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IMADA -Department of Mathematics and Computer Science |
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Research on data science tends to assume a clear-cut separation between data and data work. Such a pre-factual take on data leads to downplaying the data preparation work and front-staging data analytics. Through my longitudinal research on data work in the oil and gas industry, environmental monitoring, and the welfare sector, I realized that data are open-ended knowledge objects that are shaped by ongoing heterogeneous and collaborative practices of data work, including data curation and integration. In this talk, I draw primarily on examples from a qualitative case study of data management in the oil and gas industry to shed light on this often-overlooked work that occurs in the ‘backrooms’ of data science. I discuss how backstage data work is interwoven with data analytics to ensure the stewardship of the data flow across sources, disciplines, and evolving interpretations. Data work consists of practices to make the data sufficiently stable for subsequent analytics and must simultaneously take into account what data it might be possible to get hold of as well as the potential future uses of the data. I conclude by reflecting on how unpacking actual work practices is important to reveal and characterize changes in work and organizing in different domains. This work based on a paper published in the Journal of the Association for Information Systems (JAIS) and written in collaboration with Thomas Østerlie and Petter Grytten Almklov (NTNU). Host: Jacopo Mauro SDU HOME | IMADA HOME Daniel Merkle |