My take on aesthetics vs. utility in infovis – I promise this will only happen once (unless you meet me in person and want to argue about it):

For context, if you need it: Andrew Gelman’s critique of Robert Kosara’s Infovis example

Above: Kosara’s example from Statistical Computing & Graphics (p. 5)

This is a recurring argument against the aesthetics of infovis: that a straightforward, utilitarian solution is better, faster, clearer. Often these arguments ignore the issue of audience, which has happened (to some extent) in Gelman’s critique of Kosara’s example. Gelman writes (this is very much my own emphasis):

“Of course you’d want to look for day-of-the-week patterns…”

I’d much prefer a simple dot and line plot…”

“Which I would’ve easily noticed using a simpler, more direct graph.”

Ah! I think, but he is not everyone (in fact, he’s a statistics professor at Columbia), and others will be more engaged with the swirls. And then the surprise: Gelman acknowledges the audience! He recognizes the pull of the swirly graph, that it “invites the reader in, it’s intriguing and appealing.”

The real criticism here seems to be that the data presented is “familiar and expected.” In short, it’s boring. From my understanding, Kosara’s visualization (p. 5-8 of that pdf) was created for instruction and example, and doesn’t profess to present the new and unexpected. Boring is boring, and this data is still boring as a dot-and-line plot. Except if you presented sick days as a dot-and-line plot, no one would look at it.

Kosara has wrapped boring up in beautiful; he has made us want to look deeper, but sadly there’s not much inside. Like someone giving you birthday socks gift-wrapped in gold and silk, it feels like maybe someone’s playing a trick, and that’s uncomfortable.

Should we only ever visualize significant meaningful data? Impossible. We have to practice to improve; the more beautiful wrappers we make, the more prepared we’ll be when we find the right data. Only a few people make consistently important visualizations – Hans Rosling and Laura Kurgan come to mind. The rest of us might have a limited number of bright moments where profound insight and beauty intersect. More often we’re slogging through boring inconsequential data, hoping to make something of the mess.

And if we care about our work, we want it to be beautiful, even if the data is unremarkable: phone calls and sick days. Is it deceitful trickery to make the mundane beautiful? Maybe. Maybe we’re wrapping socks in silk. I’d rather have the pretty wrapper to look at, to engage with, and perhaps (as in the case of Kosara’s example) to learn from, and one day apply to a more profound periodic dataset.

I think the aesthetics/utility, statgraphics/infovis argument is false and tired, and I’ve only just shown up to this party. More than tired, I think the argument distracts from a higher concern: in our limited time, to what data should we apply our attention?

Gelman concludes his Chris Rock piece: “The graphs that Seth hates so much do their job in that they look unusual and draw the viewer in to look more carefully and rediscover familiar truth. After that, though, there’s not much more there, and it would be great if they could link to something more informative.”

With this I agree: as much as is possible, people who can make compelling images from data should focus our visualization efforts and (I would say) our discourse on important, meaningful data. If the data is as deep as the presentation is beautiful, the rest falls away.

 

One Response to Why Aesthetics vs. Utility is beside the point, and Meaning matters

  1. [...] jobs or how they are trained, and I don’t want to mislabel them) such as Robert Kosara and Jen Lowe, who seem a bit annoyed at how my colleagues and myself seem to follow the Tufte strategy of [...]

Set your Twitter account name in your settings to use the TwitterBar Section.