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.

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Theoretically, this article seeks to broaden the conceptualization of ignorance within STS by drawing on a line of theory developed in the philosophy and anthropology of education to argue that ignorance can be productively conceptualized as a state of possibility and that doing so can enable more democratic forms of citizen science. In contrast to conceptualizations of ignorance as a lack, lag, or manufactured product, ignorance is developed here as both the opening move in scientific inquiry and the common ground over which that inquiry proceeds. Empirically, the argument is developed through an ethnographic description of Scroggins' participation in a failed citizen science project at a DIYbio laboratory. Supporting the empirical case are a review of the STS literature on expertise and a critical examination of the structures of participation within two canonical citizen science projects. Though onerous, through close attention to how people transform one another during inquiry, increasingly democratic forms of citizen science, grounded in the commonness of ignorance, can be put into practice.

The FITS file format has become the de facto standard for sharing, analyzing, and archiving astronomy data over the last four decades. FITS was adopted by astronomers in the early 1980s to overcome incompatibilities between operating systems. On the back of FITS' success, astronomical data became both backwards compatible and easily shareable. However, new advances in astronomical instrumentation, computational technologies, and analytic techniques have resulted in new data that do not work well within the traditional FITS format. Tensions have arisen between the desire to update the format to meet new analytic challenges and adherence to the original edict for FITS files to be backwards compatible. We examine three inflection points in the governance of FITS: a) initial development and success, b) widespread acceptance and governance by the working group, and c) the challenges to FITS in a new era of increasing data and computational complexity within astronomy.