Labor Out of Place: On the Varieties and Valences of (In)visible Labor in Data-Intensive Science

Abstract

We apply the concept of invisible labor, as developed by labor scholars over the last forty years, to data-intensive science. Drawing on a fifteen-year corpus of research into multiple domains of data-intensive science, we use a series of ethnographic vignettes to offer a snapshot of the varieties and valences of labor in data-intensive science. We conceptualize data-intensive science as an evolving field and set of practices and highlight parallels between the labor literature and Science and Technology Studies. Further, we note where data-intensive science intersects and overlaps with broader trends in the 21st century economy. In closing, we argue for further research that takes scientific work and labor as its starting point.