On December 17, 2024, Credential Engine hosted the CTDL Terms Proposal for Representing Qualifications Frameworks as Linked Open Data webinar. The event followed the work of the Qualifications Frameworks as Data Global Task Group, bringing together stakeholders to explore how the proposed updates to the Credential Transparency Description Language (CTDL) can enhance the representation and use of qualifications frameworks as structured, linked open data.
What the Webinar Covered
The webinar highlighted:
- The CTDL update process and outcomes from the Qualifications Frameworks as Data Task Group.
- The global significance of qualifications frameworks in supporting learner mobility and international credential recognition.
- How the proposed CTDL terms can represent progression levels, alignments between frameworks, and relationships to credentials, assessments, and other resources.
- The potential for these capabilities to improve transparency, interoperability, and usability across education and workforce systems worldwide.
Access Webinar Materials
Whether you attended or registered for the webinar, you can now access the materials to explore the proposal in more detail:
- Webinar Recording: Video, Audio, Transcript, Chat
- Presentation Deck: Public Webinar: 17-December-2024: Qualifications Frameworks Terms Proposal
- Draft CTDL Qualifications Frameworks Terms Proposal: V2.0 Qualifications Frameworks as Data Terms Proposal 21-November-2024
How to Provide Feedback
Your input is critical to ensuring the proposed terms meet global needs. Feedback on the CTDL Qualifications Frameworks Terms Proposal is welcomed until January 10, 2025. Share your input using any of the following options:
- Google Docs: Contribute suggestions to the V2.0 Qualifications Frameworks as Data Terms Proposal 21-November-2024 focusing on the yellow-highlighted new terms.
- GitHub: Add comments via GitHub Issue #970.
- Email: Send feedback to info@credentialengine.org.
Why Your Feedback Matters
Your contributions will help refine these terms to support clear, standardized, and interoperable data about qualifications frameworks. By improving how frameworks are represented and connected as linked open data, we can empower learners, workers, and systems worldwide to make better-informed decisions.