This week-long event will pair local nonprofit and social good organizations with a small team of LANL data scientists to solve data-related problems to benefit Northern New Mexico.
This week-long event will pair local nonprofit and social good organizations with a small team of Los Alamos data scientists to solve data-related problems to benefit Northern New Mexico.
The data sprint event is sponsored by The Laboratory’s Information Science & Technology Institute and Community Partnerships Office, and will occur in summer 2026.
We are seeking community partner organizations to participate in the Data Sprint. Interested organizations should have their own data, a related question or problem they would like to answer or solve, and at least one representative willing to participate in some planning activities as well as participating during the week of the data sprint. There is no charge for the organization to participate in the project.
Information sessions (via Microsoft Teams):
Thursday, January 22, 2:00-3:00 p.m. MST
Meeting ID: 298 772 285 103 45
Passcode: uK3Wk65E
Join the meeting
Monday, February 2, 1:00-2:00 p.m. MST
Meeting ID: 245 578 648 798 74
Passcode: sV3bY7Hd
Join the meeting
Application deadline: Friday, February 20, 2026
Data Sprint: July 13-17, 2026
To be eligible to be a community partner, an organization should be a nonprofit, tribal, and/or non-Federal government entity located in one or more of the following Northern NM counties: Los Alamos, Mora, Rio Arriba, San Miguel, Sandoval, Santa Fe, or Taos. Organizations that applied in previous years are encouraged to re-apply.
If you are interested, we encourage you to attend one of the information sessions listed above. If neither time works for you and you would like to gain more information, please reach out to us at datasprint@lanl.gov.
To apply, fill out this application form.
Here we describe the two successful projects from the 2021 Community Data Sprint. Note that these are just two examples, although they were extremely successful. We encourage applications to be creative in thinking about what problems they might solve with their own unique datasets.
Los Alamos National Laboratory partnered with NNMC and SFCC to investigate student retention rates and risk factors. The colleges provided an extensive dataset on student performance and demographics, and asked whether certain types of students were at higher risk for not completing their degrees. A related question was whether there were any positive patterns in the data that indicated what additional resources the colleges might use to encourage student success.
Los Alamos National Laboratory partnered with RMYC to investigate the organization’s overall impact in a quantitative way and to evaluate the effectiveness of recent diversity initiatives. RMYC provided a dataset including member demographics, programs completed, and pre-/post-program surveys. Laboratory data scientists provided quantitative metrics regarding program outcomes, as well as success rates of students belonging to under-represented groups.