Data models and metamodels for neurosymbolic learning on LLOD?

[twktheainur]

This issue will federate the discussion and surveying of relevant data models for neurosymbolic learning in the context of LLOD

[twktheainur]

The model card ontology to reference pre-trained models that can be used in the context of neurosymbolic learning:

Publication: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-022-04797-6 Ontology on OBO Foundry: https://obofoundry.org/ontology/mcro.html

Sample java library to exploit the ontology in applications: https://github.com/UTHealth-Ontology/MCRO-Software

[gkirtzou]

Models to examine (proposed in meeting)

• DataCube: https://www.w3.org/TR/vocab-data-cube/
• FrAC module: https://www.w3.org/community/ontolex/wiki/Frequency,_Attestation_and_Corpus_Information

[gkirtzou]

On the transformation/wrapping side (proposed in meeting):

• RML : https://rml.io/specs/rml/
• CSV2RDF: https://www.w3.org/TR/csv2rdf/
• CSVW: https://csvw.org/

[twktheainur]

Description of neural architectures using OWL (scope?)

Illustrate how the embedding part of Frac could be used in that context, same for datacube Deep review needed

[twktheainur]

https://www.bobdc.com/blog/querying-machine-learning-dist/

[twktheainur]

DataURLs => #6