Moore-Sloan Data Science Environments

Moore-Sloan Data Science Environments

PLEASE NOTE:

THIS SITE IS NO LONGER MAINTAINED AND WILL BE ARCHIVED. The work of the MSDSE initiative has largely been moved to the Academic Data Science Alliance and expanded to any academic institutions interested in joining the community. For more information, please visit: https://academicdatascience.org

To learn about the work of the original MSDSE institutes, please visit:


THE BELOW CONTENT AND LINKED PAGES HAVE NOT BEEN UPDATED SINCE 2019.

Links to our final DSE Summits, run by the Academic Data Science Alliance:

2019 DSE Summit

2019 Data Science Leadership Summit

ABOUT THE MSDSEs

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:

Here’s our joint white paper detailing our approaches and some of our lessons learned: Creating Institutional Change in Data Science. For our other white papers and reports, check out our Reports page.

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