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WebMEM™

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

  • Primer
  • Memory-First
  • Protocols
    • SDT Specification
    • WebMEM SemanticMap
    • WebMEM MapPointer
    • Digest Endpoint Specification
    • ProvenanceMeta Specification
    • AI Retrieval Feedback Loop Specification
    • Semantic Feedback Interface (SFI) Specification
    • Glossary Term Protocol (GTP) Specification
    • Examples
  • RFC
  • Glossary
  • About
    • WebMEM License
    • Mission
    • Charter

JSON-LD

JSON-LD is a lightweight, machine-readable format that uses linked data to define entities, relationships, and metadata—making content more understandable and retrievable for AI systems.

🧠 Full Definition

JSON-LD stands for JavaScript Object Notation for Linked Data. It’s the most widely adopted format for publishing structured data on the web, especially in the context of schema.org markup. It allows you to describe the meaning of your content—what it is, who created it, what it refers to, and how it connects to other trusted entities.

Within WebMEM, JSON-LD plays a foundational role in creating semantic digests, boosting retrievability, and supporting semantic trust conditioning.

💡 Why It Matters

JSON-LD enables AI systems and search engines to:

  • Understand the structure and relationships of your content
  • Associate definitions, citations, and answers with verified entities
  • Recall your content as part of a training or retrieval memory graph

Google, Bing, and nearly every major LLM indexer prefer JSON-LD for structured content ingestion.

⚙️ How It Works

JSON-LD uses simple key-value pairs to describe content:

{
  "@context": "https://schema.org",
  "@type": "DefinedTerm",
  "name": "Retrievability",
  "description": "Retrievability is the likelihood that your content will be retrieved by an AI system.",
  "url": "https://webmem.com/glossary/retrievability"
}

It can be embedded directly in the <script> tag of a webpage or served via dedicated /semantic/jsonld/ endpoints as part of your structured content exports.

🧩 Use in WebMEM

JSON-LD is used in:

  • Glossary term markup (@type: DefinedTerm)
  • FAQPage and Dataset schema outputs
  • Provenance tagging for claim-level verification
  • Multi-format semantic digests for AI memory conditioning

It’s the most compact and portable way to describe your content’s structure and meaning to machines.

🗣️ In Speech

“JSON-LD is the universal language AI systems use to understand who you are, what your content means, and why they should trust it.”

🔗 Related Terms

  • Semantic Digest
  • DefinedTerm
  • Retrievability
  • Structured Content Endpoints
  • Provenance


Primary Sidebar

Table of Contents

  • Adversarial Trust
  • Agentic Execution
  • Agentic Reasoning
  • Agentic Retrieval
  • Agentic System
  • Agentic Systems Optimization (ASO)
  • Agentic Web
  • AI Mode
  • AI Retrieval Confidence Index
  • AI Retrieval Confirmation Logging
  • AI TL;DR
  • AI Visibility
  • AI-Readable Web Memory
  • Canonical Answer
  • Citation Authority
  • Citation Casting
  • Citation Context
  • Citation Graph
  • Citation Hijacking
  • Citation Scaffolding
  • Co-Citation Density
  • Co-occurrence
  • Co-Occurrence Conditioning
  • Conditioning Half-Life
  • Conditioning Layer
  • Conditioning Strategy
  • Contextual Fragment
  • Data Tagging
  • data-* Attributes
  • Data-Derived Glossary Entries
  • DefinedTerm Set
  • Directory Fragment
  • Distributed Graph
  • Domain Memory Signature
  • EEAT Rank
  • Eligibility Fragment
  • Embedded Memory Fragment
  • Entity Alignment
  • Entity Relationship Mapper
  • Entity-Query Bond
  • Ethical Memory Stewardship
  • Explainer Fragment
  • Format Diversity Score
  • Fragment Authority Score
  • Functional Memory
  • Functional Memory Design
  • Glossary Conditioning Score
  • Glossary Fragment
  • Glossary-Scoped Retrieval
  • Graph Hygiene
  • Graph Positioning
  • High-Trust Surface
  • Implied Citation
  • Ingestion Pipelines
  • Installed Memory
  • JSON-LD
  • Machine-Ingestible
  • Markdown
  • Memory Conditioning
  • Memory Curation
  • Memory Federator
  • Memory Horizon
  • Memory Node
  • Memory Object
  • Memory Reinforcement Cycle
  • Memory Reinforcement Threshold
  • Memory Surface
  • Memory-First Publishing
  • Microdata
  • Misreflection
  • Passive Trust Signals
  • Persona Fragment
  • Personalized Retrieval Context
  • Policy Fragment
  • Procedure Fragment
  • PROV
  • Public Memory
  • Python Fragment
  • Query-Scoped Memory Conditioning
  • Reflection Decay
  • Reflection Log
  • Reflection Loop
  • Reflection Sovereignty
  • Reflection Watcher
  • Reinforced Fragment
  • Resilient Memory
  • Retrievability
  • Retrieval Bias Modifier
  • Retrieval Chains
  • Retrieval Fidelity
  • Retrieval Fitness Dashboards
  • Retrieval Share
  • Retrieval-Augmented Generation (RAG)
  • Same Definition Across Surfaces
  • Schema
  • Scoped Definitions
  • Scored Memory
  • Semantic Adjacency Graphs
  • Semantic Amplification Loop
  • Semantic Anchor Layer
  • Semantic Conditioning
  • Semantic Credibility Signals
  • Semantic Data Binding
  • Semantic Data Template
  • Semantic Digest
  • Semantic Persistence
  • Semantic Persistence Index
  • Semantic Proximity
  • Semantic Retrieval Optimization
  • Semantic SEO
  • Semantic Trust Conditioning
  • Semantic Trust Explainer
  • Semantic Visibility Console
  • Signal Weighting
  • Signal Weighting Engine
  • Structured Memory
  • Structured Retrieval Surface
  • Structured Signals
  • Surface Authority Index
  • Surface Checklist
  • Temporal Consistency
  • Three Conditioning Vectors
  • Topic Alignment
  • Training Graph
  • Trust Alignment Layer
  • Trust Anchor Entity
  • Trust Architecture
  • Trust Drift
  • Trust Feedback Record (TFR)
  • Trust Footprint
  • Trust Fragment
  • Trust Graph
  • Trust Layer
  • Trust Marker
  • Trust Node
  • Trust Publisher
  • Trust Publisher Archetype
  • Trust Publishing
  • Trust Publishing Markup Layer
  • Trust Scoring
  • Trust Signal
  • Trust Surface
  • Trust-Based Publishing
  • TrustRank™
  • Truth Marker
  • Truth Signal Stack
  • Turtle (TTL)
  • Verifiability
  • Vertical Retrieval Interface
  • Visibility Drift
  • Visibility Integrity
  • Visibility Stack
  • Visibility System
  • XML

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