Definition
Structured data
Also known as: schema markup, semantic markup
Structured data, in the web context, is machine-readable markup embedded in a page that states explicitly what the page contains — an article, its author, a publication date, a question and its answer — using a shared vocabulary such as Schema.org. It is written as JSON-LD, Microdata or RDFa and lets crawlers and answer engines identify entities and relationships without inferring them from prose.
The phrase covers three encodings of the same idea. JSON-LD puts a JSON object in a <script type="application/ld+json"> block. Microdata and RDFa attach attributes such as itemprop or property to the HTML elements that already hold the text. Google supports all three and recommends JSON-LD; its guidelines also require that marked-up content be visible on the page and representative of it, so markup is never a place to say things the reader cannot see.
For answer engines the value is in what survives chunking. When a page is split into passages, a paragraph in the middle of the article no longer knows who wrote the page or when it was updated. The JSON-LD block does: it carries author, datePublished, dateModified and citation as explicit fields, and an FAQPage block states that a given question and answer belong together.
{
"@type": "FAQPage",
"mainEntity": [{
"@type": "Question",
"name": "Is AEO the same as GEO?",
"acceptedAnswer": { "@type": "Answer", "text": "They overlap heavily. …" }
}]
}The practical rule is one source of truth: generate the markup from the same CMS fields that render the visible text, so the two can never disagree. Structured data for AI answers walks through the types worth emitting and the Schema.org entry lists them.
Frequently asked questions
Is structured data required to be cited by an answer engine?
No. Answer engines cite pages that have no markup at all, and Google's guidance for its AI features points at the same practices it recommends for Search rather than any extra markup. Structured data is an accuracy layer: it removes ambiguity about what a passage is, who wrote it and when, which are the things a retrieval system otherwise has to guess.