(University of Washington)
Paper Short Abstract:
Amidst the so-called data deluge, industry cloud providers are emerging as key partners for domain scientists seeking to expand computational capacity. This gives rise to novel forms of currency and (ac)counting practices, producing what I call 'situated valorizations' of resources and engagements.
Paper long abstract:
Ever greater scales of storage and computing power are required as data-intensive research increases its reach and scope. Industry cloud providers surface as key partners for domain scientists as they both work to keep apace. This paper draws from ongoing ethnographic fieldwork with a collaboration between a large industry cloud provider and a group of 'domain' researchers in the life sciences, where the latter deploy the former's resources in their data-intensive scientific workflows. Here, I focus on two innovative features of this collaboration:
(1) Computational resources as currency: I refer here to the practice by which the cloud provider allots a predefined amount of computational resources - what are known as 'cloud credits' - along with technical support free of charge to the scientific researchers.
(2) Novel (ac)counting practices and valorizations: The cloud provider apprehends the domain scientific work first as an abstract set of spikes and dips in an online portal, which provides an account of when the scientists are actively 'spending' their credits. The domain scientists are subsequently prompted to map their scientific practices onto those abstract figures, giving the provider a more substantive account of how they are using their cloud credits.
In this process, both sets of actors are brought not only to evaluate their mutual engagements, but also to produce further 'situated valorizations' that extend to a diversity of spheres - ranging from the creation of compelling marketing materials to deploying user-centered design practices such that cloud platforms can enrol and accomodate increasingly heterogeneous domain-users.
Technologies that count: big data and social order