> For the complete documentation index, see [llms.txt](https://provenance-ai.gitbook.io/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://provenance-ai.gitbook.io/docs/on-chain-structured-data.md).

# On-chain Structured Data

Provenance AI utilizes [Fact Protocol](https://fact.technology/)’s proposed provenance standard for schema markup, which ensures on-chain provenance trail storage and fact-check attestations, allowing for retrievability by both AI systems and humans.

**Below is an example of markup with source and publisher details:**

```
{
  "@context": "https://schema.org",
  "@type": "WebPage",
  "mainEntity": {
    "@type": "Article",
    "headline": "Difference: Objective Facts vs. Subjective Facts or Claims",
    "url": "https://fact.technology/learn/difference-objective-facts-vs-subjective-facts/",
    "datePublished": "2023-07-31",
    "image": "https://fact.technology/files/2023/07/difference-objective-facts-subjective-facts-claims-opinions-fact-protocol-learn.png",
    "author": {
      "@type": "Person",
      "name": "Fact Protocol Team"
    }
  },
  "publisher": {
    "@type": "Organization",
    "name": "Fact Protocol Learn",
    "sameAs": "https://fact.technology/learn/"
  },
  "factProvenance": {
    "@type": "FactProvenanceTag",
    "originalSource": "https://www.jibc.ca/sites/default/files/community_social_justice/pdf/cl/Objective_vs._Subjective.pdf"
  }
}
```