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Issuer Identity Registry Research Report and Governance Framework for Issuer Identity Registries

Published June 9th, 2025 – Credential Engine and Digital Credentials Consortium

These companion documents present the results of a joint research initiative by Credential Engine and the Digital Credentials Consortium to design and test issuer identity registries—structured, machine-readable trust services that confirm the legitimacy of credential issuers in W3C Verifiable Credential (VC) ecosystems, with a particular focus on Learning and Employment Records (LER). 

The Issuer Identity Registry Research Report documents the full project lifecycle, including governance and technical analysis, prototype development, and practical implementation guidance.

The Governance Framework for Issuer Identity Registries provides an adaptable set of governance considerations to help organizations implement issuer registries that foster transparency, interoperability, and trust for both issuers and verifiers. Together, these resources offer actionable guidance for strengthening trust infrastructure in decentralized digital credential ecosystems.

View our announcement here. 

Download the Issuer Identity Registry Research Report here.
Download the Governance Framework for Issuer Identity Registries here.

 

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Tags: Credential Engine, Credential Transparency, Data, Issuer Identity Registries, Partnerships
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Recognition of prior learning (RPL) is the process of providing formal acknowledgment and credit for knowledge, skills, and abilities people have gained through work experience, military service, self-study, volunteering, and/or previous education. This includes credit for prior learning (CPL), transfer credit between institutions, and validation of non-traditional learning experiences. RPL empowers people to move forward and build on what they already know rather than starting over, accelerating pathways to credentials and careers.

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Fact Sheets

Recognition of Prior Learning: Helping People Move Forward

Recognition of prior learning (RPL) is the process of providing formal acknowledgment and credit for knowledge, skills, and abilities people have gained through work experience, military service, self-study, volunteering, and/or previous education. This includes credit for prior learning (CPL), transfer credit between institutions, and validation of non-traditional learning experiences. RPL empowers people to move forward and build on what they already know rather than starting over, accelerating pathways to credentials and careers.

Other ResourcesReport

Open Data Principles & Framework for the Education-to-Employment Ecosystem

Data benefits all stakeholders in education-to-employment (E2E) ecosystems. Among those data, learners need access to education and employment outcomes data to make informed decisions about their education and career pathways during and after high school. Similarly, institutions, employers, and policymakers rely on this information to improve and align education programs for career success. 

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