Full Proposal: Environmental Data Science Innovation and Impact Lab (ESIIL): Accelerating Discovery by Fostering an Open and Diverse Earth Data Revolution

University Of Colorado At Boulder, Boulder CO

Investigators

Abstract

The Environmental Data Science Innovation & Impact Lab (ESIIL) is a next-generation NSF synthesis center led by the University of Colorado Boulder in collaboration with NSF’s CyVerse at the University of Arizona and the University of Oslo. ESIIL enables a global community of environmental data scientists to leverage the wealth of environmental data and emerging analytics to develop science-based solutions to solve pressing challenges in biology and other environmental sciences. ESIIL holds that environmental data science needs all perspectives, and science needs to serve all. ESIIL’s research community generates discoveries and novel approaches through: 1) cutting-edge data-driven science, 2) innovative tools and cyberinfrastructure, 3) data science education and training, and 4) building broad collaborations and interdisciplinary teams. These activities advance the frontier of environmental data science, a rapidly evolving discipline bridging the computational, biological, environmental, and social sciences. ESIIL’s Open Analysis and Synthesis Infrastructure for Science (OASIS) cyberinfrastructure lowers barriers to scientific collaboration through a tailored user experience, seamless connection to critical data sources, and premier cloud computing. ESIIL’s education program facilitates broad access to environmental data science skills and helps develop the next-generation data-capable workforce. Partnerships with a variety of institutions help to increase data skills and knowledge sharing among researchers and citizen scientists. The ESIIL Network, a community of over 2,000 researchers and students, is a 21st-century team committed to generating data-inspired discoveries that enhance societal and ecosystem resilience. ESIIL’s vision is that cultivating an open community of practice is needed to produce innovative breakthroughs in environmental data science. Innovation Summits explore Grand Challenges such as continental-scale ecology, artificial intelligence for the Earth, big data, and adapting to our changing world. Incubator Working Groups, postdocs, and large-team collaborations generate new discoveries, and cross-sector partnerships catalyze use-inspired research through Innovation Summits and Earth Hackathons. ESIIL collaborations include industry, government, and non-profit partners, facilitating the co-production of science that has environmental policy, management, and technological applications. The National Ecological Observatory Network (NEON), Long Term Ecological Research (LTER) network, and the Critical Zone Collaborative Network (CZ Net) are strategic data partners. ESIIL facilitates best practices in team science and conducts basic research on the correlates of scientific productivity and creativity within diverse scientific teams. ESIIL accelerates scientific inquiry by supporting community-developed and high-value software, and data cubes bridge, for example, ground, airborne, and satellite data from diverse observatories and platforms. These tools, curated datasets, and reproducible and reusable workflows are deployed on ESIIL’s open cyberinfrastructure. The ESIIL Stars internship program supports students and faculty members from institutions that promote STEM education, providing data skills training, research experience, and career mentorship. The ESIIL Leaders program supports emerging scientists by fostering leadership skills in environmental data science and team science. ESIIL will develop an advanced textbook that introduces novel analytics for environmental data. By hosting open education resources on an existing learning portal, with a following of over 200,000 users per month, ESIIL education scales to a global audience. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.