REPOSITORY OF ORGANIZED CURRICULUMS (ROC)

Photo Credit: FunSEPA, by way of Learning Equality

The Repository of Organized Curriculums (ROC) global data server is a prototype platform for publishing digital curriculum standards documents used in the educational systems of different countries. The goal of this project is to make curriculum standards data available in machine-readable formats for all countries and facilitate the exchange of learning materials in a global context, in particular Open Educational Resources (OER) that can be freely redistributed and reorganized according to local educational needs.

Read the report

Learn about the digital representation of curriculum standards and curriculum alignment by reading the report Digitizing Curriculum Standards to Unlock the Potential of Open Educational Resources in a Global Context.

For additional background about the project, see the Background page.

Browse ROC data

Explore representative data samples:

Curriculum data is also accessible on GitHub, for example see the standards-ghana repository.

What is digital curriculum data?

The ROC data model enables the process of publishing curriculum data. This encompasses three types of data: digital representation of curriculum standards documents (national standards that define what students should be learning), content correlations (links to relevant learning resources), and curriculum crosswalks (mappings between the curriculum standards in different countries).

Import formats

  • Controlled vocabularies can be loaded from YAML terms definitions, or imported from SKOS/RDF data.
  • Digitized standards can be uploaded using a spreadsheet format or through a REST API.
  • Content correlations can be imported from Kolibri Studio aligned channels.

Export formats

Current exporters include JSON and YAML data formats. Export to ASN RDF and JSON-LD is planned. Need another format?  Consult the documentation to learn how to create exporters for different formats or get in touch by email.

Contribute curriculum data