WebMEM™

The Protocol for Structuring, Delivering, and Conditioning Trust-Scored AI Memory on the Open Web

PROV

PROV is a W3C standard for expressing the provenance—or origin—of data, allowing machines to verify where facts come from, how they were derived, and why they can be trusted.

🧠 Full Definition

PROV (short for Provenance Ontology) is a W3C specification used to describe the lineage of information in a structured, machine-readable format. It defines who created a statement, when it was created, where it came from, and what influenced it.

In AI-oriented publishing, PROV is used to:

  • Attach source lineage to specific facts or claims
  • Reinforce verifiability through structured metadata
  • Output as part of multi-format, machine-ingestible content packages
  • Provide AI systems with the proof of origin alongside the fact itself

🧱 Why It Matters

AI systems need context and credibility—not just content. PROV allows you to show:

  • The original source of a fact (e.g., a government dataset)
  • When it was retrieved or published
  • Who authored or modified it
  • What supporting documents or datasets it links to

By publishing content with PROV metadata, you create a verifiable trust chain and enable AI to trace claims back to primary sources.

⚙️ How It Works

A standard PROV document includes entities like:

  • prov:Entity – the content or data point
  • prov:Agent – the person or system responsible
  • prov:Activity – how it was created, modified, or derived
  • prov:wasDerivedFrom – relationship to a previous version or source
  • prov:wasAttributedTo – who authored or curated it
  • prov:generatedAtTime – timestamp of content creation or modification

💡 Use Case Example

You publish a structured dataset with fragment-level facts:

  • Each fact includes a provenance record showing the original dataset, retrieval date, and the agent who published it
  • The PROV file documents prov:wasDerivedFrom relationships to the source dataset
  • AI systems ingest the content and the proof together, improving retrieval trust

🧩 Use in WebMEM/GTD

PROV is integrated into multi-format output layers alongside JSON-LD, TTL, XML, and Markdown. It is particularly valuable for:

  • Citation scaffolding with machine-verifiable lineage
  • Attaching provenance to fragment-level facts in glossaries and datasets
  • Publishing verifiable retrieval surfaces for AI systems

🗣️ In Speech

“PROV is the structured format that tells the AI where your content came from, who created it, and why it should be trusted.”

🔗 Related Terms