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https://kg-construct.github.io/rml-io/spec/docs/#logical-source-in-rml uses CSVW but only to describe the location and dialect of a Table.
In a dataspace scenario we use TableSchema to describe some csv, to then provision ingest to a timeseries database, while enabling discovery and other semantic integration approaches.
CSVW is a nice focused spec dedicated to CSV semantic description, so I think it's worth examining it, mapping it to RML, and maybe finding some features to add to RML.
The CSVW Manufest is JSON (also JSON-LD) and it has one "defect": it maps columns not to RDF props but to URL templates. So maybe we should retool to use RML instead of CSVW.
The text was updated successfully, but these errors were encountered:
https://kg-construct.github.io/rml-io/spec/docs/#logical-source-in-rml uses CSVW but only to describe the location and dialect of a
Table
.In a dataspace scenario we use
TableSchema
to describe some csv, to then provision ingest to a timeseries database, while enabling discovery and other semantic integration approaches.CSVW is a nice focused spec dedicated to CSV semantic description, so I think it's worth examining it, mapping it to RML, and maybe finding some features to add to RML.
The CSVW Manufest is JSON (also JSON-LD) and it has one "defect": it maps columns not to RDF props but to URL templates. So maybe we should retool to use RML instead of CSVW.
The text was updated successfully, but these errors were encountered: