The scholarly record continues to evolve, gathering a wider array of research outputs—including research data sets. In response, universities and other institutions have started to acquire capacity to support data management needs on campus. While services and infrastructure are coalescing around emerging data management practices, guidelines, and mandates, many questions remain about the future of the research data management (RDM) service space, and the university’s role in acquiring and managing RDM capacity in support of their researchers.
How do we approach problems like these that are clearly too big for any one institution to solve? One piece of the solution is to scale learning.