Ship space to database: Motivations to manage research data for the deep subseafloor biosphere

Abstract

What motivates data management strategies of scientific collaborations? In this paper, we argue that infrastructures for data management are designed to support scientific work per se and to perform a variety of social functions. We present findings from a longitudinal ethnographic case study of a large, multidisciplinary, distributed scientific project studying subseafloor microbial life. A critical element of this project's plan for data management is to construct an online portal that includes a data registry and data repository. We found that a range of factors motivate the construction of these systems and their features. In addition to scientific concerns for curation and accessibility of diverse and scarce data, we argue that the building of the registry and repository is also motivated by social factors. One factor is the attempt to build a community of domain researchers to endure beyond the end of this project in 2020. Another is the potential use of the registry and database as tools to demonstrate the productivity of the project in negotiations about the allocation of ocean drilling cruise resources. Considering the social and scientific factors together enriches accounts of how knowledge infrastructures are constructed.

Ship space to database: emerging infrastructures for studies of the deep subseafloor biosphere

“…The sociotechnical configurations of each project are shaped by LSST and vice versa (European Space Agency et al, 2016;LSST Science Collaboration et al, 2009). The authors of this paper also are involved in a case study of LSST (Borgman et al, 2015).…”

“…Least studied are situations where ''no data'' exist, whether because no data were collected about a particular phenomenon, data may have existed but were not curated for longer term use, or data still exist but cannot be discovered or retrieved for a variety of reasons (Borgman, 2015).…”

“…However, a major barrier to data circulation and integration is the use of disparate standards by individual scientists, a problem particularly acute when scientists come from different disciplines or communities of practice (Baker, Jackson & Wanetick, 2005;Bietz & Lee, 2009;Borgman et al, 2015;Borgman et al, 2007). Scientists' concerns about control of data, authorship rights, and incentives to undertake the work necessary to make their data shareable also limit the adoption of these infrastructures (Borgman, 2015;Borgman, Wallis & Enyedy 2007).…”

“…Scientists' concerns about control of data, authorship rights, and incentives to undertake the work necessary to make their data shareable also limit the adoption of these infrastructures (Borgman, 2015;Borgman, Wallis & Enyedy 2007).…”

“…However, in many fields data are scarce and hard won (Borgman, 2015;Kitchin & Lauriault, 2014); their problem is the opposite of ''big data.'' Domains suffering data scarcity may have lower epistemic status than those enjoying ''data wealth'' (Sawyer, 2008, p. 355).…”