Preserve source-native data
Original labels and values remain intact. Normalized values are treated as a separate analytical layer rather than replacements for source data.
Research · Data · Open Science
Building better infrastructure for cannabis research data.
WeedDAO is a research and data cooperative in formation exploring how public cannabis laboratory data can be made more consistent, interoperable, and useful for careful research.
No token. No lab rankings. No medical claims.
Current research
Research readiness across public cannabis lab data
Our first pilot asks a practical question: how difficult is it to combine public cannabis laboratory records across different reporting systems without losing the meaning of the original data?
Audit normalization
Analyte mappings and unit-like tokens are reviewed for collisions, ambiguity, and assumptions before any external research claims are made.
Invite independent review
We are seeking methodological feedback from analytical chemistry and measurement-science experts before publication or expansion.
What we're working on
Infrastructure before hype.
01
Cannabis laboratory data standards and interoperability
02
Analyte and unit normalization
03
Measurement metadata such as LOD, LOQ, methods, and uncertainty
04
Public-data research and reproducible methodology
05
Future collaboration with growers, laboratories, researchers, and other lawful industry participants
Principles
Useful research requires restraint.
WeedDAO is designed around transparent assumptions, clear limits, and preserving the distinction between what a dataset shows and what it cannot establish.
What we do
Study data interoperability, document normalization assumptions, preserve source-native records, and seek expert methodological review.
What we don't claim
No laboratory rankings, no blanket claims about lab accuracy, no consumer-health conclusions, and no endorsement by cited data providers or agencies.
Get in touch
Interested in the methodology?
We welcome concise scientific or technical feedback, especially from analytical chemistry, laboratory QA, statistics, data standards, and measurement-science professionals.