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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.
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.
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.
Examples of digital credentials that are designed to include alignments to the Registry are Open Badges, W3C Verifiable Credentials, and Velocity Network credentials. Use these simple steps to enrich digital credentials by linking to CTDL data in the Registry.
Learning Economy Foundation and Credential Engine Joint Services Scaling LER Ecosystems with Linked Open Data and LearnCard
Learning Economy Foundation (LEF) and Credential Engine (CE) are excited to announce a partnership and joint services offering to empower learners and accelerate the adoption of open tools and protocols that enable individual agency and organizational insights. Together, LEF and CE bring a complementary package of technologies and best practices to states, post-secondary institutions, employers, and any organization looking to make ecosystem-level impact at scale.
This Action Guide describes the phases and steps that stakeholders can take to develop and sustain trusted LER ecosystems. It is based on Credential Engine’s widely and successfully used State Roadmap and Action Guide for Transparency
These questions are intended to help potential developer partners think about the various ways you might use Credential Engine’s Registry and the CTDL schema.
Credential Engine offers a suite of unique technologies and services to help many different types of organizations, agencies, and companies achieve their goals for credential and competency transparency. In addition to our open, freely available resources, we offer fee-based services for strategy, project management, and implementation support focused on using CTDL data effectively.
This fact sheet contains sample language to help communicate institutional expectations for credential transparency.
Increase the relevance of the credentials and programs you offer by using the Credential Registry to publish linked open data about their value, transferability, alignments to occupational and industry frameworks (such as O*NET and NICE), job skills, and other relevant information.