FAIR in ML, AI Readiness, & Reproducibility (FARR) Workshop
The FAIR in ML, AI Readiness, & Reproducibility Research Coordination Network (FARR RCN) welcomes computer scientists, geoscientists, research data practitioners, geosciences data and tool repositories / providers, and computing infrastructure providers and research tool builders to participate in FARR's in-person workshop on April 8-9, 2026 at the AGU Conference Center in Washington DC. Communities outside of geosciences with similar challenges, as well as industry, government, and non-profits with a stake in these topics are also encouraged to attend.
Purpose:
The FARR Workshop 2026 aims to make advances in the areas of AI Readiness, AI Reproducibility, and the intersection of the FAIR Principles and ML through
- Spurring new or deepened collaborations
- Sharing best practices and lessons learned
- Contributing to a roadmap that will serve as a guide for community-led efforts
- Exploring research gaps, priorities and next steps
Should you attend?
- Are you interested in learning about or working towards AI readiness?
- Do you want to share AI models, or use others' models?
- Are you concerned about reproducibility of work that uses AI models?
- Do you have experiences in these areas that you think others would benefit from?
If you are interested in those topics, this workshop will be a good opportunity to connect with others.