Data Readiness
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practical standards guide

Framework · Working Draft · 2022-10-27

FAIR Digital Object Framework

Maintained by FDO community

What it helps you do

FDOF supports persistent and resolvable identifiers, predictable metadata retrieval, and typing for machine-actionable digital objects.

  • Cross-cutting
PlanAcquireHarmonizeExchangeLearn + reuse

01

Where it fits and where it does not

Use these four checks before committing implementation time.

Use it when
Long-horizon infrastructure design for object-level interoperability across repositories and automated agents.
Limits
The available documentation is explicitly incomplete and should not be treated as a final specification.
Best for
Cross-cutting teams working across Plan → Exchange → Learn + reuse.
Maturity
EmergingUse only in a bounded pilot and expect the specification or tooling to change.

02

See it in the workflow

This view shows the input, the change the standard introduces, and the resulting output.

  1. InputWhat starts

    Cross-cutting source data, metadata, and local mappings

  2. FDOFWhat changes

    Use FDOF as a pinned framework across Plan → Exchange → Learn + reuse

  3. OutputWhat becomes possible

    A handoff the next system or team can validate against the same release

Readiness gateThe available documentation is explicitly incomplete and should not be treated as a final specification.

03

A concrete example

A repository assigns each dataset object a persistent ID, machine-resolvable type, and resolvable metadata record with predictable behavior.

Why it matters: Promising substrate for agent discovery and action, but current implementation choices need careful validation and governance.

04

What it fits with

Operationalizes FAIR behaviors at the object layer; may package or reference domain data and metadata expressed with other standards.

05

Implementation starter

Start with one bounded handoff. Pin, test, and review it before scaling.

  1. Define one handoff, its accountable owner, and the decision FDOF must support.

  2. Pin the exact version and companion artifacts: Working Draft · 2022-10-27.

  3. Map one representative input to the required framework artifacts.

  4. Test the result against the canonical source and record every exception.

  5. Preserve the source data, mappings, and review evidence before scaling.

06

Test the main limitation

Risk

The available documentation is explicitly incomplete and should not be treated as a final specification.

Test

Run one representative end-to-end pilot and record exactly where FDOF loses context, needs an extension, or depends on another standard.

Risk

Machine-readable output may still be unfit for analysis or ML.

Test

Test the output for missing context, provenance, terminology alignment, time leakage, and the intended downstream decision. Promising substrate for agent discovery and action, but current implementation choices need careful validation and governance.

07

Official resources

Specifications, diagrams, examples, and guides from the organizations that maintain them.

  • Primary sourceWorking Draft · 2022-10-27

    FDOF working draft

    Official publisher or steward guidance for this framework profile.

    Publisher
    FDO community
    Open official source

Next action

Put this profile in context

Compare its role with adjacent standards or place it inside an end-to-end data pathway before choosing an implementation.