Product-level data is scattered, unstandardised, and context-bound.

Research into food systems, product quality, health outcomes, and trade patterns depends on product-level information. That information is scattered across regulatory databases, certification records, and producer claims — unstandardised and tied to specific jurisdictional contexts.

Relevant fieldsAll fieldsReader views

What the disclosure layer carries.

Existing records serve bounded institutional purposes. Research comparability requires a different structure. Comparing product-level information across origins, practices, and contexts often requires reconstructing the information base from scratch.

What becomes structured.

A structured, jurisdiction-neutral format for producer-declared product information — so declarations, sources, and gaps can be compared across products, origins, and contexts over time.

Product information today

Structured disclosure

OriginDeclared
PracticesDeclared
ProcessingDeclared
ClaimsDeclared
SourcesDeclared
Testing cadenceDeclared
Declared gapsMarked · not inferred
UpdatesUpdateable
Reader viewsComparable

What becomes possible.

Product-level information that is easier to compare across producers, origins, practices, and contexts — without needing to rebuild the information structure for each research question.

Three things you do with it · researchers

Compare without reformatting

Practices and claims across producers sit on the same schema. You compare without first rebuilding the data structure for each research question.

Hold a stable spine

Schema-stable, jurisdiction-neutral fields let longitudinal work hold its shape — across years, regions, and policy regimes.

Cite a versioned snapshot

Each disclosure has a version date and change history. Cite the version you read; later updates are traceable, not erased.

Research collaboration Read the research basis