"Invisible Work" as a Lens for Understanding Humanware's Role in Research Cloud Computing: Evidence from an interview-based study

Researchers in various scientific disciplines are leveraging cloud computing resources to enhance the scale, speed, and portability of research processes and products. Like any other cyberinfrastructure, cloud computing deployment in scientific research requires arrangements of technologies, people, organizations, and institutions to ensure smooth functioning and sustainability. To date, published discussions of cloud computing's promise have often placed technological capabilities and financial benefits front-and-center. These accounts are in line with traditional return-on-investment models for assessing a new technology's viability. The attention to ROI, however, has left assessment of the "invisible" work (and costs) placed on human actors in reaching cloud computing's promise relatively unexplored. In this paper, I report on the findings of 45 interviews with career researchers, research support staff, and student researchers engaged in cloud vendor-enabled research. The purpose of conducting the interviews was to identify commonalities in the labor required to start, maintain, or migrate research processes to the cloud via vendors (e.g., AWS, Azure, and Google Cloud). Two central types of "invisible" labor emerged as themes across the interviews: absorbing the time costs of learning new skills to migrate research to the cloud and managing billing for multiple, decentralized projects. In the discussion, I contextualize these two types of seemingly mundane work in broader debates about the burden new cloud computing technologies might place on scientists and research support staff. I conclude by suggesting that continued documentation and analysis of cloud research-enabling labor is needed to ensure that these invisible costs are understood and, perhaps in the future, shared appropriately among vendors, universities, and researchers.