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practical standards guide

Ontology / data model · W3C Recommendation · 2013-04-30

W3C PROV-O

Maintained by W3C

What it helps you do

PROV-O supports an OWL 2 ontology for interoperable provenance using entities, activities, agents, and qualified relationships.

  • Cross-cutting
PlanAcquireHarmonizeExchangeLearn + reuse

01

Where it fits and where it does not

Use these four checks before committing implementation time.

Use it when
Cross-system lineage, transformation history, audit evidence, and knowledge-graph provenance.
Limits
The model is intentionally generic; useful provenance requires a scoped profile, identifier policy, and capture instrumentation.
Best for
Cross-cutting teams working across Acquire → Harmonize → Exchange → Learn + reuse.
Maturity
EstablishedSuitable for production assessment. Pin the exact release and any implementation profile.

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. PROV-OWhat changes

    Use PROV-O as a pinned ontology / data model across Acquire → Harmonize → Exchange → Learn + reuse

  3. OutputWhat becomes possible

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

Readiness gateThe model is intentionally generic; useful provenance requires a scoped profile, identifier policy, and capture instrumentation.

03

A concrete example

A derived assay table records the source files, transformation activity, software agent, parameters, and responsible organization.

Why it matters: Supports dataset and feature lineage, reproducibility, and audit, but does not define ML-specific quality or responsible-use metadata by itself.

04

What it fits with

Can enrich DCAT, Croissant, RO-Crate, and domain graphs; lighter profiles often select a practical subset of PROV terms.

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 PROV-O must support.

  2. Pin the exact version and companion artifacts: W3C Recommendation · 2013-04-30.

  3. Map one representative input to the required ontology / data model 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 model is intentionally generic; useful provenance requires a scoped profile, identifier policy, and capture instrumentation.

Test

Run one representative end-to-end pilot and record exactly where PROV-O 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. Supports dataset and feature lineage, reproducibility, and audit, but does not define ML-specific quality or responsible-use metadata by itself.

07

Official resources

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

  • Primary sourceW3C Recommendation · 2013-04-30

    W3C PROV-O Recommendation

    Official publisher or steward guidance for this ontology / data model profile.

    Publisher
    W3C
    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.