For learning SPARQL it might be useful to have full control over both the query text and the data (RDF triples). While there are many public SPARQL endpoints available their data is typically read-only for obvious reasons. To actively apply SPARQL queries to ones own data, a local triple store might be useful, e.g. for reproducing the examples from https://www.w3.org/TR/rdf-sparql-query/.
However, setting up such an infrastructure with all its dependencies might be complicated.
Question: What is the simplest¹ way to setup a local triple store with SPARQL endpoint on a usual PC?
(¹: The meaning of "simplest" depends on ones system configuration and prior knowledge, which can be reflected by different answers.)
If one has already an up-to-date Python environment, then https://github.com/vemonet/rdflib-endpoint provides a simple solution with only two commands
- pip install rdflib-endpoint (run once)
- rdflib-endpoint serve
- →Access the YASGUI SPARQL editor on http://localhost:8000
However, I am interested which alternative solutions there are.
My favourite is Blazegraph (not maintained anymore though)
Download the jar file and from command line launch it with one line
https://github.com/blazegraph/database/wiki/Quick_Start
NB. It requires Java to be installed!
An option is to download the free version of GraphDB and use locally. It comes with a SPARQL endpoint and visualisation features to explore your linked data.
Do you have Docker on your computer? If so, just choose a triplestore and setup an instance with a 1-line command.
Some examples:
- GraphDB https://hub.docker.com/r/ontotext/graphdb/
- Virtuoso https://hub.docker.com/r/tenforce/virtuoso/
- Badges
- Science topic
- Similar topics
- Mathematics