{
 "@context": "https://schema.org",
 "@type": "DefinedTerm",
 "@id": "https://wulfkaal.github.io/entities/data-provenance",
 "identifier": "kaal:entity:data-provenance",
 "name": "Data provenance",
 "termCode": "data-provenance",
 "inDefinedTermSet": {
  "@id": "https://wulfkaal.github.io/entities/index.json"
 },
 "author": {
  "@type": "Person",
  "name": "Wulf A. Kaal",
  "identifier": "https://orcid.org/0000-0003-0757-275X"
 },
 "dateModified": "2026-07-29",
 "canonicalForm": "https://wulfkaal.github.io/entities/data-provenance.md",
 "sha256": "5ca64f5c9286be185a7133e39a5646ae66ce7c547c740da408076299f3cab032",
 "additionalProperty": [
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   "@type": "PropertyValue",
   "name": "status",
   "value": "derived"
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   "value": 2
  },
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   "value": 2
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   "@type": "PropertyValue",
   "name": "year_span",
   "value": [
    "2024",
    "2025"
   ]
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  }
 ],
 "subjectOf": [
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/4941807-018",
   "identifier": "kaal:claim:4941807-018",
   "text": "An immutable blockchain log of transactions and modifications inside AI systems lets stakeholders trace the lineage of an AI decision back to its original data inputs, which makes errors easier to identify and correct.",
   "abstract": "This feature allows stakeholders to track the lineage of AI decisions back to their original data inputs, enabling easier identification and correction of errors.",
   "citation": "Wulf A. Kaal, AI Governance Via Web3 Reputation System (2024). SSRN: https://ssrn.com/abstract=4941807",
   "datePublished": "2024",
   "claim_type": "mechanism",
   "confidence": "argued",
   "is_failure_mode": false,
   "scope_conditions": [
    "where AI data inputs and modifications are recorded on an immutable ledger"
   ],
   "source_pdf_sha256": "ab66c1e99a88da1fa36b0c6b536df5184231fe6aa427f3dd53287a4e0ac79853",
   "status": "current"
  },
  {
   "@type": "Claim",
   "@id": "https://wulfkaal.github.io/claims/5245185-003",
   "identifier": "kaal:claim:5245185-003",
   "text": "Because blockchain records a verifiable and immutable history of data provenance and alterations, it mitigates data poisoning risk and supports the claim that AI models were trained on genuine datasets.",
   "abstract": "Blockchain establishes a verifiable record of data provenance and alterations, essential for sustaining trust and mitigating risks such as data poisoning, thereby ensuring AI models are trained on genuine datasets.",
   "citation": "Wulf A. Kaal, How can we Best Monitor AI Agents (2025). SSRN: https://ssrn.com/abstract=5245185",
   "datePublished": "2025",
   "claim_type": "mechanism",
   "confidence": "evidenced",
   "is_failure_mode": false,
   "scope_conditions": [
    "training data recorded on chain",
    "systems relying on large language models"
   ],
   "source_pdf_sha256": "4d7adba83ec722480e97bde6528cbe9ce98c709e45cb18794f157a64b8fe7da2",
   "status": "current"
  }
 ],
 "description": "2 claims in the published works of Wulf A. Kaal carry the concept tag 'data-provenance'. Derived node: a roster, not an adjudicated definition."
}