Lexicon
Structured Data
What structured data means, and how Paul Truscott implements it as the machine-readable foundation that lowers cost-of-retrieval across every client site.
Factual Definition
Structured data is information that is organized in a predefined, machine-readable format, such as JSON-LD, Microdata, or RDFa, allowing software systems to reliably identify and interpret specific facts, entities, and relationships within a document.
Paul Truscott's Perspective on Structured Data
Paul Truscott's perspective on structured data is that it is the most direct lever available for reducing a document's cost-of-retrieval, since it removes almost all inference burden from the system trying to extract a fact. His view is that schema markup is the most common implementation of structured data in SEO contexts, but the underlying principle, declaring facts in a predefined, unambiguous format rather than embedding them in prose alone, applies more broadly across every technical layer of a site.
He treats structured data implementation as a non-negotiable baseline for every client site, regardless of how well-written the surrounding prose already is, since well-written prose and well-implemented structured data serve different audiences, human readers and machine extraction systems, and both are required.
How Paul Truscott Applies Structured Data
Paul implements comprehensive structured data across every client site as a baseline technical requirement, treating it as complementary to, not a substitute for, well-written prose, since machine extraction and human readability are separate requirements that both need to be satisfied. Read the full methodology.
Why Structured Data Matters to Paul Truscott's Practice
Structured data is the technical foundation underlying schema markup and every other machine-readable declaration Paul builds for clients, directly supporting the low cost-of-retrieval standard central to his methodology. Read the full methodology.