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§ I · Domain DAT · Control 6 of 13
Control
DAT-06
Edition
v.1.3
Status
Public review

DAT · Data Protection & Privacy

DAT-06Training and RAG data provenance

Sources of training, fine-tuning, and RAG data are documented. Opt-out and consent requirements are honored.

The provenance of data used for training, fine-tuning, and retrieval-augmented generation is documented: where the data came from, under what terms, and what consent or opt-out obligations apply. Opt-out and consent requirements are honored at the data-ingestion layer, not as an afterthought. This control is increasingly critical as regulatory scrutiny of training-data provenance intensifies.

Table DAT-06.1 · Maturity criteria · v.1.3

L1 to L5 · the lowest level in scope caps the agent
L1Ad hoc

Controls exist informally; documentation is incomplete; no consistent review.

L2Documented

Controls are written down; ownership is assigned; review cadence is defined.

L3Operated

Controls are followed in practice; evidence is collected; deviations are tracked.

Data sources are documented with provenance records; opt-out and consent mechanisms are operational; compliance is verified at a documented cadence; data sources lacking provenance are identified and remediated.

L4Measured

Control effectiveness is measured against documented thresholds; trends are reported.

L5Continuously Improved

Controls evolve based on incident learning; maturity gains are evidenced over time.

The v1.3 edition publishes a control-specific criterion at L3 (Operated). The other levels apply the general ladder to this control; see the maturity ladder.

Evidence an assessor asks for

  1. E.1

    Data sources are documented with provenance records.

  2. E.2

    Opt-out and consent mechanisms are operational.

  3. E.3

    Compliance is verified at a documented cadence.

  4. E.4

    Data sources lacking provenance are identified and remediated.

Table DAT-06.2 · Framework mappings

6 of 7 frameworks carry a control-level reference
NIST AI RMFMEASURE 2.10NIST AI Risk Management Framework 1.0
ISO/IEC 42001A.7.5ISO/IEC 42001:2023 · Artificial intelligence management system
OWASP LLM Top 10LLM06OWASP Top 10 for Large Language Model Applications
SOC 2 (TSC)P3.1, P4.2AICPA Trust Services Criteria for SOC 2 Type II
EU AI ActArt. 10(1), Art. 10(2)EU AI Act · Regulation (EU) 2024/1689
MITRE ATLAS·MITRE ATLAS · Adversarial Threat Landscape for AI Systems
SingaporePDPA s.13, MAIGF Data, AI Verify Data GovernanceSingapore Model AI Governance Framework / AI Verify / PDPA

Mappings are directional: meeting this control evidences but does not by itself satisfy the external requirement. A middle dot means no control-level reference is published at this edition; see the crosswalk.

Related controls and terms

Cite this control

Human Intelligence. HI-AAF v1.3, DAT-06 Training and RAG data provenance. Public review edition, July 2026. https://humanintel.net/standard/dat/dat-06

Edition v.1.3 · July 2026 · Public review · Markdown · PDF

https://humanintel.net/standard/dat/dat-06

Notice

HI-AAF v1.3 is an independent framework published by Human Intelligence. It is not affiliated with NIST, ISO, AICPA, or any government or accreditation body. The framework is offered openly for review during the current draft cycle.