Structured Data
Information formatted so machines can read it directly.
Technical Term
Full explanation
Structured data is information organized in a standardized format so machines can read and interpret it directly, rather than inferring it from unstructured text.
Structured data takes many forms beyond schema markup on a webpage: database records, tables, JSON files, and standardized formats like Wikidata's statements are all structured. What they share is a predictable format that lets a machine extract a specific value reliably, rather than parsing free-form prose.
The contrast is with unstructured text, a paragraph, an article, a social post, where a fact is present but has to be located and interpreted before a system can use it. Structured data removes that interpretation step, which is why it is treated as a higher-confidence source of facts.
Why this matters
It removes guesswork. Anything a brand leaves unstructured, a system has to infer, and inference is where misrepresentation starts.
Example
A company's founding year stated in a structured record, such as a schema field or a Wikidata entry, can be pulled directly by a system. The same fact mentioned in passing within a blog post's third paragraph has to be found and correctly interpreted first.
Where this sits
Structured Data belongs to Search, SEO & Generative Optimization, one of the seven layers of the Aingworth Glossary. The established disciplines brands use to improve discoverability. Useful, and often necessary, but tactics that sit on top of a brand's underlying authority infrastructure rather than replace it.
Continue with: The Technical Work That Pays.
Related terms
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