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The processes of data collection and transformation are often opaque to users. This means they rely on their imagination to make sense of the data they produce. The images data conjure up, however, tend to be homogenous and flat: black screens, ones and zeros, big server farms in the desert. For designers and researchers who work with data as a material, this small repertoire can be stifling. For device users, it can lead to a removal of agency in how they make sense and engage with the data they produce. In this pictorial, we draw from a two-year data fictionalization project to start building an expanded repertoire of data imaginaries. We worked with seven households and seven writers to transform smart home data sets into fiction stories. Based on the interviews we conducted, we present the images participants shared with us as a step towards more expressive and varied imaginaries of data.
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This content will become publicly available on December 31, 2025
Un/Making Data Imaginaries: The Data Epics
With the increase of Internet of Things devices in home environments, data will become an even more dominant part of people’s everyday lives. The invisibility of data leads us to rely on our imagination to make sense of them, yet this imagination is heavily shaped by a technocentric lens that views data as neutral and transparent. In response, in this article, we present the Data Epics project, where we commissioned seven fiction writers to write short stories based on smart home device data provided by seven households. We offer an analysis of the writers and households’ experiences with the project, presenting seven ways in which data imaginaries are made and unmade. We contribute a reflection around how making new data imaginaries unmakes common ones, the friction in unmaking certain imaginaries, and how we might further disseminate alternative data imaginaries.
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- Award ID(s):
- 2236822
- PAR ID:
- 10584013
- Publisher / Repository:
- ACM
- Date Published:
- Journal Name:
- ACM Transactions on Computer-Human Interaction
- Volume:
- 31
- Issue:
- 6
- ISSN:
- 1073-0516
- Page Range / eLocation ID:
- 1 to 38
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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