Compliance dossier — training data (AI Act, Article 10)

Automatically generated skeleton from the dataset analysis. The "to be completed by the expert" blocks require human review (provenance, compliance judgment, mitigation measures).

1. Identity & purpose

• System / model: _____
• Dossier version: _____
• Date: _____
• Dataset: src
• Intended purpose: _____

_To be completed by the expert — intended purpose and what the data is meant to represent_

2. Provenance & legal basis

Origin of each source, licences/contracts, and — for personal data — initial purpose and GDPR legal basis.

_To be completed by the expert — provenance per source (separate flow §16), licences, GDPR legal basis_

3. Composition _(filled automatically)_

• Volume: 303 rows, 14 columns.
• Variables:

• Declared sensitive attributes: age, sex.

_To be completed by the expert — geographic / contextual / behavioural scope_

4. Preparation _(automatic observations)_

• Missing values: ca (4) → handling strategy to be documented.

_To be completed by the expert — transformation log: collection, cleaning, labelling, enrichment, aggregation_

5. Quality _(filled automatically)_

• Completeness: 4 missing value(s) (ca).
• Accuracy / outliers: chol (1).

_To be completed by the expert — representativeness and relevance to the purpose_

6. Bias

Automatic analysis

sex — disparity of the « target » rate: ratio 2.41 ⚠️

Judgment & measures

_To be completed by the expert — impact on health/safety/fundamental rights and detection/prevention/mitigation measures_

7. Gaps & limitations

Detected points to examine as potential gaps:

• [low] missing — ca
• [low] missing — thal
• [low] outliers — chol
• [high] bias — sex

_To be completed by the expert — identified and addressed gaps; out-of-scope uses_

8. Governance & traceability

• Analysis tool version: 0.2.0

_To be completed by the expert — responsibilities, audit log, versioning, maintenance/updates_