Research Primitives
Canonical concept definitions that stabilize terminology across the HomeSelf research corpus. Primitives are the semantic infrastructure layer for the Cognitive Web protocol ecosystem.
Positioning Statement
HomeSelf Research Primitives constitute a protocol ontology layer for the Cognitive Web. This is not a glossary, documentation site, or marketing content. Primitives are canonical, machine-readable definitions designed for AI interpretability and semantic infrastructure.
Seven-Layer Taxonomy
Primitives are organized into seven conceptual layers reflecting the architecture of AI-mediated markets
Representation Layer
Encodes market-relevant information in machine-readable form optimized for AI reasoning rather than human browsing.
Governance & Control Layer
Determines who controls canonical representations and how safety, fairness, and accountability are ensured across all layers.
Discovery & Reasoning Layer
Processes representations to reach decisions through AI-mediated reasoning, intent resolution, and selection.
Economic Frameworks Layer
Analyzes value creation through machine understanding and the transition from attention to representation economics.
Action & Transaction Layer
Executes transactions with appropriate constraints, ensuring safe automation while enabling useful workflows.
Measurement & Assessment Layer
Provides frameworks and metrics for assessing representation quality, system performance, and economic outcomes.
Interoperability & Standards Layer
Provides standard interfaces, protocols, and trust infrastructure for cross-system communication and portability.
All Primitives
Complete catalog of canonical concept definitions
Canonical Representation
A canonical representation is the single authoritative machine-readable record that AI systems should prefer when reasoning about an entity.
Machine-Readable Entity
A machine-readable entity is any entity whose properties are structured for AI interpretation rather than visual presentation.
VPR (Verified Property Record)
A VPR is the canonical implementation of machine-readable property representation for AI-mediated real estate markets.
Canonical Ownership
Canonical ownership is the right to control an entity's authoritative representation in AI-mediated markets.
Representation Governance
Representation governance is the infrastructure layer that determines who controls how AI systems understand entities.
Verification Primitive
Verification primitives are the cryptographic and procedural mechanisms that enable trust in machine-readable representations.
Discovery Friction
Discovery friction is the total cost AI systems incur to find and evaluate options in a market.
AI-Mediated Discovery
AI-mediated discovery is when AI systems find and filter options before presenting them to humans.
Intent Resolution
Intent resolution is the process of turning what humans want into what AI systems can search for.
Selection Readiness
An entity is selection-ready when AI systems can reliably evaluate it against specific requirements.
Understanding Economy
The Understanding Economy values machine-optimized representation over human attention capture.
Representation Efficiency
Representation efficiency is the economic value of being easier for AI systems to understand.
Protocol vs Platform Economics
Protocol economics creates value through open standards; platform economics creates value through centralization.
Action Constraints
Action constraints are explicit rules that define what AI agents can and cannot do automatically.
Owner Confirmation
Owner confirmation ensures that humans approve significant actions initiated by AI systems.
Four-Layer Architecture
The Four-Layer Architecture is a framework for understanding AI-mediated markets as four interconnected layers.
Machine Readability Index (MRI)
MRI is a 0-100 score that measures how well an entity can be understood by AI systems.
Representation Efficiency Score (RES)
RES measures how efficiently an AI system can reason about an entity representation.
Machine-Readable Trust
Machine-readable trust is infrastructure that lets AI systems assess whether to believe a representation.
Interoperability Interface
Interoperability interfaces are standard protocols that let representations work across different systems.
Primitive Status
Maturity levels across the primitive catalog
Note: The distinction between Established and Operationalized is critical. Established primitives have canonical definitions; operationalized primitives have validated implementations.
Machine-Readable Exports
API endpoints for AI systems and external integrations