[Profile picture of Ruben Verborgh]

Ruben Verborgh

TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs

Tom De Nies, Frank Salliau, Ruben Verborgh, Erik Mannens, and Rik Van de Walle

A popular way to log learning processes is by using the Experience API (abbreviated as xAPI), also referred to as Tin Can. While Tin Can is great for developers who need to log learning experiences in their applications, it is more challenging for data processors to interconnect and analyze the resulting data. An interoperable data model is missing to raise Tin Can to its full potential. We argue that in essence, these learning process logs are provenance. Therefore, the W3C PROV model can provide the much-needed interoperability. In this paper, we introduce a method to expose PROV using Tin Can statements. To achieve this, we made the following contributions: (1) a formal ontology of the xAPI vocabulary, (2) a context document to interpret xAPI statements as JSON-LD, (3) a mapping to convert xAPI JSON-LD statements into PROV, and (4) a tool implementing this mapping. We preliminarily evaluate the approach by converting 10 xAPI statements taken from the public Tin Can Learning Record Store to valid PROV without loss of information, therefore ensuring that the conversion process is reversible.

full text BibTeX other citation formats

Published in 2015 in Proceedings of the Linked Learning Workshop.

Keywords:

Read this article online

Cite this article in your work

Cite this article easily using its BibTeX entry: 

@inproceedings{denies_lile_2015,
  author = {De Nies, Tom and Salliau, Frank and Verborgh, Ruben and Mannens, Erik and Van de Walle, Rik},
  title = {{TinCan2PROV:} Exposing Interoperable Provenance of Learning Processes through Experience {API} Logs},
  year = 2015,
  month = may,
  pages = {689--694},
  booktitle = {Proceedings of the Linked Learning Workshop},
  url = {http://www.www2015.it/documents/proceedings/companion/p689.pdf},
}

Alternatively, pick a reference of your choice below:

ACM
Tom De Nies, Frank Salliau, Ruben Verborgh, Erik Mannens, and Rik Van de Walle. 2015. TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs. In Proceedings of the Linked Learning Workshop, 689–694.
APA
De Nies, T., Salliau, F., Verborgh, R., Mannens, E., & Van de Walle, R. (2015). TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs. Proceedings of the Linked Learning Workshop, 689–694.
IEEE
T. De Nies, F. Salliau, R. Verborgh, E. Mannens, and R. Van de Walle, “TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs,” in Proceedings of the Linked Learning Workshop, 2015, pp. 689–694.
LNCS
De Nies, T., Salliau, F., Verborgh, R., Mannens, E., Van de Walle, R.: TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs. In: Proceedings of the Linked Learning Workshop. pp. 689–694 (2015).
MLA
De Nies, Tom, et al. “TinCan2PROV: Exposing Interoperable Provenance of Learning Processes through Experience API Logs.” Proceedings of the Linked Learning Workshop, 2015, pp. 689–94.

Discuss this article