This is a library that, given a SPARQL query that can be satisfied by a certain RDF dataset, recommends semantically similar queries that can be satisfied by another dataset.
You can build the project using Maven 3 and a Java 8 SDK.
First checkout this project.
git clone https://github.com/carloallocca/Squire.git
Enter the directory you just checked out.
cd Squire
From the project directory you can build all the modules by running
mvn install -Dmaven.test.skip=true
When all unit tests work offline, we will stop recommending the -Dmaven.test.skip
flag.
If you want to build only some modules individually:
squire
: the core library, build this first.launcher
: command-line Java application as executable JAR file, depends on squirewebsquire
: Web Service version with HTTP API available as a WAR archive.
After building the project:
- Command Line : execute the JAR file in
launcher/target
to get the command syntax. - Web Service : drop the WAR file found in
websquire/target
into your Web container.
Enter the directory containing the JAR
cd launcher/target
Run the executable JAR once to get the list of available commands
java -jar org.mksmart.squire.squire-launcher-{version}.jar
(version
can be something like 1.1-SNAPSHOT
)
For example, to tell it to index two SPARQL endpoints:
java -jar org.mksmart.squire.squire-launcher-{version}.jar index \
http://opendatacommunities.org/sparql \
http://data.admin.ch/query/
After indexing them, use them to recommend the equivalent of a SPARQL query that works on the first endpoint (-s
) to the target endpoint (-t
):
java -jar org.mksmart.squire.squire-launcher-{version}.jar \
-s http://opendatacommunities.org/sparql \
-t http://data.admin.ch/query/ \
recommend "SELECT DISTINCT ?s ?p ?o WHERE {?s a <http://data.ordnancesurvey.co.uk/ontology/admingeo/District> . ?s ?p ?o }"
This process will generate a report after it ends. If you also want it to print a log to file while it executes, add the -l
option.
- Carlo Allocca, Samsung Inc.
- Alessandro Adamou, NUI Galway
- Mathieu d'Aquin, NUI Galway
Credit goes to the Knowledge Media Institute of The Open University, UK, for kickstarting this project.
You can use, fork and republish this software as you like so long as you retain these permissions and give us credit, preferably by citing this open access paper:
Carlo Allocca, Alessandro Adamou, Mathieu d'Aquin, Enrico Motta:
SPARQL Query Recommendations by Example. ESWC (Satellite Events) 2016: 128-133,
https://doi.org/10.1007/978-3-319-47602-5_26