01
Where it fits—and where it doesn’t
Use these four checks before committing implementation time.
- Use it when
- Use as the evidence rubric that turns FAIR from an aspiration into a repeatable release and improvement assessment.
- Do not use it as
- Do not treat FAIR DMM as a complete solution on its own. It is not a certification, and locally adapted scoring or weighting means totals from different assessment tools are not automatically comparable.
- Best for
- Teams working with Cross-cutting data across Plan → Acquire → Harmonize → Exchange → Learn + reuse.
- Maturity
- EstablishedEstablished enough for serious use; still pin the exact release and any implementation profile.
02
See it in the workflow
A standard creates value by changing a handoff, not by existing in a catalog.
- InputWhat starts
Cross-cutting data, metadata, and the local decisions around them
- FAIR DMMWhat changes
FAIR DMM applies a shared framework across Plan → Acquire → Harmonize → Exchange → Learn + reuse
- OutputWhat becomes possible
A more consistent, reviewable handoff for the next system or team
03
A concrete example
A release gate evaluates data and metadata separately against the essential, important, and useful indicators, recording evidence, exceptions, and changes between versions.
Why it matters: Tests machine-actionability around identifiers, access, knowledge representation, licensing, provenance, and community standards, but not representativeness, label accuracy, privacy, or predictive fitness.
04
What it fits with
Operationalizes FAIR; DQV can publish resulting measurements, while SHACL, repository checks, and domain validators supply evidence.
- FrameworkFAIR
Both support Cross-cutting work and meet around Plan, Acquire, Harmonize, Exchange, Learn + reuse. Compare their roles before treating them as interchangeable.
Explore relationship - Metadata vocabularyDPV
Both support Cross-cutting work and meet around Plan, Acquire, Harmonize, Exchange, Learn + reuse. Compare their roles before treating them as interchangeable.
Explore relationship - StandardISO/IEC 5259
Both support Cross-cutting work and meet around Plan, Acquire, Harmonize, Exchange, Learn + reuse. Compare their roles before treating them as interchangeable.
Explore relationship - FrameworkData Cards
Both support Cross-cutting work and meet around Plan, Acquire, Harmonize, Exchange, Learn + reuse. Compare their roles before treating them as interchangeable.
Explore relationship
05
Implementation starter
Start with one bounded handoff. Pin, test, and review it before scaling.
Name an accountable owner and the decision FAIR DMM must support.
Pin the exact version and companion artifacts: 1.0 · Endorsed RDA Recommendation · 2020.
Map one representative input to the required framework artifacts.
Test the result against the canonical source and record every exception.
Preserve the source data, mappings, and review evidence before scaling.
06
Limitation to test first—and the tests that catch it
It is not a certification, and locally adapted scoring or weighting means totals from different assessment tools are not automatically comparable.
Run one representative end-to-end pilot and record exactly where FAIR DMM loses context, needs an extension, or depends on another standard.
A structured or machine-readable result can still be unfit for analysis or AI.
Test the output for missing context, provenance, terminology alignment, time leakage, and the intended downstream decision. Tests machine-actionability around identifiers, access, knowledge representation, licensing, provenance, and community standards, but not representativeness, label accuracy, privacy, or predictive fitness.
07
Why we believe this
Checked against the canonical source, with knowledge-base analysis clearly separated from publisher claims.
Evidence notation: E1 + E4. The code is shorthand; the plain-language statement above is the claim.
08
Source shelf
Official diagrams, examples, specifications, and explainers. Nothing external loads until you choose to open it.
RDA FAIR Data Maturity Model Recommendation
The canonical publisher or steward source used to verify this framework profile.
- Publisher
- Research Data Alliance FAIR Data Maturity Model Working Group
- Rights
- Rights remain with the publisher; this knowledge base links to the source rather than copying it.
- Access
- Opens the publisher's source in a new tab; no external media loads on this page.
- Verified
- 2026-07-13