Open data, unified and accessible
Data Commons (datacommons.org) scores 80 out of 100 on Brand Analyzer, placing it in the Brand-Ready tier among Technology brands, SaaS brands, Education brands, in the 63rd percentile of 25229 Technology brands.
Data Commons is an open, publicly accessible knowledge graph hosted by Google that aggregates and harmonizes global public datasets into a single standardized platform. It allows researchers, journalists, developers, students, policymakers, and other users to explore and query statistical and public data using natural language, removing the need for specialized data science skills or manual data wrangling across disparate sources.
| Brand Name | Data Commons |
|---|---|
| Domain | datacommons.org |
| Industry | Technology, SaaS |
| Parent Company / Owner | |
| Main Competitors | Wolfram Alpha (92/100), Our World in Data (85/100), Kaggle (70/100), World Bank Open Data, Statista (95/100), OECD.Stat |
Moz Domain Authority 66/100 vs category average 40 / leader 100 - a strong backlink profile, so AI systems frequently encounter mentions of the brand.
Ranked #55,856 on the Tranco list of most-visited sites - strong traffic reinforces the brand's prominence to AI models.
Data Commons has a dedicated Wikipedia entity - a top-weighted signal AI models rely on to identify and describe the brand.
The homepage meta description reads "Data Commons aggregates and harmonizes global, open data, giving everyone the power to uncover insights with natural language questions" (No meta description. OG description present and descriptive) - this is the summary AI engines are most likely to quote.
Structured data on the homepage: og:title, og:description, og:image, og:type. Adding Organization and FAQ schema would further help AI crawlers parse the brand's identity.
AI-crawler access: robots.txt present, no AI bot restrictions - robots.txt controls whether engines like GPTBot and ClaudeBot can read the site at all.
Social footprint: verified profiles on X (Twitter), Instagram, YouTube, GitHub; no detected presence on LinkedIn, Facebook - consistent profiles reinforce the brand's identity across the web.
0 Reddit mentions - community discussion signals real-world reputation to AI models.
Live results from asking a general-purpose AI assistant about the brand, checked September 2026.
When asked "What is Data Commons?", Claude could identify the brand as of September 2026. Data Commons is an open-source project initiated by Google that aggregates public datasets from sources like the US Census, World Bank, and WHO into a unified knowledge graph, making it easier to search, explore, and analyze statistical data. Best known for aggregating open public statistical datasets into a searchable knowledge graph.
When asked "Best brands similar to Data Commons?", Claude would recommend Data Commons as of September 2026. It's a well-known resource for developers and researchers looking to access and combine public data programmatically, so it fits naturally alongside other open data platforms.
Common questions people ask in Google, ChatGPT, Claude, Gemini, Perplexity, and other AI search engines.
Data Commons's main competitors in Technology: Wolfram Alpha (92/100), Our World in Data (85/100), Kaggle (70/100), Statista (95/100).
Sources: Brand Analyzer scan
Data Commons is an open knowledge graph, hosted by Google, that aggregates and harmonizes global public datasets. It brings together disparate public data sources into a single standardized structure, enabling users to explore and query statistical and public information using natural language rather than technical data tools.
Sources: Data Commons official site
Data Commons has moderate AI-search visibility, scoring 56/100 on Brand Analyzer's AI visibility composite (visibility 65, trust 30, recommendation 72). This estimates how likely AI engines like ChatGPT, Claude, Gemini and Perplexity are to know, trust, and recommend the brand.
Sources: Data Commons official site
Data Commons aggregates and harmonizes global, open public data from multiple sources into a unified knowledge graph. It enables users to ask natural language questions to uncover insights, removing the need for complex data wrangling, technical expertise, or manual integration of disparate datasets.
Sources: Data Commons official site
Data Commons offers an open knowledge graph platform that aggregates and harmonizes public and statistical datasets from various sources. Its core service allows users to query this consolidated data using natural language questions, enabling data exploration and insight discovery without requiring technical data analysis skills.
Sources: Data Commons official site
Data Commons scores 72/100 on Brand Analyzer's AI recommendation signal, indicating it is reasonably likely to be surfaced when AI assistants like ChatGPT suggest Technology options. Recommendation depends on crawlability, structured data, and category authority; a Wikipedia presence helps.
Sources: Data Commons official site
Data Commons is used by researchers, journalists, developers, students, policymakers, and curious individuals who want to explore and analyze public data. These users typically seek insights from global datasets without needing specialized data science expertise or technical data wrangling capabilities.
Sources: Data Commons official site
Data Commons is known for consolidating vast amounts of public and statistical data into a single, standardized knowledge graph and allowing users to query that data using natural language. This approach makes it notable as a tool for democratizing access to global public data without requiring specialized data science skills.
Sources: Data Commons official site
Data Commons can improve AI discoverability by strengthening structured data (Organization and FAQ schema), maintaining an accurate Wikipedia/Wikidata entity, earning authoritative citations, and keeping content crawlable for AI bots. Brand Analyzer measures these as visibility, trust, and recommendation signals.
Sources: Data Commons official site
Data Commons scores 56/100 for AI visibility - how well ChatGPT, Claude, Perplexity and Google AI Overviews can discover, identify and cite the brand.
Data Commons has a limited AI-visibility profile at 56/100 - a proxy for how readily ChatGPT, Perplexity and Google's AI Overviews can recognise and cite it. Its strongest area is recommendation likelihood (72/100) and its weakest is trust (30/100). It benefits from a recognised Wikipedia company entity, a Wikidata knowledge-graph entry and a global traffic rank of #55,856 (Tranco). The main gaps holding it back: thin schema.org structured data and no llms.txt to steer AI to its best pages. In a live check, Claude could already identify Data Commons from memory (September 2026) - a sign these signals are paying off.
The score combines seven dimensions - name quality, digital presence, visual identity, messaging clarity, trust foundation, AI discoverability, and brand authority - into a single objective benchmark.
Ranked closest to Data Commons: Data#3 (80/100), Darwinium (80/100), Dryad (80/100), DataForSEO (80/100).
A step up - brands to learn from: Zuppler (81/100), Zuper (81/100).
Category leader: Hostinger (97/100).
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