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Glossary

What Is JSON-LD (A Structured Data Format)

JSON-LD is a structured data format embedded in a page as JSON; it lowers comprehension cost, not a citation promise.

Author
Xingge
Published
2026-11-09
Updated
2026-11-09
Level
L2 Reproducible
Version
1.0

Term details

Name
What Is JSON-LD (A Structured Data Format)
Type
Glossary
ID
json-ld-en

What Is JSON-LD (A Structured Data Format)

JSON-LD (JavaScript Object Notation for Linked Data) is a structured data format embedded in a page as JSON, and the recommended usage by schema.org. Structured data only lowers comprehension cost; it is not a promise of citation.

Definition

This site's working definition: JSON-LD is a script block that describes page entities and page relationships with key-value structures, usually organized with @graph and covering the site, organization, author, page, and breadcrumbs.

This site writes only two fields for an entity, the identifier and the name; the remaining fields are maintained on the entity home page, so the same subject does not carry conflicting descriptions across sites.

Boundaries: what it is easily confused with

Easily confused conceptKey difference
MicrodataMicrodata lives in HTML attributes; JSON-LD is a separate block
Schema standardschema.org is a vocabulary convention, not a search engine rule
Page body textStructured data is a supplementary description and does not replace body text

Common misconceptions

  • Assuming that adding JSON-LD earns citations. It only affects comprehension cost.
  • Letting structured data contradict body text. Conflicts between fields and body text are read as untrustworthy.
  • Repeating complete entity fields on every page. Scattered field maintenance easily produces conflicts.

Basis and verification

This definition is this site's working definition, marked L2. Required fields and examples for each page type are on the machine-readable layer method page in the method index.

Review cycle: 180 days.

Related sections: glossary index, method index, metric index, editorial policy.

Evidence

Author

Xingge

GEOA method research, focused on how Chinese LLMs cite and describe brands accurately.

Entity https://shingle.com.cn/#person

Author profile