Published online by Cambridge University Press: 01 January 2022
This article considers the temporal dimension of data processing and use and the ways in which it affects the production and interpretation of knowledge claims. I start by distinguishing the time at which data collection, dissemination, and analysis occur (Data time, or Dt) from the time in which the phenomena for which data serve as evidence operate (Phenomena time, or Pt). Building on the analysis of two examples of data reuse from modeling and experimental practices in biology, I then argue that Dt affects how researchers (1) select and interpret data as evidence and (2) identify and understand phenomena.
This research was funded by the European Research Council under the European Union’s Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement 335925 (project: The Epistemology of Data-Intensive Science) and the ARC Discovery Grant Organisms and Us (DP160102989). I am very grateful to Dan Bebber, Robert de Bruin, Midori Harris, Val Woods, Steve Oliver, and the many others who wish to remain anonymous for taking time from their schedules to discuss their research with me. Many thanks also to the audience and other participants in the symposium Data in Time: The Epistemology of Historical Data at the 2016 PSA/HSS meeting in Atlanta, where this article was presented; to participants in the Biological Interest Group in Exeter, particularly Niccolò Tempini, Brian Rappert, Ann-Sophie Meincke, Dan Nicholson, Giovanna Colombetti, Thomas Bonnin, and Staffan Müller-Wille for their comments; and to Adrian Currie, Alison Wylie, James McAllister, James Griesemer, Rachel Ankeny, William Bechtel, John Dupré, and David Sepkoski for useful discussions.