Wien.gv.at Schema.org Deep Analysis

Beyond Surface Metrics: Is It Unique or Boilerplate?

Analysis Date: January 25, 2026 | Deep Sample: 100 URLs | Full Sample: 250 URLs

Key Finding: Quantity vs Quality

While 100% of pages have schema.org markup, 71% of schema fields are identical boilerplate repeated across all pages. The "unique" data is limited to basic metadata (page title, URL, dates).

100%
Pages with Schema
100
Unique Schema Patterns
189
Boilerplate Fields
77
Unique Fields
0
Contact Details
12
Schema Types Used

Hypothesis Testing: Data Scientist Approach

H1: All pages have identical schema (pure boilerplate)

Test: Compare MD5 hash of full JSON-LD across all pages

✓ REJECTED: 100 unique hashes found (100% different)

H2: Organization schema is always identical

Test: Extract and compare Organization JSON across pages

✓ REJECTED: 83 different Organization schemas found

H3: Only metadata fields vary (name, URL, date)

Test: Count unique values per field across all pages

✗ CONFIRMED: 71% of fields are constant, only metadata varies

H4: Rich contact information is provided

Test: Check for phone, email, address in schema

✗ CONFIRMED MISSING: No ContactPoint JSON-LD found

The Real Picture: Boilerplate vs Unique

Uniqueness Breakdown

Quality Assessment

Quality Score

What's Actually IN the Organization Schema?

{ "@context": "https://schema.org", "@type": "Organization", "@id": "https://www.wien.gv.at/bildung/...#Organization-362ec", "dateModified": "2025-09-03T19:39:17+02:00", "datePublished": "2025-03-10T14:11:00+01:00", "inLanguage": "de-DE", "name": "MA 08" // <-- This is the ONLY useful info! }
Missing from Organization Schema:
  • Full department name (only abbreviation "MA 08")
  • Address / location
  • Phone number
  • Email address
  • Opening hours
  • Description of services
  • Parent organization (City of Vienna)
Organization Content

Fields That Actually Vary Per Page

Varying Fields
Field Unique Values Assessment
@id 100 (100%) Good - Page identifier
name 86 (86%) Good - Page title
url 86 (86%) Good - Canonical URL
description 79 (79%) Good - Page description
dateModified 60 (60%) OK - Update timestamp
headline 49 (49%) OK - Article headlines

Schema Type Combinations

Schema Combinations

Wien.gv.at uses 12 different schema type combinations. The most common is Organization + WebPage (49% of pages), followed by CollectionPage for category pages.

Surface-Level Analysis (Previous Findings)

Adoption Rate

Adoption Rate

Implementation Methods

Implementation Methods

Schema Types Found

Schema Types Bar

Type Distribution

Schema Types Pie

Conclusions for GEO

What Wien.gv.at Does Well

  • 100% schema.org coverage
  • Uses JSON-LD (modern, recommended)
  • Page-specific metadata (name, URL, dates)
  • Multiple schema types (WebPage, Article, Event, etc.)
  • Unique @id per page

What Could Be Improved

  • Organization lacks contact details
  • No phone/email in structured data
  • Department names are abbreviations only
  • No GovernmentService schema for services
  • No FAQPage for help content
  • 71% of fields are boilerplate
Bottom Line for AI/LLM Visibility

Good: AI systems can identify this as official Vienna government content and extract basic page information.

Missing: AI cannot extract contact details, service information, or department descriptions from schema - it would need to parse the HTML content instead.

Methodology

AspectDetails
Surface Analysis250 URLs random sample from 8,447 sitemap URLs
Deep Analysis100 URLs with full JSON-LD extraction and field comparison
Uniqueness TestMD5 hash comparison of serialized JSON-LD
Field AnalysisFlattened key-value extraction, unique value counting
ToolsPython, requests, matplotlib