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Structured data

What is schema markup?

Schema markup is machine-readable information that describes entities, properties, and relationships represented by a page.

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Structured-data architecture

schema markup

Model visible entities and stable relationships, validate the deployed graph, and review consumer-specific requirements separately.

Primary topicschema markup

Schema markup is machine-readable information that describes entities, properties, and relationships represented by a page.

Operating outcomeAccountable improvement

Describe real entities and relationships accurately without manufacturing unsupported claims.

Review statusMaintained resource

Reviewed for accuracy, clarity, and operational use.

01

Schema.org vocabulary

Schema.org provides shared types and properties. A type represents what an entity is; properties describe it and connect it to other entities.

02

Structured-data formats

  • JSON-LD — JSON inside a script element
  • Microdata — attributes placed in HTML
  • RDFa — linked-data attributes in HTML
03

What schema does not do

  • It does not guarantee a rich result.
  • It does not replace visible content.
  • It does not make an unsupported claim true.
  • It does not fix crawl, indexing, quality, or performance problems by itself.
04

Entity fit for schema markup

Use schema markup only when the page visibly represents the corresponding entity or relationship. Begin with the page purpose and the entity graph, then select the most specific supported type. Do not let the available vocabulary dictate claims the page does not make.

01

Visible support

Every material property should be supported by visible, current, and accurate page content.

02

Stable identity

Use consistent identifiers when the same organization, person, place, product, service, or webpage appears across the graph.

03

Consumer requirements

Treat Schema.org validity and search-consumer eligibility as related but separate checks.

05

Deployment record for schema markup

  • Syntax validation, type/property validation, consumer testing, and post-deployment inspection.
  • Record the page template, generator, source fields, responsible owner, and release reference.
  • Avoid publishing properties that are unsupported, hidden, stale, or inconsistent with visible content.
  • Parse the deployed json-ld, validate the graph, compare it with visible content, and test any target consumer requirements.
  • Schedule review when visible content, offers, ownership, locations, products, or consumer documentation changes.
Next useful action

Turn schema markup into an accountable record.

A maintainable structured-data graph for schema markup with stable identifiers and ownership.