Knowledge Graph - Graph Schema Validation

Validate knowledge graph schemas and data against defined ontology, RDF/OWL, or property graph schema constraints.

Graph Schema Validation

Validate knowledge graph schemas and data against defined constraints.

This skill ensures graph data conforms to schema definitions, ontology rules, and consistency requirements.

Quick Start

Use When

• Validating graph data before ingestion
• Testing schema correctness
• Enforcing ontology constraints
• Checking graph consistency
• Verifying RDF/OWL compliance
• Validating property graph models

Inputs

• RDF datasets (Turtle, RDF/XML)
• OWL ontologies
• Property graph schemas
• Cypher structures
• Graph data files
• Graph exports

Outputs

• Validation report
• Detected violations
• Suggested corrections
• Conformance status
• Constraint violations

Example

Input Schema:

text

Student: student_id (UNIQUE), name, email
Course: course_code (UNIQUE), title, credits
Relationship: (Student)-[:ENROLLED_IN]->(Course)

Input Data:

text

(Student {name: "Alice"})              # INVALID: missing student_id
(Student {student_id: "S001", name: "Bob"})-[:ENROLLED_IN]->(Course)  # OK

Validation Report:

text

Violations: 1
- Node S002: Missing required property student_id
- Suggestion: Add student_id to Student node

Validation Types

1. Schema Conformance

• Node labels match schema classes
• Relationships follow schema rules
• Property types are valid

2. Property Validation

• Required properties present
• Data types correct
• Property names consistent

3. Relationship Validation

• Relationships follow schema rules
• Direction correct
• Source/target types valid

4. Cardinality Constraints

• Minimum/maximum occurrences
• Uniqueness constraints
• Collection sizes

5. Graph Integrity

• No orphan nodes
• No broken references
• No duplicate identifiers
• Consistent relationships

Schema Formats

RDF/OWL (SHACL Shapes)

turtle

:StudentShape a sh:NodeShape ;
  sh:targetClass :Student ;
  sh:property [
    sh:path :student_id ;
    sh:datatype xsd:string ;
    sh:minCount 1
  ] .

Property Graph (Cypher Constraints)

cypher

CREATE CONSTRAINT student_id_unique ON (s:Student) REQUIRE s.student_id IS UNIQUE
CREATE INDEX ON (s:Student)(name)

Execution Steps

1. Load Schema – Load ontology, SHACL shapes, or schema definition
2. Load Data – Load graph data to validate
3. Define Rules – Specify validation constraints
4. Execute Validation – Check data against rules
5. Generate Report – Produce validation results
6. Suggest Fixes – Recommend corrections

Recommended Libraries

• RDF/OWL: rdflib, pyshacl, owlready2
• Property Graph: neo4j, py2neo, networkx
• Data Validation: pydantic, jsonschema
• Graph Analysis: networkx

Best Practices

✓ Validate before production deployment
✓ Enforce constraints at database level
✓ Use consistent property naming
✓ Define validation rules early
✓ Maintain validation tests
✓ Document constraint rules
✓ Review violation reports carefully

References

See validation-patterns.md for validation strategies and example-validations.md for domain validation examples.

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Version: 1.0.0