Thinking About Guideline for Data Interoperability - Design concept and workflows for learning analytics
Download as PPTX, PDF2 likes602 views
The document discusses guidelines for data interoperability, focusing on design concepts and workflows within the context of the Korea Education & Research Information Service. It outlines potential mapping processes for structural, syntactic, and semantic data between various specifications like IMS Caliper and xAPI. Additionally, it proposes action items for further development and collaboration among experts regarding data models and implementation strategies.
Thinking About Guideline for Data Interoperability - Design concept and workflows for learning analytics
- 1. Thinking About Guideline for Data Interoperability - Design concept and workflows - Korea Education & Research Information Service Yong-Sang Cho, Ph.D zzosang@keris.or.kr FB: /zzosang Twitter: @zzosang JTC1/SC36 WG8 webinar December 1, 2015
- 2. Subject Triple Bindings Predicate Object With contexts information Learning Applications Generated (objects) Outcomes Courseware GroupTimestamp Data Structure
- 3. Event Store Learning Record StoreIMS Caliper Sensor APIs xAPIs Data Mapping & Matching Process _______________ P1. Structural & Syntactic Mapping P2. Semantic Matching Learning Environments (a) on S/W apps, platform and web Repository Metadata Repository Metadata …… Learning Environments (b) on S/W apps, platform and web …… IMS Caliper Metric Profiles xAPIs Recipes Data Flows
- 4. <IMS Caliper properties of assignable> <xAPI Statement properties> P1. Potential example for structural/syntactic mapping rule between specs
- 5. <IMS Caliper> <xAPI + Recipes> Class Class http://www.imsglobal.org/caliper/ http://adlnet.gov/expapi/Entities … Concept tree Property/relation Property/relation Concept detail tree {actor, action, event, target, generated, etc…} {actor, verb, object, context, etc…} Instance Instance { “action”: “completed” } { “verb”: “finished” } Instance Table - ontology mapping rule Structural/ Syntactic Mapping Semantic Mapping P2 (a). Potential example for ontological mapping rule between specs (under assumption xAPI’s recipes are looked as single form)
- 6. Semantic Filter/ Mapper IMS Caliper Sensor APIs xAPI – recipe (a) xAPI – recipe (b) xAPI – recipe (c) … Ontology Repo (for common sense) P2 (b). Potential example for ontological mapping rule between specs (under assumption xAPI’s recipes are looked differently)
- 7. Learning Environments … Data Collection APIs …… Collected Data Stores ………………… Data Mapping & Matching … (4) Notify learning activity occurred (5) Capture & Store data temporarily at end- point of APIs (6) Authorization for transmission (8) Test conformance & store received data (9) Request transform of data for target repository (10) Query metadata for repositories’ features, i.e. data model and URI (11) Transmit source data (7) Transmit captured data (12) Structural/Syntactic mapping (13) Semantic matching (14) Transmit transformed data (1) Identify entities and properties for data model of APIs (2) Structural/Syntactic mapping profiling (3) Semantic matching profiling (15) Test received data and exception for non-conformant data Sequence for data mapping and transformation
- 8. Action Items • Design ToC for ISO/IEC PDTR 20748-3. Any requirements? • Make use cases for lead conversation and call for further use cases to Los i.e. xAPI and IMS Caliper experts will be invited to contribute for this work • Do we need to make code for implementation? Or separate the code from this document as a reference software? i .e. using GitHub of SC36 or ask to make new project under LOs • Any other items?
- 9. More Questions? Korea Education & Research Information Service Yong-Sang CHO, Ph.D zzosang@gmail.com FB: /zzosang Twitter: @zzosang