Credential Transparency Identifiers (CTIDs) bring the benefits of unique identifiers to credentialing ecosystems. CTIDs allow credentials and their associated information to be distinguished, thoroughly described, and widely recognized through effective data management practices.

Unique identifiers enable industries to help people identify, describe, and compare specific offerings. Examples of industry agreements about useful unique identifiers include UPC codes for retail products, URLs for webpages, ISBNs for books, GPS coordinates for locations, and MLS numbers for real estate listings. 

Credential Transparency Identifiers (CTIDs) bring the benefits of unique identifiers to credentialing ecosystems. CTIDs allow credentials and their associated information to be distinguished, thoroughly described, and widely recognized through effective data management practices.

What is a CTID?

A CTID is a globally unique identifier associated with a specific credential or credential-related resource. The Credential Transparency Description Language (CTDL) defines 69 different types of resources utilizing CTIDs, including credentials, programs, courses, organizations, competencies, and more. These clearly defined types of resources can be expanded as CTDL expands to address the needs of credentialing ecosystems.

Each CTID is made up of a standard UUID prefixed with “ce-”. For example, the CTID for Ivy Tech Community College’s Associate Degree in Cyber Security Information Assurance is “ce-48b8cad7-2c58-4a9c-b46a-74caa362d30b”. This unique format ensures that no two CTIDs have the same value, enabling systems to easily identify specific resources and exchange data reliably.

How do CTIDs work?

Applications use CTIDs to help people access credential information across multiple systems and platforms. This makes it convenient for individuals to engage with credentialing ecosystems, regardless of where the information is stored. To ensure precise tracking and comprehensive descriptions of CTDL data, it is essential for databases to store CTIDs for the purpose of publishing and/or consuming CTDL data.

The Credential Registry serves as one connection point for data using CTIDs. Information associated with any CTID published to the Credential Registry can be accessed directly by appending the CTID to URLs. For example,

These links can be embedded in various systems and applications to ensure that clearly identified credential information is integrated across a variety of applications, including across multiple organizations, such as career exploration tools, marketing platforms, curriculum management tools, longitudinal data systems, transfer systems, college catalogs, and digital credentialing tools, as well as within Learning and Employment Records issued to individuals. 

Call to Action

Considering the substantial size of the credentialing market, the growing demand for reliable, transparent credential information, the wide array of stakeholders seeking such information, and the pivotal role credential information plays in numerous consequential decisions, Credential Engine strongly recommends that credential data managers integrate CTIDs into their source data systems. 

Join the movement towards more transparent credentialing ecosystems by incorporating CTIDs into your credential-related IT systems.

To learn more about CTIDs, please visit our technical site at https://credreg.net/ctdl/ctid. Reach out to info@credentialengine.org if you have any questions or comments. 

 

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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

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.

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.

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