WORKSHOP: Data Management and Data Sharing Workshop for Science and Technology Studies

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This award will fund a workshop that will bring together key members of the STS community to engage in intensive discussions about data management issues. The need for the meeting is initially driven by a recent requirement implemented by NSF; each research proposal is now required to have a suitably adequate data management plan. The requirement is generally formulated; NSF recognizes that there is a vast array of scientific research cultures with differing practices of data management. Moreover, these many such cultures (including STS) address pertinent data-management issues in widely different ways. Issues include what constitutes data, and how data should be characterized, formatted, securely stored, and made broadly accessible for re-use by others, while also addressing concerns of privacy and the need at times to grant only limited access. The workshop will focus on articulating current needs, as well as proposed responses and solutions, for development of effective data management principles and routines in the STS domain. The workshop organizers have four distinct goals: (1) to generate provisional templates for data management plans for individual projects across the diverse fields of STS. (2) To produce a workshop report that summarizes the discussions with a focus on current and future needs and existing and possible solutions (including the templates); the report will be made broadly available on an existing secure, open-access repository at Arizona State University. In addition, they will produce two white papers. One white paper is (3) to be circulated to members of the STS community and to other research communities through professional societies to solicit input and work toward a shared understanding of infrastructural needs. Another white paper will (4) outline opportunities for computational work that will become possible only if the communities establish robust data management strategies; it will outline future strategies for taking advantage of opportunities for computational work in the diverse STS fields represented that is predicated on available and accessible data. The white papers will address how STS fields can implement strategies of data driven science and will consider what benefits would accrue from doing so.