Validate structured data
Check whether data conforms to explicit structural constraints.
Desired outcome
Validation findings tied to stated rules.
Explore from the outcome
Where this function can lead
These documented connections are starting points for selection, not a ranked list.
Ways to do it
Methods that can help achieve this outcome.
- Expectation-based validation
Run explicit assertions about data properties against selected datasets.
Link evidence: GX Core overview
- RDF shape validation
Check an RDF data graph against explicit graph-shaped constraints.
Link evidence: Shapes Constraint Language (SHACL)
- Schema-based validation
Apply explicit structural rules to identify records that do not conform.
Link evidence: JSON Schema Draft 2020-12
Tools and services
Software or services that can put a method to work.
- Ajv
JavaScript validator that compiles JSON Schemas into validation functions.
Link evidence: Getting started with Ajv
- GX Core
Python library for defining data expectations and running validation workflows.
Link evidence: GX Core overview
Specifications and guidance
Standards and frameworks relevant to the work.
- JSON Schema Draft 2020-12
Specification for describing and validating the structure of JSON data.
Link evidence: JSON Schema Draft 2020-12
- SHACL
W3C language for validating RDF graphs against stated shapes.
Link evidence: Shapes Constraint Language (SHACL)
Typical inputs
- Structured records and a schema
Typical outputs
- Pass/fail results and validation errors
Sources
Last reviewed 2026-09-30