Pala Native American Youth Receive DataJam Award with Guidance from SDSC

Published May 26, 2022

By Kimberly Mann Bruch, SDSC External Relations

Staff from the San Diego Supercomputer Center (SDSC) at UC San Diego recently worked with middle and high school students from the Pala Native American Youth Council to conduct an informal data science study on the pH levels of the San Luis Rey River that flows through Pala tribal land. The students then compared their local information with a larger data set from the California Natural Resources Agency.

“The students only collected a few samples of river water on the reservation, but we were pleased that they found that the pH levels were healthy in the area that they sampled,” said Pala Tribal Chairman Robert Smith. “Our goal with the project was to have the students work with SDSC’s Kim Bruch and increase their general knowledge of science/technology—we were extremely proud of their efforts to learn about sample collection strategies and how to conduct simple data science studies.”

This work was completed in conjunction with the DataJam, which is an annual competition among high school teams that ask a question about their community and use publicly available datasets and data analytics, under the guidance of college students who serve as DataJam mentors, to answer their questions.

“Teams work through each academic year with the DataJam finale held in the Spring and this year we expanded our reach to informal settings such as the youth council at Pala—we were pleased to present the ‘Best New Team’ Award to these outstanding young women,” said Judy Cameron, Pittsburgh DataWorks director and University of Pittsburgh professor. “This was the first year that we have worked with informal afterschool groups and of the 21 total teams, the Pala group stood out in several respects. First, we have only had a few teams collect their own data for the DataJam. Most teams use publicly available datasets to answer their research questions. The Pala team both collected their own data and used a publicly available dataset. Second, the San Luis Rey River is of particular importance to the Pala reservation and it was very impressive to see the team look into a resource that is particularly meaningful to their community. Third, the girls on this team were younger than most students competing in the DataJam, and we were very excited to see their commitment and perseverance in pursuing their research question.

The Pala Native American Youth Council students presented their DataJam poster in both English and Cupeño. Credit: Kimberly Mann Bruch

One of the most powerful aspects of the Pala team’s DataJam presentation was that it was delivered in English as well as Cupeño, the language of the Indigenous people from the region. The team was mentored by Diana Duro, a Pala elder who is fluent in Cupeño.

Another critical aspect of the project was to ensure that any data collected on or about the tribal land was treated with the utmost respect and that ownership was retained by the Pala youth conducting the research, operating within the framework of the CARE Principles for Indigenous Data Governance. The tenets of CARE include Collective Benefit, Authority to Control, Responsibility, and Ethics.

Next the Pala students will work with Bruch this summer to expand their study. The young women want to collect samples from additional areas on the reservation and also look at more factors such as mineral content.

“With the advent of affordable water sensors and easy to access tools for analysis, citizen science is more approachable than ever. These tools come at a time when our youth are curious and anxious about the state of natural resources and the effects of climate change,” said Christine Kirkpatrick, director of the SDSC Research Data Services. “Through the DataJam model, Kim’s leadership, and partnership with the Pala Native American Youth Council, an opportunity arose to showcase the intense brainpower and hard work of the Pala youth to acquire data science skills and to apply them to the study of their local environment. We look forward to our next project together where we hope to include traditional knowledge and methods alongside the DataJam model for further study.”