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SPARQL Queries

Because a parsed model is an ordinary Apache Jena DatasetGraph, you can run standard SPARQL over it with Jena's ARQ engine — no special API. This page shows how to query parsed CIM data and points you to static query validation when you want to catch query mistakes before you run anything.

Querying parsed CIM data​

Parse a model, build a query with the appropriate CIM namespace prefix, and execute it against the CimDatasetGraph:

import de.soptim.opencgmes.cimxml.parser.CimXmlParser;
import de.soptim.opencgmes.cimxml.sparql.core.CimDatasetGraph;
import org.apache.jena.query.*;
import java.nio.file.Path;

CimXmlParser parser = new CimXmlParser();
CimDatasetGraph dataset = parser.parseCimModel(Path.of("model.xml"));

String queryString = """
    PREFIX cim: <http://iec.ch/TC57/CIM100#>
    SELECT ?equipment ?name
    WHERE {
        ?equipment a cim:Equipment ;
                   cim:IdentifiedObject.name ?name .
    }
    """;

Query query = QueryFactory.create(queryString);

// Execute query on the CIM dataset
try (QueryExecution qexec = QueryExecutionFactory.create(query, dataset)) {
    ResultSet results = qexec.execSelect();
    while (results.hasNext()) {
        QuerySolution solution = results.nextSolution();
        // Process results
    }
}
Match the CIM version's namespace

Use the prefix that matches your model's CIM version: http://iec.ch/TC57/2013/CIM-schema-cim16# for CIM 16, http://iec.ch/TC57/CIM100# for CIM 17, and https://cim.ucaiug.io/ns# for CIM 18. See Compliance for the full table.

Named graphs in the dataset​

A full model exposes its body as the default graph and its header under a named graph, while a difference model keeps the forward/reverse/preconditions containers as separate named graphs (see Architecture). Plain WHERE { ... } patterns match the default graph (the body); use GRAPH ?g { ... } if you need to query header or difference graphs explicitly.

Validate queries statically first​

Running a query tells you whether it returns rows — not whether it is correct for the schema. A typo in a class name or a property used on the wrong domain silently returns nothing. CIMVocabCheck validates SPARQL statically against the CIM/RDFS profiles — flagging unknown classes and properties, domain/range violations, and datatype mismatches — without executing the query and without needing any RDF data. Pair it with CIMXML to catch query mistakes before they reach a dataset.