One of the organizations working with Los Alamos National Laboratory on the Data Sprint is the nonprofit Rocky Mountain Youth Corps which provides workforce development training and educational programs to young people in New Mexico. Photo Courtesy LANL
A new Los Alamos National Laboratory program is pairing local nonprofit and social good organizations with LANL data scientists to solve data-related problems to benefit Northern New Mexico.
Work on the first Northern New Mexico Community Data Sprint started in February with a call for interested community organizations who had a collection of data and a question or problem they would like to answer or solve. There is no charge for organizations to participate in the project.
Eleven community organizations applied to take part, and the two chosen partners were the nonprofit Rocky Mountain Youth Corps, and a joint project from Northern New Mexico College and Santa Fe Community College.
“Competition for community partner participants was strong, and we received many applications from truly outstanding community organizations,” says Lissa Moore from the Laboratory’s information sciences group, who is organizing the sprint. “The winning partners were selected by our organizing committee based on technical feasibility of the proposed data-related project, availability of the dataset, and the impact that participation in the sprint would have both on the organization itself and the Northern New Mexico community.”
Rocky Mountain Youth Corps (RMYC) provides workforce development training and educational programs to young people in New Mexico. Corpsmembers work on land conservation and historic preservation projects, and also teach environmental education programs. The organization is seeking to understand its performance in gender diversity, effective mentorship and general impact.
“RMYC applied to Data Sprint so we could develop the tools we need to evaluate the key performance indicators that focus us on our mission,” says Herbert Foster, development director at RMYC. “After looking at our data, I realized we needed help to aggregate it and evaluate it using verifiable statistical methods so I could feel confident in sharing the data with staff, funders, and the community. The Data Sprint will give us the direction we need to make the best decisions about our data and how we can best utilize the tools we already have.”
The colleges’ project focuses on student retention rates, risk factors and signs of academic and professional success).
“We saw this opportunity from LANL to answer complex questions knowing that LANL’s scientists have the willingness and talent to understand and implement a project that will give us some of the very needed solutions to improve student retention,” says Ivan Lopez, provost and vice president for academic affairs at Northern New Mexico College.
“Nationally, only 25-30% of community college students graduate on time (3 years for an associate degree). But if we wait to the end to see how many students graduated it’s too late,” says Yash Morimoto, associate vice president for planning and institutional effectiveness at SFCC. “We want to know of an earlier and better way to detect any systemic challenges students are facing so that we can better assist them in crossing the finish line.”
Sponsored by LANL’s Information Science & Technology Institute (ISTI) and Community Partnerships Office, Laboratory computer scientists with experience in applied machine learning, data science and agile code development will spend a week over the summer working with the partners analyzing their data and helping to draw conclusions from it. (Normally the team would meet in person, but COVID restrictions will see them collaborating virtually this year.)
The Laboratory researcher’s time is paid for by ISTI and the program is coordinated under the Laboratory’s Community Technical Assistance initiative, which makes the unique expertise and capabilities of the Laboratory available at no cost to tribal entities, governmental entities, and nonprofits located in the seven counties of Northern New Mexico.
“We are looking forward to a fun and productive Community Data Sprint week, working with our partner organizations and learning about the needs of the Northern New Mexico community, and finding ways for LANL data scientists to use their skills and knowledge to give back to their community,” says Moore.