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)
Search engines make extensive use of structured data (JSON-LD), and pages with clean, consistent facts are less likely to be misquoted.
Compared with Microdata and RDFa, JSON-LD is decoupled from the HTML structure and is easier to reuse and maintain in component-based frontends.
The 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.
Schema.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.
Structured 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.
Structured 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.
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.
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
/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
The 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.
7 more timeline events
All Facts (18)
dl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%Partially VerifiedJSON-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.
65%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.
50%UnverifiedData ontologies are typically expressed in standard formats such as OWL, RDF, or JSON-LD.
50%UnverifiedSemantic markup defined by Schema.org (such as Product, Event, and FAQPage types in JSON-LD format) was originally designed for search engines.
50%UnverifiedFor RAG to work effectively, external data must have clear metadata annotation, use standardized formats (such as JSON-LD, CSV, or common ontologies like Schema.org), and enable efficient retrieval through APIs or vector databases.
50%UnverifiedWebMCP uniformly uses JSON-LD format for communication.
50%UnverifiedIn data stack practice, lighter-weight YAML configurations, JSON-LD, or proprietary DSLs are also widely used to express ontologies.
50%UnverifiedPages using JSON-LD structured data have a 40%+ improvement in the probability of being correctly parsed by AI.
50%UnverifiedJSON-LD 是 W3C 推荐的结构化数据格式，目前全球超过 30% 的网页已使用 Schema.org 标记
50%