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May 9, 20260 citationsOpen Access

AUGMANITAI Provenance Standards — AI-SBOM + C2PA + W3C-VC + SHACL-Shapes + System-Prompts

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AEAndreas Ehstand

Key Points

  • The research aims to establish robust standards for the provenance and validation of AI and software components.
  • Developed a restricted bundle of 17 files encompassing various provenance and validation standards.
  • Implemented infrastructure for AI Software Bill of Materials (AI-SBOM) and related validation frameworks.
  • Designed templates for cryptographic proof and configurations for verifiable credentials.
  • Achieved standardized formats for software provenance and authenticity with AI-SBOM and C2PA.
  • Validated the effectiveness of SHACL shapes in RDF constraint validation.
  • Demonstrated reproducibility of LLM behavior through structured system-prompts.

Abstract

Restricted bundle of 17 files covering wissenschaftliche Provenance- und Validierungs-Infrastruktur: AI-SBOM (Software-/AI-Bill-of-Materials in CycloneDX + SPDX + Generator-Skript), C2PA (Coalition for Content Provenance and Authenticity Manifest-Generator + Template + Training-Mining-Assertion 'do-not-train signal'), W3C Verifiable Credentials (AUGMANITAI-Authorship VC + Issuer-Konfiguration + Cryptographic-Proof-Template), SHACL Shapes (Term-Shapes + Relation-Shapes für RDF-Constraint-Validierung), System-Prompts (kompakter + Long-Form + JSON-strukturierter Inject für reproduzierbare LLM-Behavior-Eval). Strict-Wissenschaft, Standards-konforme Provenance-Infrastruktur.

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Cite This Study

Andreas Ehstand (2026) studied this question.

synapsesocial.com/papers/69fed090b9154b0b828779bdhttps://doi.org/10.5281/zenodo.20060930
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