Data visualizations can be designed to look beautiful, if you possess the required visual design skills. The question is, “Should data visualizations be beautiful?” For years a battle has raged between infographic designers who emphasize the importance of aesthetics and data visualizers with a more practical bent who focus on the degree and quality of understanding that results. Those in the aesthetics camp argue that if an infographic is not eye-catching, no one will look at it, and that compromises in the quality of communication are justified as a means to capture the reader’s attention. Those in the optimal-understanding camp argue that the reader’s attention is wasted if the visualization does not clearly and accurately tell its story. In truth, most people have joined one camp of the other, not because of deep thinking on the topic, but because of preferences formed by their experience or lack of it. I’ve tried to occupy a middle ground, pointing out that visualizations can be both aesthetically pleasing and fully informative, without compromising either concern, but that this takes a high degree of visual design and communication skill. While the battle rages, however, fundamental questions are being ignored.
Should data visualizations be beautiful?
What qualifies as beautiful?
If you believe as I do that data visualizations, despite secondary variations in purpose, are always meant to inform, then their effectiveness is determined by the degree and quality of understanding that results. Therefore, a data visualization should only be beautiful when beauty can promote understanding in some way without undermining it in another. Is beauty sometimes useful? Certainly. Is beauty always useful? Certainly not.
What’s always required is that a visualization work for the human eyes, which means that it should not be displeasing to the eyes. A few basic principles of visual aesthetics can be followed—good color choices, legible fonts, proper placement and spacing, etc.—to achieve this result. Making a visualization beautiful is rarely required and it is usually not worth the effort unless your audience is huge and the information is really important. In addition, it can often work against the goal of informing. Making a data visualization beautiful in a way that compromises the integrity of the data always works against you. Even when the information is not compromised, however, beauty can work against you by drawing attention to the design of the visualization rather than the information that it seeks to communicate. Think back over your life and ask: “Were the people who influenced and taught me the most all physically beautiful? If they were wrapped in a different physical package, would that have affected their ability to influence me or my ability to listen to them? Did I ignore information that wasn’t delivered by stunningly attractive people?” Beauty is not the goal of visualization and it is usually not required to achieve the goal.
On those occasions when making a data visualization beautiful is truly useful, we must face the fact that beauty is indeed “in the eyes of the beholder.” What qualifies as beautiful for some is not beautiful to others, beyond the basic aesthetics that I referred to earlier that are rooted in visual perception. Most of what we deem beautiful is a product of culture and experience. If you love wine, as I do, you probably no longer prefer the wines that you found pleasing in the beginning. The fruit-bomb California Zinfandel’s that I loved in the past are no longer palatable to me. I now prefer wines that were crafted in the European tradition to produce greater subtlety and depth of character and to pair well with food.
To further illustrate this point, I’ve found that, when arguing the importance of beauty in data visualization, people often illustrate their position using works by infographic designers such as David McCandless. To my eyes, however, even when I ignore the fact that the information has been ravaged, I rarely find his work beautiful. Obviously, some people see his work differently than I do, but that’s the point that I’m making. Beauty is a fleeting target. What qualifies as beauty varies with the tastes of the audience.
If you’re a gifted graphic artist and communicator and have the skill that’s required to craft beautiful data visualizations when they’re needed, that’s wonderful, and I wish you well. Just don’t hinder the advance of data visualization by arguing that it must always be beautiful. Remember that the goal is to enlighten.