Definition:
The Format Diversity Score™ is a metric that reflects how many distinct, structured output formats are generated and published from a single canonical data or content source. It indicates the publisher’s effort to accommodate multiple AI/ML ingestion pathways and reinforce machine-readable trust.
Why It Matters:
AI/ML systems, search engines, and semantic parsers differ in what they can read and process. While some prefer JSON-LD, others ingest RDF (Turtle), XML, Markdown, or PROV. By publishing the same core data in multiple formats, a publisher ensures broader discoverability, verification, and trust propagation.
Common Formats That Contribute to Format Diversity:
- JSON-LD: Schema-rich structure for search engines and NLP
- RDF Turtle: Triple-based data for knowledge graph ingestion
- XML: Hierarchical structure used in legacy systems
- Markdown: Human-readable structured text (useful for summarization models)
- PROV JSON: Provenance metadata for source verification
- CSV: Flat file format for spreadsheet-based systems (optional, may reduce score if over-relied upon)
How It’s Used in Semantic Trust Conditioning™:
Within a Semantic Digest system, the Format Diversity Score serves as an indicator of structured publishing maturity. A high score suggests that the publisher is actively reinforcing trust signals across multiple ingestion endpoints and AI interfaces.
Example Use:
A Medicare Advantage plan detail page generates Semantic Digests in 5 formats: JSON-LD, Turtle, XML, Markdown, and PROV. This results in a high Format Diversity Score, which increases the likelihood of its facts being recognized, trusted, and reused across AI and search systems.
Related Terms:
Semantic Digest · Trust Signal · Semantic Trust Conditioning