This project develops an open and scalable data infrastructure for AI–enabled ecological and biodiversity research. It addresses challenges of fragmented, inconsistent, and inaccessible data by enabling automated, standardized access across a variety of sources while preserving data quality, provenance, and attribution. The infrastructure includes a dynamic inventory and map of existing data sources, assessed for their readiness to support AI applications. It defines shared schemas, aligns taxonomies and ontologies, and provides standard machine-accessible interfaces to enable AI model training and deployment. It is evaluated using a set of exemplar use cases spanning multiple stakeholders. By aligning technical development with the needs of science and decision-making, this infrastructure will serve as a foundation for AI-driven discoveries and action in ecology and related fields.
The FAIR4AI-Bio initiative is funded by the US National Science Foundation's Findable Accessible Interoperable Reusable Open Science (FAIROS) program under Awards 2531924, 2531922, 2531925, 2600200 (Collaborative Research: Disciplinary Improvements: AI-ready Ecology and Biodiversity Data Infrastructure for Open Science). It started in October 2025.
Disclaimer: Any opinions, findings and conclusions or recommendations expressed in the materials here are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
