Data Standards Organizations
Definition: Technical communities and organizations that develop and put forth specifications and standards to protect learner data and promote interoperability
Examples: W3C, 1EdTech, DIF, HR Open, Credential Engine
Roles and Workstreams
Developing
- Develop and provide oversight of key standards
- Map and harmonize data standards and create and align on standards for data infrastructure - integrity, ownership, protection and privacy
Issuing
- Encourage the adoption of open standards and open application programming interfaces (APIs)
- Support including open standard linked open data in LERs to provide meaning and contextualization
Using
- Identify and close data standards gaps that hold back adoption and uptake
- Support the use of open standards for research and data analysis
Adopting
- Support the use of open standards by all types of systems, including government and open source systems as well as commercial and proprietary systems
- Provide test suites and other mechanisms for technology providers to demonstrate that their products conform to specific standards and demonstrate interoperability
“LER specifications are important, because they represent years of debate and consensus-building, among an ecosystem of stakeholders. It's not that the specifications are implying that this is the one true way of doing advancement records, it's that enough participants have agreed on one particular approach, to make it an excellent starting point.”— Dmitri Zagidulin, Co-Chair, W3C Verifiable Credentials for Education Task Force
Business Case
Technical Interoperability - Secure and interoperable exchange of learning and employment records leading to increased accessibility. Syntactic, structural, and semantic similarity to help define and develop open data standards
Efficiency and Equitable Ecosystem - More efficient and equitable learning and employment ecosystem for individual learners as well as service providers.
Data Standards - Developing open standards that empower learners and workers with data about their knowledge, skills, and abilities
Social Case
Equity and Efficiency - Opening up new ways to match people to work, learning, and resources as well as streamlining data usage in hiring
Shared Access - Collaboration among states, institutions, employers, and organizations to build a more efficient, equitable, and collaborative learning and employment ecosystem
