Abstract

Data archive and database design have typically fallen under the purview of data workers who seek to create a seamless vision of data integration. Following the technical practices of data work, this research seeks to provide theoretical scaffolding to inform the design of data archives and interfaces that treat the history of datasets as seamful, that is, as selectively revealing the heterogeneous transformations that data undergo from their generation to the present. Drawing on ethnographic and historical investigations of data interoperation efforts in the State of Alaska’s Salmon and People (SASAP) project, we retell a series of debated and negotiated alterations of datasets. From these vignettes, we extract a common set of transformations that data undergo, which we call data genealogies. Usually, following closure of negotiations, datasets reveal little to nothing of the debates that went into them; however, our approach will seek to keep present these narratives of data transformation.

Keywords:

data; seamful design; ethnography; salmon

Creative Commons License

Creative Commons Attribution-Noncommercial 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial 4.0 License

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Jun 25th, 12:00 AM

Data Streams, Data Seams: Toward a seamful representationof data interoperability

Data archive and database design have typically fallen under the purview of data workers who seek to create a seamless vision of data integration. Following the technical practices of data work, this research seeks to provide theoretical scaffolding to inform the design of data archives and interfaces that treat the history of datasets as seamful, that is, as selectively revealing the heterogeneous transformations that data undergo from their generation to the present. Drawing on ethnographic and historical investigations of data interoperation efforts in the State of Alaska’s Salmon and People (SASAP) project, we retell a series of debated and negotiated alterations of datasets. From these vignettes, we extract a common set of transformations that data undergo, which we call data genealogies. Usually, following closure of negotiations, datasets reveal little to nothing of the debates that went into them; however, our approach will seek to keep present these narratives of data transformation.

 

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