Credential EngineCredential Engine
Fact Sheets

Linked Data Fact Sheet

Structured data is machine-readable and used by search engines to understand the content of web pages. Linked Data is a type of structured data that links between systems via the Web. When data is both structured and linked, it becomes a powerful tool that search engines and other systems can leverage.
Download Resource
Linked-Data-Fact-Sheet

Share this Resource

Tags: CTDL
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.

Report

Equity Advisory Council Report and Recommendations

Credential Engine’s work is centered around data transparency. Transparent, linked, open data has been identified as a particularly valuable tool for revealing inequities, understanding their root causes, and then informing and driving systemic change in a number of areas, including postsecondary education and training. Credential Engine understands that in a society rife with inequities, a commitment to open data use alone is not sufficient. To support the intentional identification and publishing of key data to aid the field in assessing equitable pathways, transfer, and the recognition of learning, Credential Engine convened a broad coalition of equity-focused thought leaders, called the Equity Advisory Council (EAC). The Council, along with HCM Strategists, and Credential Engine staff worked diligently to create a report of recommendations.

View All Resources
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.

Report

Equity Advisory Council Report and Recommendations

Credential Engine’s work is centered around data transparency. Transparent, linked, open data has been identified as a particularly valuable tool for revealing inequities, understanding their root causes, and then informing and driving systemic change in a number of areas, including postsecondary education and training. Credential Engine understands that in a society rife with inequities, a commitment to open data use alone is not sufficient. To support the intentional identification and publishing of key data to aid the field in assessing equitable pathways, transfer, and the recognition of learning, Credential Engine convened a broad coalition of equity-focused thought leaders, called the Equity Advisory Council (EAC). The Council, along with HCM Strategists, and Credential Engine staff worked diligently to create a report of recommendations.

Get in Touch

Our team of experts is ready to help you embark your credential transparency journey. Whether you have questions about our technologies, services, or don’t know how to get started, we’re here to assist.

Name(Required)
Skip to content