definition of art first, which is not an easy task, though.
Considering art as a mere synonym of aesthetic or creativity is incorrect at best.
While I can agree with you on the fact that art is not involved in your work, there is certainly room to see projects of data visualization on which art or artists could have played an important role in terms of novelty and vision.
Hi Fabio,
Without first defining what we mean by “art,” we cannot begin to identify ways in which art is involved in data visualization. Until its defined, we cannot actually say one way or the other whether my work in data visualization involves art. What I’m getting at is the fact that we cannot meaningfully use the term art in relation to data visualization without first defining it, yet people use it regularly in this context. Let’s either clarify what we mean by art in this context or stop making the claim that data visualization involves art.
Isn’t the ‘art’ of anything not imply ‘art’ but more so the ‘skill’ of something. E.g., the ‘art’ of surgery. So the ‘art’ of data visualisation is really just the skillfulness of it, which I think may imply how well the data is communicated in visual form. For example, I can think of how a histogram would trump a line graph in one situation, and vice versa in another situation. The so-called ‘art’ was the selection of one over the other, given the almost non-scientific manner in which I decided this was the case.
Michael,
I think your observation is accurate. People often use the term “art” in this context as a synonym for “skill.” Used in this way, however, referring to the “art and science of data visualization,” as if they are quite different, makes no sense. Also, when art is defined in this manner, “artistic license” makes no sense. License isn’t needed to do something skillfully. In a recent discussion with a colleague, she described data visualization as an art to justify her decision to do things in her own way, even when those ways are not the most effective. By saying that data visualization is an art as well as a science, she was saying that merits of graphical solutions cannot be judged, because who’s to say that one work of art is better than another. This use of the term art opens the door to a world of ineffective work.
In addition to the observations made already, I think a big part of this goes back to the conflation of ‘art’ and ‘design’.
I know it kind of a cliche to quote the dictionary, but I actually think the first definition that comes up on Google might be informative here:
“art: the expression or application of human creative skill and imagination, typically in a visual form such as painting or sculpture, producing works to be appreciated primarily for their beauty or emotional power.”
We could argue all day as to whether creative skill and imagination are regularly used in data visualization, but maybe the key difference is really the goal of the work. Information visualization should be appreciated primarily for its ability to inform, not its beauty or emotional power. If beauty/emotional impact are present, and enhance the ability to convey information, then maybe that should be celebrated, but it isn’t the point of the work. Conversely, we might argue that the famous graphics depicting the slave ship Brooks aren’t primarily intended to inform (I don’t think they mean to teach the reader how to pack a slave ship, or to measure the efficiency of the slavers), but rather to invoke an emotional response. So, perhaps the latter should fairly be called art.
Would be interested to hear your thoughts on this.
David,
As you pointed out, the definition that you quoted doesn’t fit, because data visualizations are not “works to be appreciated primarily for their beauty or emotional power.†This is not to deny the potential usefulness of beauty and emotional power, but merely to deny the primacy of these qualities in data visualization.
Where does this leave us? The only meaning that seems to fit at all is the one that Michael suggested when he pointed out that by “art†people often mean something done skillfully, as in “The Art of War.†If this is what we mean by art in this context, referring to the “art and science of data visualization†suggests that data visualization should be informed by principles and practices that have emerged from science should be applied with skill. We achieve this by studying the science of data visualization, extended through our own empirical observations, and by developing skill in applying what we’ve learned through a great deal of practice. Understood in this way, “artistic license†is replaced with “wise choices that arise from expertise.†Excuses for data visualizations that fail to promote understanding are banished.
hi Steve,
Moritz Stefaner published a very interesting post today which is related to this topic:
http://well-formed-data.net/archives/1210/little-boxes
Andy
Andy,
Moritz and I think alike on this topic. Form and function, aesthetics and usability, are not in competition with one another–or at least shouldn’t be. When form diminishes function, which is the case with many infographics, it is a result of lazy, unskilled design. When function fails to collaborate with form, it defeats itself.
The discussion that I’ve tried to initiate here is not directly related to Moritz’s article, other than the fact that he also points out the misuse of terms such as art and aesthetics. I am not making a case against art. I am making a case against the use of loaded terms such as art without defining them, which leads to confusion and often to an excuse for ineffective data visualization as well.
In an exchange in my most recent blog about 100% stacked bar graphs, Cole Nussbaumer Knafic clarified what she meant by the term “art” when she spoke of the “art and science of data visualization.” When I pressed for a definition, she responded that by “art” she meant “personal choice.” Art has many meanings, but “personal choice” isn’t one that I’ve previously encountered. I think this illustrates well the looseness with which people use the term “art” in relation to data visualization and the potential for confusion that it creates.