- From: <dave.lewis@cs.tcd.ie>
- Date: Thu, 29 Jan 2015 00:13:56 +0000
- To: public-csv-wg@w3.org
Hi, I have a use case in the publishing and processing of language resources where we are interested in converting the meta-data of a CSV resource into RDF without that actual data. This would allow us to use SPARQL to search for tables on the meta-data attributes without loading all the data into an RDF store. As the tables can be large, the latter is an overhead, and unnecessary to our use case as there are well developed tools to process or filter tabular language data once the tables required are located. My reading of the mapping algorithm at: http://w3c.github.io/csvw/csv2rdf/#map-annotated-tab-table is that it doesn't permit the mapping of data to be omitted, i.e. step 10 specified 'SHALL' Had you considered such a meta-data only mapping use cases? Further, such a mapping would also raise the possibility of having a RDF equivalent of the .csvm file accompanying a csv file. This might be valuable in use cases where RDF/DCAT crawlers are already in use, which could then pick up the meta-data without themselves having to implement the JSON-RDF mapping. Am I correct that currently the json .csvm format is the only valid format for meta-data. I haven't been tracking the WG very closely, so my apologies if this has already been discussed. Kind Regards, Dave -- Director - Knowledge and Data Engineering Group The CNGL Centre for Global Intelligent Content School of Computer Science and Statistics Trinity College Dublin
Received on Thursday, 29 January 2015 00:14:28 UTC