Although data-driven research is already accelerating scientific discovery, substantial systemic challenges in academia need to be overcome to maximize its impact. Toward that end, working in partnership with one another and with the Gordon and Betty Moore Foundation and the Alfred P. Sloan Foundation, three universities (the University of California Berkeley, New York University, and the University of Washington) have been attempting to create supportive environments for researchers using and developing data-intensive practices. Known as the Moore-Sloan Data Science Environments (MSDSE), this collaboration is structured through a set of working groups on cross-cutting topics viewed as critical to advancing data science in academia: career paths and incentives, software development, education, reproducibility and open science, reflexive and reflective ethnography, and the role of physical space in collaboration. This project briefing will cover the efforts and activities of the MSDSE partnership and share some of the best practices and lessons learned that have emerged from five years of collaborative institutional experimentation, from cross-domain workshops and project incubators to the challenges of creating (and filling) new staff data scientist positions outside of any one particular lab or discipline. This briefing will also report on a recent landscape overview of data science in US research universities completed by Abt Associates as part of an evaluation of the MSDSE partnership, as well as a recent leadership summit of data science faculty leads from universities across the country.
Additional authors: Josh Greenberg (Sloan Foundation), Chris Mentzel (Moore Foundation)
www.msdse.org
