JSON-LD
JSON-LD (JavaScript Object Notation for Linked Data) is a linked data format standardized by the W3C, extending JSON syntax to express semantic, structured data within digital documents. Its core mechanism uses the @context field to map JSON keys to standard vocabularies such as Schema.org, enabling explicit semantic definition and data interlinking. JSON-LD is widely used in the semantic web, structured web page markup, and knowledge graphs, and is fully compatible with existing JSON environments for straightforward integration.
Core Facts
Timeline (last 90 days)
Implementing Schema.org markup is low-cost: adding a JSON-LD script to the page head is enough, and it does not affect the human reading experience.
For e-commerce product pages, Schema.org vocabulary (such as Product, Offer, and AggregateRating) can be annotated via JSON-LD, enabling search engines (such as Google) and AI agents to extract key information directly without parsing the HTML structure.
Voxelo 3.0 publishes the captured 3D information in JSON-LD format and provides 2-3 times more product attributes than typical product pages.
JSON-LD's @graph format allows multiple nodes that reference each other via @id to be declared in a single script block, enabling search engines to link multiple entities into a graph.
Structured data is usually embedded in pages as JSON-LD, follows the Schema.org vocabulary, and uses `@context`, `@type` and properties to describe entities.
AI agents depend on structured semantic data more heavily than traditional crawlers, and schemas such as Product, SoftwareApplication, Article and Organization should be consistent with the visible content of the page.
Validation tools such as Schema Markup Validator can detect JSON-LD syntax errors and missing required fields, but cannot determine whether the semantics are consistent with visible content, which still requires manual checking.
Schema.org is a vocabulary jointly maintained by major search engines, and websites can embed markup such as Organization, Product, and FAQPage via JSON-LD or Microdata.
Schema Markup is a form of semantic annotation embedded in web pages in a machine-readable format, most commonly the Schema.org vocabulary with JSON-LD; it does not directly improve rankings itself, but it lowers the cost for models to understand the entity.
Search engines make extensive use of structured data (JSON-LD), and pages with clean, consistent facts are less likely to be misquoted.
16 more timeline events
All Facts (20)
JSON-LD is a format for embedding structured data in web pages, declared via the <script type="application/ld+json"> tag, allowing machines to understand the entities, attributes, and relationships in a page without parsing the body text.
70%Unverifieddl元素可以与Schema.org的结构化数据标注（JSON-LD或Microdata格式）配合使用，帮助搜索引擎识别FAQ富文本摘要
85%UnverifiedImplementing Schema.org markup is low-cost: adding a JSON-LD script to the page head is enough, and it does not affect the human reading experience.
50%UnverifiedFor e-commerce product pages, Schema.org vocabulary (such as Product, Offer, and AggregateRating) can be annotated via JSON-LD, enabling search engines (such as Google) and AI agents to extract key information directly without parsing the HTML structure.
50%UnverifiedVoxelo 3.0 publishes the captured 3D information in JSON-LD format and provides 2-3 times more product attributes than typical product pages.
50%UnverifiedJSON-LD's @graph format allows multiple nodes that reference each other via @id to be declared in a single script block, enabling search engines to link multiple entities into a graph.
50%UnverifiedStructured data is usually embedded in pages as JSON-LD, follows the Schema.org vocabulary, and uses `@context`, `@type` and properties to describe entities.
50%UnverifiedValidation tools such as Schema Markup Validator can detect JSON-LD syntax errors and missing required fields, but cannot determine whether the semantics are consistent with visible content, which still requires manual checking.
50%UnverifiedAI agents depend on structured semantic data more heavily than traditional crawlers, and schemas such as Product, SoftwareApplication, Article and Organization should be consistent with the visible content of the page.
50%UnverifiedSchema.org is a vocabulary jointly maintained by major search engines, and websites can embed markup such as Organization, Product, and FAQPage via JSON-LD or Microdata.
50%UnverifiedSchema Markup is a form of semantic annotation embedded in web pages in a machine-readable format, most commonly the Schema.org vocabulary with JSON-LD; it does not directly improve rankings itself, but it lowers the cost for models to understand the entity.
50%UnverifiedSearch engines make extensive use of structured data (JSON-LD), and pages with clean, consistent facts are less likely to be misquoted.
50%UnverifiedCompared with Microdata and RDFa, JSON-LD is decoupled from the HTML structure and is easier to reuse and maintain in component-based frontends.
50%UnverifiedThe new content digest retains body text, links, HTML attributes, title, meta tags, and JSON-LD structured data, and excludes other scripts, styles, scoped-style ids, build output names, the generator tag, and whitespace characters between tags.
50%UnverifiedSchema.org provides a shared vocabulary for articles, FAQs, products, and software, and in practice it is usually embedded in the page <head> as a JSON-LD script, for crawler machines to read without affecting the user-visible rendering.
50%UnverifiedStructured data refers to key-value markup embedded in pages in formats such as JSON-LD, Microdata or RDFa, using explicit fields to describe page content.
50%UnverifiedStructured markup (Schema Markup) is standardized semantic annotation embedded in a webpage's HTML; common formats include JSON-LD, Microdata and RDFa, with Schema.org being its most widely adopted vocabulary.
50%Unverified对AI检索系统而言，JSON-LD的价值在于把事实变成机器可读的字段，使模型能直接获取结构化答案而无需从HTML文本中自行抽取
50%Unverified/api/jsonld-cross-validate extracts all JSON-LD blocks on the page, resolves cross-block @id references and detects contradictions, including the same @id with different @type, inconsistent name/url/logo declarations for the same entity, priceRange conflicts, aggregateRating conflicts, date validity, and dead sameAs links
50%UnverifiedThe author recommends using JSON-LD rather than microdata because it is a single code block, easy to maintain, and the most reliably parsed format by mainstream systems.
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