Seminar | January 24 | 3:10-5 p.m. | 107 South Hall
Over the past year Iâve been doing a good deal of thinking about the broad way weâve framed the work of research data management and preservation, and the roles of various parties (researchers, data curators, repositories, etc.) in this effort. The dominant model to date has been one of describing datasets, archiving them into repositories, and assuming that they will be discovered and reused by other scholars.
Iâll critically examine this model and some of the ideas â for example, the FAIR principles, privacy challenges, and widespread use of machine learning â place great stress on this model, along with the proliferation of what Iâll call âscholarly information aggregation and management environmentsâ. Iâll speculate about what these developments may imply for how to reformulate the research data management enterprise, including some discussion about implications for funding, roles, and resource allocation and prioritization.