We are working to catalyze a new era of research that enables interdisciplinary approaches to data-intensive discovery.

Changes in academia are required to more fully support data scientists who enable new data-driven discoveries. We aim to create new types of institutional environments in which these discoveries can take place.

The Data Science Cooperative

One approach we are now supporting, together with the Academic Data Science Alliance, is the creation of a Data Science Cooperative for early-mid career researchers who use data intensive tools and methodologies. Born out of the MSDSE Alumni, this group is mobilizing their collective knowledge and culture to provide a grassroots Data Science Environment.

The mission of the Data Science Cooperative is to equip a trusted and growing community of academically-minded data scientists to share expertise in ways that benefit the individual members and the cooperative. Their peer-powered culture, software-enabled communications systems, convening capacity, and common voice will help members find collaborators, audiences, answers, and financial support. And their cooperative projects will gather and cultivate collective knowledge assets for the shared benefit of membership and audiences. They will pursue their mission in a way that aligns with academic values like transparency, inclusion, and knowledge sharing.

The 2019 Call for Nominations for the Co-Op Leadership Committee is currently underway. See the FAQ’s for more information.

Moore-Sloan Data Science Environments

Other Data Science Centers

Many other institutions have an interest in promoting and facilitating data-driven discovery in academia. Below is a partial list (compiled a few years ago) of those that align closely with the objectives of the Data Science Environment Partnership.

Note: Although certificate and undergraduate or master’s degree programs in data science are a critical component of academic data science, we focus here on programs that emphasize the use of data-driven approaches to active research. For international data science educational programs, see this curated list: github.com/ryanswanstrom/awesome-datascience-colleges.

Institution Center or Program
Caltech Center for Data Driven Discovery
Columbia University Data Science Institute
Johns Hopkins University Institute for Data Intensive Engineering and Science
Michigan State University Computational Mathematics, Science and Engineering
Princeton University Center for Statistics and Machine Learning
Rensselaer Polytechnic Institute Data Science Research Center
Stanford University Stanford Data Science Initiative
University of Chicago Computation Institute
University of Massachusetts Amherst Center for Data Science
University of Michigan MIDAS: Michigan Institute for Data Science
University of Rochester Goergen Institute for Data Science
University of Virginia Data Science Institute
University of Washington at Tacoma Center for Data Science
Harvard University Data Science Initiative
Vanderbilt University Data Science Institute