AI search visibility / Entity and structured data / ARTEFACT
Schema implementation
Structured data generated from the same content the page renders, so the two can never drift apart.
Schema implementation drawn as a pipeline. Parts: Content mapping, Schema generator, Validation checks and Structured data register. Acceptance: Every scoped page emits JSON-LD from its approved content record. The emitted entities and properties match the facts visible on the page. Every scoped page passes the agreed automated validation checks.
01
Content mapping
02
Schema generator
03
Validation checks
04
Structured data register
- Every scoped page emits JSON-LD from its approved content record.
- The emitted entities and properties match the facts visible on the page.
- Every scoped page passes the agreed automated validation checks.
WHAT THIS ARTEFACT IS
A named output with defined parts
Schema implementation generates machine-readable entities and relationships from the same approved content records used by the visible page, preventing markup from drifting away from published facts.
What is inside it
- 01
Content mapping
Approved page fields map to named schema properties without maintaining a second copy of the same fact.
- 02
Schema generator
The page render produces the selected JSON-LD entities and relationships from those content records.
- 03
Validation checks
Automated checks reject missing required fields, invalid values and markup that disagrees with visible content.
- 04
Structured data register
The register lists each page, entity type, source fields, owner and latest validation result.
WHAT IT TAKES
Inputs, time and ownership
FROM YOU
4 inputs
- Access to page templates
- Approved content records
- A named content owner
- Current markup examples
WORKING RANGE
CLIENT ROLE
A content owner must approve the entity facts, relationships and visible page text that the markup describes.
WHERE IT SITS