Collaborative Call for FAIR Scientific Process Schemas
Join the collaborative effort to create standardized, machine-actionable descriptions of scientific processes. Register by January 31, 2026.
A collaborative effort is underway to create a community-driven collection of scientific process schemas inspired by schema.org, focusing on experimental and simulation workflows across various scientific domains.
The goal is to develop standardized, machine-actionable descriptions of scientific processes to support FAIR metadata, reproducible benchmarks, and ML models that understand experimental conditions.
- Contributors are invited to provide collections of full-text articles (~50+) describing specific experimental or simulation processes.
- Expert feedback on automatically mined schemas or running schema-miner is also welcome.
- Co-authorship opportunities are available based on the level of involvement.
To participate, register your interest by January 31, 2026.
Tags: FAIR scientific processes, schema.org, ORKG templates, machine learning, scientific data, experimental workflows