Cupel: A Framework for Professional Competence Provenance

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Main Author: Merwe-Chartier, Eugene Andrie
Format: Recurso digital
Published: Zenodo 2026
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author Merwe-Chartier, Eugene Andrie
author_facet Merwe-Chartier, Eugene Andrie
contents Traditional professional credentials have broken down as proxies for competence. This paper identifies a structural trust deficit in professional labour markets and proposes Cupel, an open framework specification for professional competence provenance. Cupel defines a taxonomy of trust signal types, a schema for representing and linking those signals, and an interoperability architecture that sits above existing standards including W3C Verifiable Credentials, C2PA, the Credential Transparency Description Language (CTDL), and Open Badges 3.0. The framework is released under AGPL-3.0, with trademark protection ensuring conformance integrity.
format Recurso digital
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publishDate 2026
publisher Zenodo
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spellingShingle Cupel: A Framework for Professional Competence Provenance
Merwe-Chartier, Eugene Andrie
professional competence
credentials
verifiable credentials
trust signals
provenance
open standards
W3C
C2PA
Open Badges
CTDL
interoperability
AI
Traditional professional credentials have broken down as proxies for competence. This paper identifies a structural trust deficit in professional labour markets and proposes Cupel, an open framework specification for professional competence provenance. Cupel defines a taxonomy of trust signal types, a schema for representing and linking those signals, and an interoperability architecture that sits above existing standards including W3C Verifiable Credentials, C2PA, the Credential Transparency Description Language (CTDL), and Open Badges 3.0. The framework is released under AGPL-3.0, with trademark protection ensuring conformance integrity.
title Cupel: A Framework for Professional Competence Provenance
topic professional competence
credentials
verifiable credentials
trust signals
provenance
open standards
W3C
C2PA
Open Badges
CTDL
interoperability
AI
url https://doi.org/10.5281/zenodo.18976395