Data Visualization is driven by data. Its form is often derived from optimizing the efficiency of inputting data (and information about that data) into a human brain. It is a very pragmatic practice, built around numbers and logic. And yet it is beautiful. It evokes emotions. It can be aesthetically pleasing, or hideous. It communicates complex concepts and provokes thought. It is consumed for enjoyment. Some visualizations even share similarities with poetry.

A National Portrait of Drunk Driving infographic by johnmnelson.

There are several stages in the life cycle of data visualizations, and while the core of the practice is driven by rational thinking, any number of stages in the process have opportunities for subjective decisions or artistic interpretations.

Creation

The topic covered by a visualization is the starting point for the process of creation. Just like in many art pieces, this is where the inspiration begins. The decisions made during this stage determine the mood of the piece, and the concepts it addresses. Another opportunity for artistic decisions is in the architecting of the visualization. Deciding on the form that the visualization will take on, determining connections between the data and the visual variables, and setting up the structure of the visualization are all points for artistic decisions. These decisions often have optimal choices, but choosing what to optimize for is where human creativity sneaks into the process. This stage doesn’t just determine what the visualization will look like, but the details of what it communicates, and what data it prioritizes. (by Giorgia Lupi of Accurat) In addition to the visualization itself, there is a whole range of graphic design decisions that are made to support it. Layout, color scheme, font selection, and any elements that add visual hierarchy are all opportunities for creativity. This process is often closely tied with the architecting stage, and sometimes the line between the two blurs, but that only increases opportunities for artistic decisions.

Speed Comparison Chart infographic by gDigitalAgency.

It’s interesting how those little decisions—the slightly bolder color on one bar, the odd curve of a line, a label that draws a smirk—start to accumulate in a finished visualization. These aren’t arbitrary; they’re the result of a thousand micro-judgments, quick fixes, or vague rules of thumb that are honestly more art class than statistics. If you’ve ever stumbled across a chart that just “felt off,” it’s probably because the creator made one of those choices without noticing. And sometimes those quirks are exactly what make a piece memorable. Whether it’s personal or just eccentric, the impression sticks around longer than you’d expect.

Sometimes, too, the backstory of a visualization quietly shapes its entire tone. Maybe the original dataset was patchy, or the client wanted something “bold” without knowing what bold even means in context. These offhand requests or quirks in the source material can send the design down a path that’s totally unforeseen. It’s a tug-of-war between fidelity to the data and the sometimes chaotic realities of the project—the kind of thing that would never show up in a legend but absolutely changes what you see on screen.

Consumption

After a visualization is created, people view it (that is the point, after all). Sometimes visualizations are consumed privately, especially if they show sensitive data. But often, they are publicly shared in printed publications, video formats, or on the internet.

Worldwide Internet Users infographic by jkan.

Privately viewed visualizations are typically very functional, as the investment into their aesthetics tends to be lower. Publicly viewed visualizations are still functional, but they have often had much more time invested into improving their appearance. Many people consume them for enjoyment. They spur conversations on cultural issues, and trigger emotions.

Titanic – Class and Gender selected survivors infographic by newsillustrator.

The obvious answer here is that data visualizations can be art. They share similar processes to art creation, and they are viewed in a similar manner. If you create visualizations, keep it up — and start thinking of yourself as an artist if you don’t already.   Drew Skau is Visualization Architect at Visual.ly and a PhD Computer Science Visualization student at UNCC with an undergraduate degree in Architecture. You can follow him on twitter @SeeingStructure

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