Data Crafting: How Play & Craft Changes Data Comprehension

I recently led a workshop on Data Crafting. The idea (of getting our hands dirty by crafting with data) spontaneously arose in a conversation between myself and Natalie Vladis, a Quantitative Fellow at Harvard Medical School.

Here’s what happened: Natalie loves crafting and lives in data. I love data visualization, occasionally hodgepodge things, and believe that adults don’t play enough. In the month of January, we wanted to facilitate a creative, hands-on play date with data — to make dataapproachableAND to build a space where experts can explore new facets of their data.

The value of play is scientifically grounded. But play in the context of data? That’s relatively new. Most literature in the space focuses on building data literacy in children, and while design has often integrated facets of play to inspire new work, it’s failed to effectively trickle down into its interdisciplinary neighbor, data visualization.

Play comes from curiosity, inquiry, and exploration. By latching on to curiosity and allowing ourselves to explore, we learn new techniques without the stress of expectation or competition, and uncover unknown facets of the world. This is particularly important when we are intimidated by something, or when we have become accustomed to it, associating it with the mundane.

But we think data is austere — perfect — and that makes it hard to play with.

Combine the perceived complexity of data that the general populace maintains (an internalized belief, if you will) with visualizations’ rhetorical force — a major reason why we find it difficult to fact check, debug, and critique them — and we find a conundrum: data and its representations are unapproachable.

By that, I mean data, as an intangible, big concept, is scary. People avoid it. And those that work regularly with data (as analysts, researchers, and scientists) often only understand one idea, one perspective, of what data is and are therefore limited in the ways they can represent and engage with said data. Because again, data feels hard to play with.

That’s how Data Crafting came into being. Data should be fun, should be approachable, should be played with. The best way Natalie and I could think to make that happen is by crafting.