This repo is for testing approaches to deploying Qlever and the UI and Mapping via Docker compose files.
If you are interested in these components, you should check out them directly at;
Also, if you just want to run Qlever local with data for testing, you should use Qlever-control
This repo is really focused on leveraging the above in custom Docker compose workflows and eventually in tools like Dagster.
Also see the README.md in catalogues for how to download and index data from your own Qleverfile.
At present the compose.yaml is the main config we are working with.
The following two extensions to QLever are of interest.
Path Search Feature Documentation for SPARQL Engine
May also want to try qlever format: Accept: application/qlever-results+json
curl -s "http://workstation.lan:7001" -H "Accept: text/tab-separated-values" -H "Content-type: application/sparql-query" --data "SELECT * WHERE { ?s ?p ?o } LIMIT 10" ;
curl -s "http://workstation.lan:7001" -H "Accept: text/tab-separated-values" -H "Content-type: application/sparql-query" --data @./searchODIS/dataset.rq ;
curl -s "http://workstation.lan:7019?timeout=600s&access-token=odis_7643543846_6dMISzlPrD7i" -H "Accept: text/csv" -H "Content-type: application/sparql-query" --data "SELECT * WHERE { ?s ?p ?o }" > results.csv