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Credential Engine’s Statement of Capabilities Regarding USDOL’s “Strengthening Community Colleges” Grant

Provisions are now requiring the publishing of data related to credentials and competencies in linked open data schema makes the specific reference “credential transparency description language”—the specification hosted by Credential Engine. Learn how working with CTDL will ensure compliance with USDOL's grant.
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“In addition, the Department aims to ensure that individuals, employers, education and training providers, and others have access to the most complete, current, and beneficial information about providers, programs, credentials, and skills necessary to make more informed decisions. Access includes having such information fully operable on the semantic web and able to be used in modern applications, tools, and services to support better understanding of available pathways; and the development of improved navigation and guidance tools to help individuals make better decisions about which pathways are best for them. To this end, the Department requires that information about all credentials (including, but not limited to, badges, certificates, certifications, licenses, and degrees of all levels and types) and competencies (knowledge, skills, and abilities) developed or delivered through the use of federal funds be made publicly accessible through the use of linked open data formats that support full transparency and interoperability, such as through the use of the credential transparency description language specifications.” (page 11)

– Section I.A.1.c of the SCC FOA

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Tags: Credential Ecosystem, CTDL, Data
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Fact Sheets

Open, Interoperable Data for Actionable Credential Ecosystems

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.

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

The Value of CTDL for AI

As uses of AI and machine learning are very quickly evolving for applications like skills mapping, learning opportunity recommendations, and career exploration, CTDL provides huge advantages for improved accuracy and relevance in these applications. The CTDL schema and CTDL data in the Credential Registry are highly useful for training and refining AI models because they are structured data that is organized, predefined, and formatted consistently. And the more data that is available in CTDL, the more thoroughly AI tools can analyze patterns in the linked open data and make valuable connections. Credential Engine is working with partners on innovations that combine CTDL as a rich data schema, the huge body of CTDL data that is already in the Credential Registry, and new AI-assisted tools that publish to and consume from the Credential Registry. This resource provides an overview of structured data and the value of CTDL for AI.

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