How To Feel Microplastics: Designing a Relational Data Setting
Yanni Loukissas, Ploy Pruekcharoen, Emily Weigel, Miles Appleton, Sylvia Janicki; Academic Research
Abstract
For humans, all data are felt experiences. Unlike our computer systems, which can only be data-driven, we can hold data in tandem with complex feelings about the subjects they represent. In this paper, we share our designs for a public project to “viseralize” (Dobson) data on a large collection of US new stories about the environmental and human health effects of microplastics: the tiny, nearly invisible, and yet ubiquitous debris resulting from the breakdown of commercial products. Set at the center of our university campus, on an architectural-scale media canvas, the project invites local public engagement with a torrent of discordant news headlines, ranging in tone from the pragmatic to the catastrophic. We explain this project as an affective data setting: an arena in which participants can reflect on their feeling based judgements about a subject in relation to “alleged evidence” (Borgman) about it. Our paper, which includes qualitative reflections on both the production and reception of the project, offers lessons for critical data studies scholars, about how public data visualizations resonate on an emotional register. In 2019, All Data Are Local: Thinking Critically in a Data-Driven Society introduced the notion of a data setting as an interpretive context in which a data set is meant to be understood. Here, we explore the research potential in designs for data settings that foreground their affective dimensions. At the heart of the project is a human question, what can data settings do: not just for us instrumentally, but to us emotionally?