This project is an experiment into an Elm-based front-end to a Sparql 1.1 compliant endpoint. It is thoroughly tested against Jena Fuseki over the rest API.
The design philosophy recognizes that in general select queries return tabular data, while construct queries return graph data in the shape of subject, predicate, object triples.
For the purpose of the UI, the graph results are pivoted in such a way that all predicate/objects for a subject are gathered onto a 'card'. The reverse of the 'card' (Back Links) shows all places where the subject of the 'card' appears in the object position in other triples.
In this project Server.py is a Python Flask API that intercepts Sparql commands, forwards them to the endpoint and prepares the results for the front end.
- Apache Jena Fuseki. Choose the latest release from the Maven Repository. This is a Java
jarand so needs a working Java JRE or SDK. The latest version as at 2021-02-16 is 3.17.0, which is used below. Usecurlto get a copy as below:
curl --output <WHERE-YOU-WANT-TO-HOLD-FUSEKI> https://repo1.maven.org/maven2/org/apache/jena/jena-fuseki-server/3.17.0/jena-fuseki-server-3.17.0.jar
The server can be started with the following command:
java -Xmx2g -jar fuseki-server.jar --tdb2 --loc <WHERE-YOU-WANT-YOUR-DATABASE> --set tdb:unionDefaultGraph=true --update <THE-NAME-OF-YOUR-DATASET>
- A Python 3.6+ environment.
There are a standard set of queries which I use a lot to investigate a Knowledge Graph. These start with ! and convert to the full query in the query window. For example, !size converts to select (count(*) as ?count) {?s, ?p ?o}.