Creating an effective, efficient, and fair marketplace for credentials, qualifications, and skills requires collaboration among various stakeholders, including employers, educational providers, quality assurance organizations, assessment bodies, funders, and guidance platforms.

Since 2016, Credential Engine has led the development and evolution of the open-source Credential Transparency Description Language (CTDL). This language encompasses over 1000 terms for rich descriptions of credentials, competencies, skills, jobs, occupations, providers, quality assurance entities and processes, assessments, pathways, learning opportunities, outcomes, and more. CTDL is a continuously evolving framework that supports global linked open data for credentials. Credential Engine offers unparalleled technical, programmatic, application, and policy expertise. This resource provides deeper insight into the CTDL and Credential Registry, and how they can power and improve learning and work data ecosystems.

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Fact Sheets

Publishing Jobs Data with CTDL: One-Pager

Publishing linked open data about jobs increases opportunities for people to achieve their learning and career pathway goals spanning education, training, and work. Using the Credential Transparency Description Language (CTDL) and the Credential Registry offers an open standard, transparent, and data-driven approach to bridging the gap between education and work in data ecosystems. It supports informed decision-making, effective skill matching, and collaborative partnerships for the betterment of learners, employers, and the economy. This one-pager provides key value propositions for improving the connections between learning and work in data ecosystems.

Fact Sheets

Publishing Jobs Data with CTDL: One-Pager

Publishing linked open data about jobs increases opportunities for people to achieve their learning and career pathway goals spanning education, training, and work. Using the Credential Transparency Description Language (CTDL) and the Credential Registry offers an open standard, transparent, and data-driven approach to bridging the gap between education and work in data ecosystems. It supports informed decision-making, effective skill matching, and collaborative partnerships for the betterment of learners, employers, and the economy. This one-pager provides key value propositions for improving the connections between learning and work in data ecosystems.

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