This document describes a method for extracting metadata from open online courses on the Open edX platform using a NoSQL database and dynamic mapping of queries. An ontology was developed to model course structure and content, which is stored in a triplestore with a SPARQL endpoint. This allows courses to be interlinked and their materials made more reusable and flexible. Future work proposed includes fully integrating this approach into Open edX and developing recommendation services.

1. Dmitry Mouromtsev, Aleksei Romanov, Dmitry Volchek and Fedor
Kozlov Laboratory ISST @ ITMO University, St. Petersburg, Russia
“Metadata Extraction from Open edX Online Courses
Using Dynamic Mapping of NoSQL Queries”

2. The evolution of education technologies

3. MOOC statistics

4. Course distribution

5. Students enrollment in edx.org

6. The Open edX platform

7. • Use semantics to make education materials reusable and
flexible
• Interlink different types of data
• All advantages of Linked Data for education
Stay Linked

8. Just Imagine

9. • Enhanced Course Ontology for Open edX Platform
• Triple store and SPARQL endpoint as a backend
• Data providers for automatic data extraction
Basics

10. Course structure hierarchy

11. Course structure hierarchy

12. Course structure hierarchy

13. Course structure hierarchy

14. Ontology development tools
• Protégé - open source ontology editor
http://protege.stanford.edu
• Ontodia - free online OWL and RDF diagramming tool
http://ontodia.org

15. • 18 Classes
14 Object Properties
23 Data Properties
• based on Top-level
ontologies: AIISO,
BIBO, TEACH
Ontology model (course and users)

16. Ontology model (course structure)

17. • The Course Structure API not provides the information about
content
• Data about courses and their content is stored in MongoDB
database
• SQL database rewriters as are no use
Method

18. Method

19. Implementation

20. Outcomes
select ?s ?p ?o where
{?s ?p <http://www.semanticweb.org/EdxOntology/Main#ObjectId('5690d8ac457ebc0ba9429fb5')>}
SPARQL queries to extracted metadata

21. • Download course data via SPARQL endpoint
• Develop new and update existing courses by refining and
reusing already existing information.
• Interlink and relate distinct courses
Conclusion

22. • Documentation and implementation of the described method
as a component of Open edX
• Full ontology mapping with course information on any
language
• Recommendation service for course developers
• Native edX integration
Future Work

23. Thanks!
Dmitry Volchek - dvolchekspb@gmail.com
Romanov Aleksei - gloomspb@gmail.com
https://github.com/ailabitmo/edx-ontology
Russia, Saint-Petersburg, 2016