Over the past year, the Framework Working Group has quietly been doing foundational technical work that will shape how Regen’s ecological and credit metadata is managed, queried, and integrated — both internally and across the broader data ecosystem. I have not been directly working on this, but am keen to surface the work, hear insights and invite the network to be tracking the evolution of our digital infrastructure and data structures. Big shout out to @corlock_RND @paul121 , Jeancarlo Barrios, Sam Bennetts and the rest of the crew (Forum won’t let me tag more than 2 folks). Even though much of this is behind the scenes, it has big implications for interoperability, data quality, and long-term platform sustainability. And is work that many folks just don’t want to dig into as thoughtfully and deeply as it requires.
Here’s more the work done to-date, what’s in progress and upcoming, and why this work matters. Please drop thoughts and questions.
Work done to-date (2024–2025)→
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Migrated the core credit class and project metadata schemas into LinkML, a semantic modeling framework that enables automatic generation of JSON Schema, SHACL constraints, and other tooling
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Ported all existing credit class metadata into the new standard format, while keeping the old on-chain data untouched (so no breaking changes)
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Launched a live SPARQL endpoint / RDF knowledge graph, with CI/CD pipelines that validate, convert, and publish datasets automatically on each update
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Created validation tooling, documentation, and quality checks to ensure consistency and robustness
In Progress & Upcoming Work→
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Porting project-level metadata to the new schema (a more complex lift given the diversity of project data).
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Coordinating with the Regen App backend/frontend teams so that on-chain datasets can eventually be updated to the new standard.
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In the future: building APIs, query tools, more schema coverage (e.g. spatial/temporal modeling, new credit class types), and better controlled-vocabulary support.
Why This Matters→
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It enables Regen data to be more interoperable with external research, climate/ecology registries, and semantic-web tools
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Developers, methodologists, data scientists will have cleaner, more consistent tooling to work with Regen datasets
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The approach is future-proof — as requirements evolve, code generation and semantic schemas make iteration safer and more maintainable
Curious for a full deep dive? @corlock_RND wrote a detailed summary — including timeline, contributors, schema docs, resources, and more:
→ Read the full progress update on GitHub
These datasets will live in the playground directory of the regen-data-standards repo, but are dependent on merging of regen-data-standards#46 and regen-data-standards#43
These schemas live in the schema directory of the regen-data-standards repo