Skip to end of metadata
Go to start of metadata

You are viewing an old version of this page. View the current version.

Compare with Current View Page History

« Previous Version 13 Next »

UPM recommends the morph-xr2rml tool in order to convent data from mongDB to RDF.
UPM has experience with morph and we could afford this task.
We also can contribute to T2.4 with recommendations on which ontologies can fit the model better.

InfAI:

For a semantic-representation of our current data, my colleagues recommended the tools:

Depending on our use-cases of a RDF representation, it might be sufficient to only map data and queries to our actual MongoDB content. In case we have more sophisticated usage scenarios (e.g. a lot of requests), it is better to have an ETL process to a fully featured triple-store.
Anyway, we came up with the following vocabs to (basically) describe slides, decks, users and all the rest:

  • Sioc
  • Doap
  • DC
  • Foaf

As another colleague of mine researches about co-evolution of RDF based data, he has an extensive overview of changeset describing vocabs, that might fit for our revision model of slides/decks.


Klaas notes hangout 16-12-2016 (Roy, Antje, Klaas):
Multiple use-case for semantic representation/annotation:

  1. In-page semantic annotation (manual add+view. Use NLP?) based on LOD cloud and custom ontologies (Upload own ontology?!). makes slide content more explicit - Good for learners/teaching (RQ: Klaas)
  2. NLP/Named entity recognition (LSI?) on slide content to detect topics of slide/slides/decks - link to LOD
  3. Be an LOD provider - RDF store - store ontologies + instances + provide SPARQL query endpoint
  4. Semantic search - search in semantic annotations / decks/slides in RDF. cluster slides/decks based on topics
  5. Translate RDF/semantic-annotations?!
  6. We already have a system for tagging → help in determining topics / link to LOD cloud. Antje: could use of training - currently lack of data.

Do we want to semantically represent all data on slidewiki (users, comments, etc..) or only public data, or only tags/semantic annotions? More data is more use cases.

Research questions:


Klaas - RQ: Do in-slide semantic annotations and (possibly) domain ontology of teaching materials/didactic help learners (slide consumers) and teachers/instructors (slide consumers) in better learning (better grade results, better understanding, support for diverse students (languages)) + better learning analytics? Relates to use case 1 + use case 4 + use case 5
Klaas - RQ: Can we infer new knowledge based on annotations on slides? Relates to use case 1 + use case 4 + use case 5

Klaas - RQ: can we propose a ontology + instances + relationships + knowledge base for a certain deck/lecture series based on the annotated instances in a deck/series of slides?



  • No labels