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Module 16: Comprehensive Structured Data & Schema Patents

200+ patents across 20 categories of structured data — the most complete patent reference for schema markup and rich results.

Overview: 20 Categories of Structured Data Patents

This module covers how Google interprets, validates, and uses every major schema type. Understanding these patents reveals why certain schema implementations work and others fail.

#CategoryPatent Count
1Schema.org Interpretation & Vocabulary7+
2JSON-LD Processing & Validation8+
3Microdata Extraction & Parsing8+
4RDFa Parsing & Resource Description8+
5Rich Snippet Generation15+
6Knowledge Panel Data Extraction10+
7FAQ Schema Processing5+
8HowTo Schema Implementation5+
9Product Schema & E-Commerce Data20+
10Review & Rating Schema10+
11Event Schema Processing8+
12Recipe Schema Implementation5+
13Video & Multimedia Schema12+
14Article & News Schema10+
15LocalBusiness & Location Schema15+
16Organization Schema8+
17Person/Author Schema8+
18Breadcrumb & Navigation Schema5+
19Sitelinks Search Box Schema3+
20Schema Spam Detection & Validation10+

CATEGORY 1: Schema.org Interpretation & Vocabulary

Key Patents:

PatentFiledInnovation
US 20220292143A12021Dynamic website characterization using LLMs
US 9268820B22012Knowledge panels from schema
US 20140280084A12013Semantic deduplication via schema
US 20200279151A12018Graph neural networks for schema
WO 2018106974A12017Content validation via schema

How Google Uses Schema.org:

  • Schema.org defines 800+ types and 3,000+ properties
  • Type hierarchies enable inheritance (LocalBusiness extends Organization extends Thing)
  • Properties nested for complex relationships
  • Extracts entity type from primary markup
  • Validates against schema.org vocabulary
  • Maps properties to knowledge graph fields

CATEGORY 2: JSON-LD Processing

Why JSON-LD Is Google's Preferred Format:

  • JavaScript in <script> tags — no HTML structure dependency
  • Multiple JSON-LD blocks on single page supported
  • Easier for JavaScript frameworks to generate
  • Preferred for Google Assistant integration
  • Portable — can be injected without modifying HTML

Google's JSON-LD Processing Steps:

  1. Parse JSON structure
  2. Validate against schema.org vocabulary
  3. Extract typed properties
  4. Resolve nested objects
  5. Map to entity/content indexes

CATEGORY 3: Microdata Extraction

Microdata HTML Structure:

html
<div itemscope itemtype="https://schema.org/Person">
  <span itemprop="name">Bill Slawski</span>
  <span itemprop="jobTitle">Director of SEO Research</span>
  <span itemprop="worksFor" itemscope
        itemtype="https://schema.org/Organization">
    <span itemprop="name">Go Fish Digital</span>
  </span>
</div>

Processing: DOM tree parsing → scope boundary detection → property value extraction.


CATEGORY 5: Rich Snippet Generation (15+ Patents)

Rich Result Eligibility Requirements

ALL of these must be true:
1. Schema markup present and valid
2. Marked-up content visible on page (not hidden)
3. Schema accurately reflects actual page content
4. Page passes quality threshold
5. Page is indexed and crawlable
6. No spam violations

Rich Result Types by Schema Type

Schema TypeRich ResultSERP Feature
FAQPageExpandable Q&A pairsSERP accordion
HowToNumbered stepsStep-by-step rich result
ProductPrice, rating, availabilityShopping carousel
AggregateRatingStar ratingsStars under title
EventDate, location, ticketsEvent rich result
RecipeCook time, calories, ratingRecipe card
VideoObjectThumbnail, duration, key momentsVideo carousel
ArticleAuthor, publish date, imageTop stories
BreadcrumbListPath hierarchyBreadcrumb in SERP
WebSite + SearchActionSearch boxSitelinks search box

CATEGORY 6: Knowledge Panel Data Extraction

US9268820B2 - Knowledge Panel Creation (2016)

Knowledge Panel Triggers:

  • Entity has significant web presence
  • Schema.org markup confirms entity type
  • Wikidata/Wikipedia page exists
  • Sufficient inbound citations

Data Sources (Priority Order):

  1. Official website structured data (JSON-LD)
  2. Wikipedia / Knowledge Graph internal data
  3. Wikidata properties
  4. High-authority third-party sources
  5. Web-crawled facts with high confidence

Building Toward a Knowledge Panel

json
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "@id": "https://yourdomain.com/#organization",
  "name": "Your Company Name",
  "url": "https://yourdomain.com",
  "logo": "https://yourdomain.com/logo.png",
  "description": "Clear entity description",
  "foundingDate": "2010",
  "sameAs": [
    "https://en.wikipedia.org/wiki/Your_Company",
    "https://www.wikidata.org/wiki/Q12345",
    "https://www.linkedin.com/company/yourcompany",
    "https://www.facebook.com/yourcompany"
  ],
  "knowsAbout": ["Topic 1", "Topic 2", "Topic 3"]
}

CATEGORY 7: FAQ Schema Processing

Implementation Requirements

html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is the question text?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "The complete answer text."
      }
    }
  ]
}
</script>

FAQ Rich Result Rules:

  • Questions must be actual H2/H3 on the page (or prominently visible)
  • Answers must be complete in the schema (not just references)
  • Max ~10 Q&A pairs for display
  • Do not use for self-promotional content (Google rejects)

CATEGORY 8: HowTo Schema

Implementation Pattern

json
{
  "@type": "HowTo",
  "name": "How to [do task]",
  "totalTime": "PT30M",
  "estimatedCost": {"@type": "MonetaryAmount", "currency": "USD", "value": "0"},
  "step": [
    {
      "@type": "HowToStep",
      "name": "Step 1 Name",
      "text": "Step 1 description",
      "image": "https://example.com/step1.jpg"
    }
  ]
}

CATEGORY 9: Product Schema (20+ Patents)

Required Product Properties

json
{
  "@type": "Product",
  "name": "Product Name",
  "description": "Product description",
  "sku": "SKU123",
  "brand": {"@type": "Brand", "name": "Brand Name"},
  "offers": {
    "@type": "Offer",
    "price": "29.99",
    "priceCurrency": "USD",
    "availability": "https://schema.org/InStock",
    "url": "https://example.com/product"
  },
  "aggregateRating": {
    "@type": "AggregateRating",
    "ratingValue": "4.5",
    "reviewCount": "127"
  }
}

CATEGORY 15: LocalBusiness Schema

Complete LocalBusiness Implementation

json
{
  "@context": "https://schema.org",
  "@type": ["LocalBusiness", "RoofingContractor"],
  "@id": "https://example.com/#business",
  "name": "Business Name",
  "url": "https://example.com",
  "telephone": "+1-555-000-0000",
  "address": {
    "@type": "PostalAddress",
    "streetAddress": "123 Main Street",
    "addressLocality": "City",
    "addressRegion": "State",
    "postalCode": "12345",
    "addressCountry": "US"
  },
  "geo": {
    "@type": "GeoCoordinates",
    "latitude": "25.7617",
    "longitude": "-80.1918"
  },
  "openingHoursSpecification": [
    {
      "@type": "OpeningHoursSpecification",
      "dayOfWeek": ["Monday", "Tuesday", "Wednesday", "Thursday", "Friday"],
      "opens": "08:00",
      "closes": "18:00"
    }
  ],
  "hasMap": "https://goo.gl/maps/[your-link]",
  "priceRange": "$$",
  "servesCuisine": "N/A",
  "sameAs": ["https://maps.google.com/?cid=XXXXXXXXXXXXXXXX"]
}

CATEGORY 17: Person/Author Schema

Author Schema for E-E-A-T

json
{
  "@type": "Person",
  "@id": "https://example.com/#author-name",
  "name": "Author Name",
  "jobTitle": "SEO Expert",
  "description": "15-year SEO professional specializing in...",
  "url": "https://example.com/author/name",
  "image": "https://example.com/author-photo.jpg",
  "sameAs": [
    "https://www.linkedin.com/in/authorname",
    "https://twitter.com/authorhandle"
  ],
  "worksFor": {
    "@id": "https://example.com/#organization"
  },
  "knowsAbout": ["SEO", "Content Marketing", "Technical SEO"]
}

CATEGORY 20: Schema Spam Detection

What Triggers Schema Spam Flags

Google Rejects Schema When:

  • Marked content is not visible on the page
  • Schema claims do not match actual page content
  • AggregateRating on pages without actual reviews
  • Fake or incentivized reviews in schema
  • FAQ content that's self-promotional advertising
  • Schema irrelevant to page purpose

The Entity Schema Stack (Priority Implementation Order)

For any business or author entity, implement in this order:

1. Organization / LocalBusiness — Entity establishment
2. Person (Author) — Author attribution and E-E-A-T
3. WebSite + SearchAction — Sitelinks search box
4. WebPage / Article / BlogPosting — Page-level metadata
5. BreadcrumbList — Navigation hierarchy
6. FAQPage — Q&A rich results
7. Service / Product — Service/product schema
8. AggregateRating — Reviews (only if real reviews exist)

Key Patents Referenced

PatentTitleYear
US9268820B2Knowledge Panel from Schema2012-2016
US8594996B2Entity Disambiguation via NLP2012-2014
US20150127617A1Entity Salience2015
EP3005168A1Featured Snippet Eligibility2015
US20120158633A1Knowledge Graph2012
WO 2018106974A1Content Validation via Schema2017-2018

Next Steps

  1. YouTube & Video SEO Module — Video schema
  2. Local SEO Module — LocalBusiness schema in depth
  3. E-E-A-T Module — Author schema and trust

Grounded in Bill Slawski's SEO by the Sea patent research