Refine Your Search

Filters

CTDL Linked Open Data Explainer

We sometimes get questions about how CTDL, 1EdTech’s CASE specification, and the Competency and Skills System (CaSS) relate. The short answer is that CTDL is a family of open schemas designed to support Linked Open data that connects resources such as credentials and jobs to competencies; CASE is a specification designed for system-to-system exchange of competency frameworks, and CaSS is an open-source software for competency management that we utilize as part of the Credential Registry publishing system. The information below further describes these technologies and their relationships.

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.

Fact Sheets

Credential Transparency State Partnerships Overview

State and regional partners are working with Credential Engine to use the Credential Transparency Description Language (CTDL) and publish data to the Credential Registry. Credential Engine’s technologies support numerous statewide priorities. This resource provides an overview of our current state and regional partnerships.

Additional Resources

State Roadmap & Action Guide

Your State or Region’s credential transparency journey starts here.

Toolkits

Our toolkits contain useful resources for States and organizations looking to implement credential transparency. Our State Toolkit is specifically designed to be used with our Roadmap & Action Guide.

Partner Map

Meet the partners that are bringing credential transparency to their states and regions.

Skip to content