The Aesthetics of Data Settings (Inside Intrenchment Creek)

 

In the summer of 2021, I made a 9-minute video about a data physicalization project I put together in my home (isn’t that where everything happens these days?) The assemblage focuses on a small scale waterway that runs directly behind my house called Intrenchment Creek. The creek is an emergent and interstitial aesthetic realm, between domestic spaces on abutting properties and what William Cronon would call “wildness,” as opposed to wilderness. This wildness draws my two small children, Felix (almost 6) and Sonja (4), as with many plants and animals that dwell there. But it is increasingly under threat by development in Atlanta, that is following a wave of gentrification across the city. New construction decreases the area of permeable surface in the city, sending runoff, debris and even raw sewage into the creek.

In my efforts to explore and expand my relationship to the creek, I have turned to data. I downloaded publicly available water quality data for 2020 from a USGS website and explored it with help from Georgia Tech biologist Emily Weigel. Weigel drew my attention to important changes indicated in these data as increased flow rates and turbidity levels. These signal a range of threats to the health of the waterway, and its surrounding ecosystem. I wrote a program in P5.js – a JavaScript programming environment – to identify and graphically present data from moments of unusually high turbidity, in relation to precipitation, water height, and flow rate. But I wanted to go further – to bring the creek home sensorially, in a way that even my children could grasp.

So, I built a material data assemblage in my house, that combines the graphic output of my program with common domestic things: a wall, string, screw hooks, wood dowels, mail tags, and twelve small rubber ducks. The ducks are a deliberate aesthetic choice. Cute, tactile, playful, soft, cheap, and disposable; they introduce an alternative to the purportedly neutral conventions of contemporary data visualization, for example: dots, circles, or lines.

In “The Stuff of Bits,” Paul Dourish brings critical attention to the material design of our representations of data. Design for data—as much as anything else—is what Don Schön calls a “reflective conversation with materials.” Here I am bringing many materials into the conversation. Not just digital materials, but also the space of my house and the objects within it. The result is not a data set, but a data setting: a new interpretive context in which the data are meant to be understood. This assemblage suggests how we might create alternative reflective and expressive conversations with data, when we do not expect data to speak for themselves.