Why Data Science Needs Curation and Why Curation Needs Data Science

Curation has become a new buzzword for everything from the craft of carefully selecting ingredients for a chef-curated menu to algorithmic filtering of massive news feeds. Legitimate concerns about the purpose, transparency, results, and scale of curation practices and methods lie beneath the surface of curation mania. The premise of this talk is that advancements in data science will depend on vast improvements in methods and tools to curate data. The current "state of the art" in curation is very focused, context dependent, and hands-on. In this talk I will identify areas for research and development based on shared goals across the data science and curation communities.
Margaret Hedstrom is the Robert M. Warner Collegiate Professor of Information at the University of Michigan where she teaches in the areas of archives, collective memory, and digital curation. She was PI for two large NSF-sponsored projects: SEAD (Sustainable Environments "“ Actionable Data) and an IGERT traineeship called "Open Data." She was a member of the Board for Research Data and Information, National Academy of Sciences and chaired the National Research Council study committee on Data Curation Workforce and Education Issues. She has served on numerous national and international boards, including the National Digital Strategy Advisory Board to the Library of Congress, the Advisory Committee on Historical Diplomatic Documentation, U.S. Department of State, and the ACLS Commission on Cyber-Infrastructure for the Humanities and Social Sciences. She earned a PhD from the University of Wisconsin in 1988.