A “Revolution” in Environmental Data Science
New national center at 鶹ѰBoulder will tackle pressing socio-environmental challenges with big data analytics, more
Funding of $20 million for 5 years will support collaborative research and education involving huge science datasets, innovative cyber infrastructure, machine-learning approaches to analysis, and engagement with decision makers and other stakeholders.
ESIIL, pronounced like the word “easel,” promises to empower a diverse community of researchers to turn environmental data into actionable knowledge, said ESIIL director Jennifer Balch, an associate professor of Geography and a fellow of CIRES. The metaphor of an easel is intentional, Balch said: “We want to be the structure to support vivid new science.”
NSF and other agencies and organizations have established environmental networks and observatories that are generating vast amounts of open access environmental data—more data than can be analyzed to their full potential today, said Balch. So, she and colleagues from across 鶹ѰBoulder, the University of Arizona, and the University of Oslo proposed building “a community of thousands” of researchers and students who know how to ask and answer important environmental questions with data.
University of Arizona research assistant professor Tyson Swetnam, part of the new center’s leadership team, is an informatician at , an NSF-funded cyberinfrastructure center. Swetnam said he can imagine ESIIL supporting a project, for example, by a student researcher located in rural Arizona who lacks access to large computing resources. With just a cell phone and intermittent broadband internet connection, she should be able to freely explore and analyze diverse datasets on the cloud, looking for evidence of, say, genetic resilience in spruce trees growing on the peaks of Arizona’s sky islands, where many species are threatened by warming, drought, pests and disease.
“We want to support open data, open source software, open code…and open science,” Swetnam said.
鶹ѰBoulder Computer Science professor Claire Monteleoni is another critical ESIIL leadership member, an expert in using machine learning in climate science who helped create the field of a decade ago. Monteleoni said she’s especially inspired by ESIIL’s focus on team science. The lab will be studying itself, essentially, to help identify factors that help diverse teams work well together, as well as the impact of teamwork training. “I’ve spent the first chunk of my career trying to get people working on climate change to talk with people working on AI and machine learning,” Monteleoni said. “So it will be great to have lessons coming from team science as we connect these communities.”
Finally, ESIIL will involve students and communities. ESIIL’s Stars internship program, for example, will support students and faculty members from Oglala Lakota College, United Tribes Technical College, and Metropolitan State University of Denver, to start. And ESIIL’s Leaders program will support emerging scientists from underrepresented communities.
Linking Tribes and Tribal colleges, other academic institutions, government agencies and private organizations, is a key characteristic of the new center, said James Rattling Leaf Sr., ESIIL’s Tribal liaison. “Effective partnerships and communication among these groups are needed to address major challenges facing our world and ESIIL is well positioned to address those challenges.”
Principal investigator: Jennifer Balch
Funding: National Science Foundation (NSF)
Collaboration/support: at the University of Arizona; Cooperative Institute for Research in Environmental Sciences (CIRES) , Department of Computer Science, , USGS ter, all at 鶹ѰBoulder; of Denver; ; e; and , Norway.