{
  "notice": "Illustrative mapping from the AI Governance Engineer Body of Knowledge v0.5.0 (not a claim of conformity)",
  "version": "0.5.0",
  "license": "CC BY 4.0",
  "licenseUrl": "https://creativecommons.org/licenses/by/4.0/",
  "schemaVersion": 2,
  "schema": "https://aigovernanceengineer.com/api/v1/schemas/obligation.json",
  "self": "https://aigovernanceengineer.com/api/v1/obligations/aige-obl-usgao-data.json",
  "source": "https://aigovernanceengineer.com/obligations/aige-obl-usgao-data",
  "citation": {
    "title": "AI Governance Engineering: The Thesis & Body of Knowledge",
    "authors": [
      "Jorge García Aibar"
    ],
    "parentDoi": "https://doi.org/10.5281/zenodo.22956197",
    "conceptDoi": "https://doi.org/10.5281/zenodo.22857084"
  },
  "obligation": {
    "id": "AIGE-OBL-USGAO-DATA",
    "url": "https://aigovernanceengineer.com/obligations/aige-obl-usgao-data",
    "json": "https://aigovernanceengineer.com/api/v1/obligations/aige-obl-usgao-data.json",
    "framework": "US federal audit and oversight",
    "frameworkId": "us-gao-ai-accountability",
    "clause": "principle 2 (data), practices 2.1 to 2.8",
    "obligation": "GAO AI Accountability Framework principle 2: data",
    "requirement": "Document the sources and origins of development data and assess their reliability, categorisation, variable selection and any synthetic, imputed or augmented data; assess the dependencies, bias, security and privacy of the data used in operation",
    "artefact": "Dataset datasheet with lineage; data-quality and representativeness evals; data-flow map",
    "layers": [
      2,
      3
    ],
    "dutyHolder": null,
    "scope": "Federal agencies and other entities; auditors and third-party assessors",
    "authority": "U.S. Government Accountability Office; inspectors general",
    "appliesFrom": "2021-06-30",
    "appliesStatus": "voluntary",
    "appliesNote": "Non-binding audit framework; published 2021-06-30",
    "milestones": [],
    "systemClass": [],
    "patterns": [],
    "crosswalkTopics": [
      "data-governance",
      "supply-chain",
      "fairness-non-discrimination",
      "privacy-data-protection"
    ],
    "reviewed": "2026-09-27",
    "chapter": "https://aigovernanceengineer.com/bok/regulatory-map#federal-audit-and-oversight"
  }
}