CIMVocabCheck

Static SPARQL and SHACL validation against RDFS / CIM profile schemas. CIMVocabCheck answers the question "does this query (or shapes graph) make sense for the schema I'm working with?" — without executing anything and without needing any RDF data.

It catches mistakes at development time, in unit tests, or in CI: unknown classes and properties, domain/range violations, datatype mismatches, invalid SHACL cardinalities, and typos in the standard rdf:/rdfs:/owl:/sh: vocabularies.

CIMVocabCheck ships in several forms:

Form	What it is	Page
Library	cimvocabcheck-core — the validation engine, callable from Java	Library & tests · API
CLI	cimvocabcheck-cli — a command-line tool for CI pipelines	CLI
CIMLangServer	cimvocabcheck-lsp — an LSP 3.17 server over stdio	Language server
Editors	The CIMNotebook VS Code extension & IntelliJ plugin front the language server	CIMNotebook

Inspired by gdotv's "SPARQL Query Guardrails".

Why static validation?

Running a SPARQL query against a triplestore does not tell you whether the query is correct for your schema — a typo'd property name simply returns no rows. CIMVocabCheck compares every class and property IRI in your query or shapes graph against the schema and reports what doesn't fit.

Concern	CIMVocabCheck	SPARQL execution	SHACL validation
Needs an RDF dataset	❌	✅	✅
Needs a schema (RDFS / profile)	✅	❌	✅ (shapes)
Detects unknown class / property IRI	✅	❌ (returns ∅)	❌
Detects domain / range mismatch	✅	❌	❌
Detects bad data values	❌	❌	✅

CIMVocabCheck is complementary to SHACL data validation, not a replacement: it validates the query/shape itself against the schema, where SHACL validates data against shapes.

What it checks

• Existence — every class and property IRI must exist in the selected profiles.
• Semantics — rdfs:domain / rdfs:range / rdfs:subClassOf compatibility, implied types, datatype mismatches.
• SHACL structure — sh:targetClass, sh:class, sh:path, node-kind vs range, cardinality.
• Embedded SPARQL — sh:sparql, sh:target, sh:validator, sh:rule fragments are extracted and fully validated.
• Standard vocabularies — typos like rdf:typ or sh:minCountt are flagged against the official W3C vocabularies.

See Validation checks for the complete catalogue of diagnostic codes, and Known limitations for what is intentionally not checked.

Next steps

• Getting started — run the bundled SPARQL & SHACL examples.
• Configuration — point CIMVocabCheck at your CGMES profiles via opencgmes.jsonc.
• Library & tests — drive it from Java / JUnit.