Are you a pioneer in your field? Excited about Environmental Data Science? Ready to be part of something bigger? Then grab your laptop, your expertise, and your passion for making the world a better place and join us for Environmental MosAIc, ESIIL’s first Hackathon. Together, we're not just learning and using AI; we are unlocking a greener and more inclusive tomorrow.
Environmental MosAIc: November 15-17, 2023
Important Dates:
October 26: Pre-hackathon webinar on environmental data science
November 2: Pre-hackathon virtual training on AI
Nov 9: Pre-hackathon virtual training on CI
Why Environmental MosAIc?
- High-stakes outcome: The environmental problems we face are real and immediate. Extreme weather events like hail and flooding cause devastation annually. Biodiversity loss threatens ecosystem services. Climate change exacerbates environmental justice issues. The list goes on… Our mission? Use big data and AI to understand and predict these occurrences and help prepare humanity for them.
- Interdisciplinary and cross-sector collaboration and networking: Environmental MosAIc isn't just another hackathon. It's a cauldron where the sciences meet technology, creating a rich mosaic of innovation. Environmental scientists, data analysts, and AI experts from academia, non-profits, and the public sector come together under one digital roof to collaborate and provide solutions to on-the-ground needs in a respectful and inclusive environment.
- Resources to address environmental challenges: Participate in training on Environmental Data Science, AI, and cyberinfrastructure. With these tools under your belt, unleash your green genius to interrogate petabytes of provided data.
- State-of-the-art cyberinfrastructure: Work on a cloud-based, highly secure platform that allows for the seamless integration of data sets, AI models, and analytical tools.
Why artificial intelligence (AI)?
Environmental Data Science is a convergent discipline that focuses on using big data and emerging technologies to drive discovery, solutions, and science to better understand the environment and the interactions between humans and the natural world. EDS draws upon natural and social sciences like biology, systematics and biodiversity science, ecology, ecosystem science, evolutionary biology, geography, sociology, anthropology, and economics, as well as data sciences like computer science, information science, and mathematics.
Complex, right? AI can efficiently handle this vast and multi-faceted information, uncovering hidden patterns and trends that otherwise may go unnoticed, predict future outcomes, and provide (near-)real-time insights. AI analytics can thus help us make data-informed decisions, proactively address environmental issues, identify opportunities, and optimize strategies to increase the resilience of our communities and the sustainability of our practices.
Who should participate in Environmental MosAIc?
Anyone interested in environmental data science and AI!
New to coding or AI?
Are you an AI expert who wants to learn more about environmental challenges?
Interested in exploring the potential of a huge environmental data cube?
Would you like to meet new collaborators and connect with funding agencies and community partners?
If you answered "yes" to any of these questions, this is the right track for you!
Participants will join a team of environmental scientists, data experts, and coders to explore a global data cube, consider the objectivity of the data, propose a scientific question that can be addressed with all or some of the data sets, frame the question as an AI problem in a manner that promotes fairness and mitigates harmful bias, and present your proposal to a panel of experts. ESIIL will provide mentors, a data cube with global environmental data, cyberinfrastructure, AI and cyberinfrastructure training, and technical support.
All teams will receive feedback from a panel of experts from the National Science Foundation (NSF), North Central Climate Adaptation Science Center (NC CASC), academics, and other community partners. The best proposal will receive a financial award to meet one time in person in Boulder, CO (via ESIIL’s working groups) as well as cyberinfrastructure, and technical and scientific support to complete their project.
Applications
We are currently processing applications and successful applicants will be informed by October 6.
Track II
Are you interested in flood prediction? Would you like to form your own team? Do you or others in your team have experience in AI? If you answered “yes” to all these questions stay tuned for more information about Environmental MosAIc - Track II coming soon!
If you have any additional questions, needs, or concerns, please contact Virginia Iglesias at Virginia.Iglesias@colorado.edu.
This Hackathon is funded by the National Science Foundation (via award # DBI-2153040), and subject to the NSF’s terms and conditions.