dataone.org 56 D
🛡️ SEO 22 🤖 GEO 81 ⚡ Perf 47 🏗️ Arch 59

dataone.org — Global SEODiff Score 56/100

dataone.org
📊

dataone.org shows strong AI visibility with an ACRI of 78/100, outperforming 89% of indexed domains. Compared to other developer sites (avg score: 57), dataone.org performs above the benchmark, suggesting strong competitive positioning in AI search. Server-side rendering keeps the ghost ratio near zero, giving AI systems direct access to all visible content. A 10.0× bloat ratio is typical for sites in this tech tier — not wasteful, but streamlining could further boost extractability. Zero schema blocks puts this site at a disadvantage in knowledge graph and AI-answer pipelines that rely on explicit structured data. The site maintains an open-door policy for AI crawlers — GPTBot, ClaudeBot, and other major agents are all allowed.

56
D — Global SEODiff Score
Comprehensive search visibility assessment
Below average — Traditional SEO (22) needs urgent attention.
🎯 Top Fix: Add Organization + WebSite JSON-LD → +5–8 pts
🔬 Automated SEODiff Assessment · Snapshot: Feb 26, 2026 · 📋 API
Does your site score higher than dataone.org?
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🧮 Score Transparency — How is this calculated?
🛡️ Traditional SEO (25% weight)22 × 0.25 = 5.5
🤖 AI Readiness / GEO (40% weight)81 × 0.40 = 32.4
⚡ Performance (20% weight)47 × 0.20 = 9.4
🏗️ Architecture & Trust (15% weight)59 × 0.15 = 8.8
Weighted sum = 5.5 + 32.4 + 9.4 + 8.8
Global SEODiff Score = 56 (D)
📊 ACRI Sub-Scores (AI Readiness Detail)
100
Bot Access
avg 92
100
Rendering
avg 93
70
Structure
avg 35
0
Schema
avg 10
90
Tech Stack
avg 64
🔀
Visibility Delta: Google vs AI
Google (Tranco)
Top 15%
Rank #148040
Aligned
Gap
AI (ACRI)
Top 11%
Score 78/100

dataone.org has balanced Google and AI visibility — both rank roughly in the same tier. ACRI measures technical crawler readiness. Read the methodology →

Why dataone.org ranks here

Tech stackHugo
Industrydeveloper
RenderingSSR
Schema coverage0 blocks
Token bloat10.0×

Fastest improvements

  • Add basic Organization and WebSite JSON-LD to fix “0 schema blocks” (see Schema Coverage).
  • Reduce token bloat (navigation/footer/code) so agents reach your main content faster (see Token Bloat).
  • Create an llms.txt file so AI crawlers can discover your content structure without heavy crawling. Generate llms.txt →
  • Run a full entropy audit to find which DOM regions waste the most tokens. Run Entropy Audit →
🧪

JavaScript Rendering Check

We check what AI crawlers miss when they skip JavaScript execution.

Running headless browser to simulate AI extraction…
🛡️

Traditional SEO

22/100 25 % of Global Score 🟢 High Confidence

📝 Title Tag

44 chars
Good length

Optimal range: 30–60 characters for SERP display.

📋 Meta Description

32 chars
Too short

Optimal range: 120–160 characters for snippet control.

🔤 Heading Hierarchy

  • ✗ Exactly 1 <h1> tag — found 0
  • ✓ Has <h2> headings — found 5
  • ✗ <h2> not before <h1>

🔍 Indexability

  • ✓ Canonical tag present → https://www.dataone.org/
  • ✓ No noindex directive
  • ✓ Meta viewport set
  • ✗ HTML lang attribute
  • ✗ Hreflang tags
  • ✓ Googlebot allowed by robots.txt

🌐 Social / OpenGraph

  • ✗ og:title
  • ✗ og:description
  • ✗ og:image
  • ✗ twitter:card
📐 How the SEO Pillar score is calculated

SEO Pillar = Title (20 pts) + Meta Desc (20 pts) + Heading Hierarchy (20 pts) + Indexability (20 pts) + Social/OG (20 pts)

Each sub-score is derived from the checks above. Canonical tag, lang attribute, og:image, and a single H1 are the highest-impact items.

🤖

AI Readiness / GEO

81/100 40 % of Global Score 🟢 High Confidence

This pillar aggregates citation share, hallucination risk, bot access, schema health, and content extractability. The individual diagnostic sections below contribute to this score.

🔗

Citation Alternatives

Research
💡
Insight: In the developer sector, hikkoshizamurai.jp (ACRI: 88) currently has stronger AI extractability. AI models tend to prefer sources with higher semantic structure and schema coverage. Domains with ACRI < 40 see 3.5× more hallucinations. Read the research →
dataone.org
59
Your ACRI Score
88
Industry Peer ACRI
AI models prioritize pages with strong semantic structure and schema coverage. hikkoshizamurai.jp has schema coverage of 5 blocks and uses Custom / Proprietary. Improve your score by implementing the remediation patches below.
📊 Side-by-Side Comparison →
🚨

Hallucination Risk

Research

Is AI lying about your brand? This panel measures how likely LLMs are to hallucinate facts when extracting information from your page.

Analyzing hallucination risk…

🤖 Bot Access Matrix

GPTBot (OpenAI)
Allowed
ClaudeBot (Anthropic)
Allowed
CCBot (Common Crawl)
Allowed
Google-Extended
Allowed
Googlebot
Allowed

👻 Rendering (Ghost Ratio) Docs

Ghost Ratio 0%
0% — Safe 50% 100% — Risk
Status Server-Side Rendered (Safe)
Rendering Type SSR

📊 Structure & Information Density Docs

Structure Grade 70/100 — Good
Structured Elements 117 elements (117 lists, 0 rows, 0 headers)
Total Words802
Raw Density14.6%

🏷️ Schema Health Docs

Organization Schema ❌ Missing
Product / Service Schema ⚠️ Not Found
Total Schema Blocks0 — No JSON-LD detected

Schema Coverage Map

0/7 schema types detected
❌ Organization
❌ Product/Service
❌ Breadcrumb
❌ FAQ
❌ Article
❌ WebSite
💡Organization schema missing. AI models cannot identify your brand entity. Without it, your brand won't appear in Knowledge Panels or be associated with your content.
💡Product / Service schema missing. AI models don't know this is a SaaS product. Add Product or SoftwareApplication schema so AI understands what you offer and can surface pricing/features.
💡BreadcrumbList schema missing. AI cannot understand your site hierarchy or how pages relate to each other.
💡FAQ schema missing. Adding FAQPage schema lets AI models directly extract Q&A pairs for Featured Snippets and chatbot answers.
💡WebSite schema missing. Add WebSite + SearchAction so Google can generate a Sitelinks Search Box for your brand in AI results.

📐 AI Efficiency Metrics Docs

56
AI Extractability
Low
Crawl Cost
None
Blocklist Risk
Extractability56/100 — AI models can partially extract answers from this page
Crawl CostLow (30/100) — efficient for AI crawlers to process
Blocklist RiskNone — 0 of 5 AI crawlers blocked

Token Bloat Research

10%
🗑️ 90%
Useful Content (15.6 KB)Bloat (140.6 KB)
Token Bloat Ratio10.0× — Normal

Multimodal Readiness

Visual Context86% Optimized for Vision
Image Alt Coverage50 / 58 images have alt text

TDM Rights

TDM-Reservation HeaderNot set
X-Robots-Tag: noaiNot set

🔥 Structural Entropy Check Research

0 Entropy
Poor Token Bloat: High
Noise Ratio: 90.0% · SNR: 0.11 · Signal: 3981 / Noise: 35996 tokens

🔬 AI-Crawler Simulation

See your website the way AI crawlers do. CSS stripped, structure labeled, content chunked.

🌐
This is what humans see — styled, branded, visual.
Toggle to "AI Agent View" to see what GPTBot, ClaudeBot, and other AI crawlers actually extract from this page.
🤖

AI Answer Preview

NEW

See how AI models summarize your site. Left: your actual content. Right: what the LLM extracts and says about you.

Simulating AI extraction…

🔧 Tech Stack

FrameworkHugo
AI-Readiness Score90/100
ServerApache/2.4.29 (Ubuntu)
CDN
HTTP Status200
Load Time1227 ms
Raw HTML Size156.2 KB
Visible Text Size15.6 KB

Performance & Speed

47/100 20 % of Global Score 🟢 High Confidence

⏱️ Time to First Byte

1227 ms
Slow — bots may time out or deprioritise

Google considers <200 ms "good". AI crawlers may have even shorter timeouts.

📦 Page Weight

1112
DOM nodes
156 KB
HTML payload
Moderate weight — acceptable for most scenarios

🗄️ Cache & CDN

  • ✗ Cache-Control header
  • ✗ CDN cache status
  • ✗ CDN detected

🔬 Tracker Tax

1
tracker scripts
1
third-party domains
0.0%
token overhead
Minimal tracker load — clean signal for bots
googletagmanager.com
📐 How the Performance Pillar score is calculated

Perf Pillar = TTFB (35 pts) + Page Weight (25 pts) + Cache/CDN (20 pts) + Tracker Tax (20 pts)

TTFB <200 ms = full marks. DOM >3000 or payload >300 KB incurs heavy penalties. Tracker scripts beyond 5 reduce score.

🏗️

Architecture & Trust

59/100 15 % of Global Score 🟡 Medium Confidence

🗺️ Sitemap & Robots

  • ✗ Sitemap declared in robots.txt
  • ✓ Googlebot allowed
  • ✓ GPTBot allowed
  • ✓ ClaudeBot allowed

🔗 Linking

65
internal links
7
external links
Good internal linking — helps crawlers discover content

🔒 Security & Trust

  • ✗ HSTS header (Strict-Transport-Security)
  • ✗ Content-Security-Policy header
  • ✓ HTTP status 200 OK (got 200)

♿ Accessibility Signals

  • ✗ HTML lang attribute
  • ✓ Meta viewport for mobile
  • ✗ Single H1 for screen readers
📐 How the Architecture Pillar score is calculated

Arch Pillar = Sitemap & Robots (30 pts) + Linking (25 pts) + Security (25 pts) + Accessibility (20 pts)

Having a valid sitemap, allowing AI bots, HSTS, and a good internal link count are the highest-impact items.

🏅 AI-Verified Trust Badge

Your site scores 59/100. Reach 80+ to unlock the green "AI-Verified" badge. Fix the issues below to improve your score.

AI-Verified badge for dataone.org
Pending Audit — score below 80 threshold
<a href="https://seodiff.io/radar/domains/dataone.org" rel="noopener"><img src="https://seodiff.io/api/v1/badge?domain=dataone.org" alt="AI-Verified by SEODiff" width="280" height="52"></a>

💡 Paste in your site footer, GitHub README, or email signature. Badge updates automatically as your score changes.

🔗 Similar developer Sites

Domains with a similar tech stack, industry, and AI readiness profile to dataone.org. Compare side-by-side.

Domain ACRI AI Score Tech Stack Token Bloat Schema
dataone.org (this site) 59 78 Hugo 10.0× 0
coreui.io 61 77 Hugo 8.8× 0 Compare →
perlfoundation.org 55 74 Hugo 10.6× 1 Compare →
heroiclabs.com 60 76 Hugo 12.3× 1 Compare →
nakamacloud.io 60 76 Hugo 12.3× 1 Compare →
theqrl.org 54 73 Hugo 7.7× 0 Compare →
Compare All 5 Similar Sites →
🩹

Remediation Patches

COPY-PASTE

Auto-generated code fixes tailored to dataone.org. Copy and paste these into your codebase to improve AI visibility. These patches are mathematically proven to increase extraction accuracy →

Add Organization JSON-LD
High Impact ⏱ 5 min
AI models cannot identify your brand entity without Organization schema. This is the #1 fix for AI visibility.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Dataone",
  "url": "https://dataone.org",
  "logo": "https://dataone.org/apple-touch-icon.png?v=2026-01-12_19.16.53_%2b0000",
  "sameAs": []
}
</script>
Add WebSite + SearchAction JSON-LD
High Impact ⏱ 5 min
Enables the Sitelinks Search Box in Google and allows AI to understand your site structure.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "WebSite",
  "name": "Dataone",
  "url": "https://dataone.org",
  "potentialAction": {
    "@type": "SearchAction",
    "target": "https://dataone.org/search?q={search_term_string}",
    "query-input": "required name=search_term_string"
  }
}
</script>
Add FAQ Schema
Medium Impact ⏱ 10 min
FAQ schema lets AI models directly extract Q&A pairs. This is the easiest way to get featured in AI responses.
html
<script type="application/ld+json">
{
  "@context": "https://schema.org",
  "@type": "FAQPage",
  "mainEntity": [
    {
      "@type": "Question",
      "name": "What is Dataone?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Add your answer here — describe what Dataone does in 1-2 sentences."
      }
    },
    {
      "@type": "Question",
      "name": "How does Dataone work?",
      "acceptedAnswer": {
        "@type": "Answer",
        "text": "Explain the key features and how users interact with Dataone."
      }
    }
  ]
}
</script>
📈

Projected Impact

ROI EST.

If you apply the patches above, here's the estimated improvement for dataone.org:

Current Score
78
Projected Score
94
Improvement
+16 pts
Add Organization schema +6 pts
Add WebSite schema +4 pts
Reduce token bloat +3 pts
Add FAQ schema +3 pts

*Estimates based on SEODiff's scoring model. Actual results depend on implementation quality.

📋 Data Export

Download scores and metadata for audits, client reports, or CI/CD pipelines. Exports contain computed metrics only (no copyrighted content).

All data is generated automatically and updated with each crawl. JSON exports contain scores and metadata only (no copyrighted content).

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🧭 Self-Diffing (Private Layer)

For owned domains, combine this world snapshot with private drift + regression history.
Template Drift
Track in My Site
Drift → Traffic Impact
In development coming soon
Regression Incidents
Track in My Site
Internal Linking
Deep Audit graph
Semantic Structure
GEO view in Deep Audit
Content Quality
Thin/duplicate tracking

🕒 History

Score over timeAvailable in My Site history
Drift eventsTemplate timeline + incidents
Drift → Revenue AttributionComing soon
Schema/rendering/extractability changesTracked per scan in project history