Learning records

Interoperability: learning traces

In short:

  • The learning traces interop building block is a parser translating datasets of learning traces into a common xAPI profile


Start date: T0 (T0 = expected: Q1 2023)
End date : T0 + 12 months
Duration (in months): 12

Where we are now

  • A common xAPI Profile is currently being discussed with the member of the Learning Analytic working group
  • The work will start Q1 of 2023. Want to learn more and join the effort: join here!

Objectives and Expected Outcomes

The objective of this building block is to specify and develop APIs type "parser" to convert educational traces from one standard to another. Depending on the software and tools used in the field of education and training (LMS, LXP, ENT, etc.) several standards coexist in terms of data model of learning traces: SCORM, xAPI, cmi5, IMS Caliper, etc. This task will allow to combine learning traces data sets expressed in different standards. This will allow, among other things, the aggregation of datasets (e.g. from LRS) in order to obtain either a larger volume of data or a follow-up of learning over a longer period of time and/or across several applications and educational platforms. These combined datasets will allow training of Machine Learning models on a scale that was previously impossible, except in situations of monopolistic data appropriation (e.g. Microsoft with Linkedin, Linkedin Learning and Teams).
Note that by nature, the aggregation of learning traces could pose problems of identification of the individuals concerned (i.e. the learners). Therefore, in alignment with the Anonymization and Pseudonymization task, the APIs of this task will de facto integrate anonymization and pseudonymization functionalities, with a particular vigilance for geographical data which are generally the weak points allowing de-anonymization.


  • Definition of the architecture of the API endpoints in accordance with the technical recommendations of GAIA-X
  • State of the art of the latest evolutions of learning traces standards
  • Quantitative inventory of the main software learning outcomes standards and tools used in the field of education and training in France and in Europe from the list identified in the working groups of the Data space Education & Skills (i.e. SCORM, xAPI, cmi5, IMS Caliper)
  • Development of the endpoints necessary for parsing the various priority standards identified above
  • Integration of anonymization/pseudonymization features
  • expression of data in JSON-LD format to ensure interoperability with other data spaces
  • API testing with model datasets provided by Prometheus volunteer partners (see support list)
  • De-anonymization tests of learning traces (in connection with the task Anonymization and Pseudonymization)
  • Deployment of the service in a managed version in one of the partner cloud providers
  • Development of automated service deployment scripts for multi-cloud use (infrastructure as code e.g. Terraform) at partner cloud providers
  • Drafting of the public documentation, hosting and putting it online

Sequence diagram


T0 + 4
Documents : Specification, state of the art and quantitative study
T0 + 8
Development of the service and production launch in beta version (v0)
T0 + 10
QA test report + de-anonymization tests
T0 + 12
Development of final version (v1) of the service + multi-cloud deployment scripts