Moore-Sloan Data Science Environments

Moore-Sloan Data Science Environments

Although data-driven research is already accelerating scientific discovery, substantial systemic challenges in academia need to be overcome to maximize its impact and create supportive environments for researchers using and developing data-intensive practices.

We seek to enhance data-driven discovery by supporting cross-disciplinary academic data scientists at research institutions. Our work is organized around six challenges, which are themes used to effectively focus our efforts to advance the future of academic data science. Learn more:

We have created three Data Science Environments to work toward our goal:

Please read one of our white papers on Creating Institutional Change in Data Science.

Other institutions are working toward similar goals. Read more about other data science initiatives.