In the Backrooms of Data Science
Peer reviewed, Journal article
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Much Information Systems research on data science treats data as pre-existing objects and focuses on how these objects are analyzed. Such a view, however, overlooks the work involved in finding and preparing the data in the first place, such that they are available to be analyzed. In this paper we draw on a longitudinal study of data management in the oil and gas industry to shed light on this backroom data work. We find that this type of work is qualitatively different from the front-stage data analytics in the realm of data science, but is also deeply interwoven with it. We show that this work is unstable and bidirectional. That is, the work practices are constantly changing and must simultaneously take into account both what data it might be possible to get hold of as well as the potential future uses of the data. It is also a collaborative endeavor, involving cross-disciplinary expertise, that seeks to establish control over data and is shaped by the epistemological orientation of the oil and gas domain.