Envisioning the Future of Critical Minerals and Materials Cyberinfrastructure
A two-day working meeting to design a shared digital network for critical minerals and materials — convening academia, government, and industry to set a strategic national roadmap.
Save the date.
Building the data backbone for critical minerals discovery
Modern technologies rely on secure supplies of essential minerals. Finding these resources increasingly depends on integrating data from a wide range of sources. Yet geological datasets are inherently multi-scale, multi-disciplinary, and multi-modal, which pushes existing academic and government data storage and distribution infrastructures to their absolute limits.
This workshop will bring together experts to discuss and design a shared digital network for critical minerals and materials. Outcomes of this event will help secure vital supply chains, strengthen national infrastructure, and train a modern science workforce.
The two-day meeting convenes participants from academia, government, and industry to establish a strategic roadmap for critical minerals cyberinfrastructure, addressing multi-modal data integration, data silo harmonization, and interoperability standards for artificial-intelligence-driven economic geology.
Workshop format
Two days of structured, participatory work rather than a conference program:
- Invited keynotes framing the national landscape
- Lightning presentations from participants
- Structured breakout sessions producing roadmap content
What we will work on
AI Advances and Data Needs
Discusses needs of multi-modal dataset processing and specialized computational models to promote AI application in mineral exploration.
Evolution of Data Services
Explores upgrading legacy repositories into AI-driven, dynamic platforms that automate data ingestion and synthesize complex community inputs.
Inter-sector Data Discovery
Tackles isolated data silos by designing cross-sector frameworks to quickly find, access, and merge disparate datasets.
AI-Ready Datasets
Defines criteria for standardizing and structuring raw geoscience data into clean, harmonized inputs that eliminate human cognitive bias.
Standards and Interoperability
Identifies essential data standards, licensing, and governance models required to build a resilient and FAIR-compliant cyberinfrastructure.
Workforce Development
Analyzes workforce gaps and training needs of AI for geoscientists and domain knowledge for data scientists and engineers.
Workshop co-leaders
Dr. Xiaogang Ma
University of Idaho
Dr. Shaunna Morrison
Rutgers University
Dr. Anirudh Prabhu
Carnegie Science
Dr. Tao Wen
Syracuse University
Taking part in the workshop
We expect to support approximately 80 participants from academia, government, and industry. Details on participation will be posted here TBA