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Ontologies & Data Model

Structured knowledge representation built on FIBO standards with custom ƒXYZ extensions for progressive membership, multi-token systems, and AI agent integration. Our ontology-driven approach ensures semantic interoperability with global financial standards.

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Foundation: FIBO (Financial Industry Business Ontology)

The Financial Industry Business Ontology provides the standardized foundation for our knowledge graph, ensuring compatibility with global financial systems and regulatory frameworks.

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Core FIBO Components

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Financial Instruments

Standardized definitions for currencies, derivatives, and financial products:

• Currency classifications and exchange rate models
• Liquidity instruments and risk parameters
• Derivative contracts and structured products
• Credit facilities and lending instruments

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Market Infrastructure

Trading venues, settlement systems, and market data structures:

• Exchange definitions and trading protocols
• Settlement mechanisms and clearing systems
• Order book structures and price discovery
• Market data feeds and reference systems

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Regulatory Framework

Compliance standards and regulatory entity relationships:

• KYC/AML standards and verification procedures
• Reporting requirements and regulatory submissions
• Jurisdiction mapping and legal frameworks
• Compliance rules and audit requirements

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Legal Entities

Corporate structures and legal relationship definitions:

• Corporate hierarchies and ownership structures
• Legal jurisdictions and regulatory domains
• Contractual relationships and agreements
• Fiduciary responsibilities and obligations

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ƒXYZ Custom Extensions

Custom ontologies that extend FIBO to support ƒXYZ-specific concepts while maintaining interoperability.

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Membership Schema

Progressive membership system with rites and validation:

@prefix fxyz: <https://fxyz.network/ontology/> .
@prefix fibo: <https://spec.edmcouncil.org/fibo/ontology/> .

fxyz:Member a owl:Class ;
    rdfs:subClassOf fibo:LegalPerson ;
    rdfs:label "Network Member" ;
    rdfs:comment "Individual or entity participating in the ƒXYZ network" .

fxyz:memberLevel a owl:DatatypeProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range [ owl:oneOf ( "Novice" "Expert" "Master" ) ] .

fxyz:validationScore a owl:DatatypeProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range xsd:float .

fxyz:ritesCompleted a owl:ObjectProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range fxyz:Rite .

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Token Ecosystem

Multi-token system with provenance tracking:

fxyz:TokenSystem a owl:Class ;
    rdfs:subClassOf fibo:FinancialInstrument ;
    rdfs:label "ƒXYZ Token System" .

fxyz:florinBalance a owl:DatatypeProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range fxyz:ConfidentialAmount .

fxyz:jouleCredits a owl:DatatypeProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range fxyz:EnergyUnits .

fxyz:howTokens a owl:DatatypeProperty ;
    rdfs:domain fxyz:Member ;
    rdfs:range fxyz:KnowledgeUnits .

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Governance Model

Holacracy-inspired governance with circle structures:

fxyz:GovernanceCircle a owl:Class ;
    rdfs:subClassOf fibo:Organization ;
    rdfs:label "Governance Circle" .

fxyz:circleHierarchy a owl:ObjectProperty ;
    rdfs:domain fxyz:GovernanceCircle ;
    rdfs:range fxyz:GovernanceCircle .

fxyz:roleDefinition a owl:ObjectProperty ;
    rdfs:domain fxyz:GovernanceCircle ;
    rdfs:range fxyz:Role .

fxyz:proposalSystem a owl:ObjectProperty ;
    rdfs:domain fxyz:GovernanceCircle ;
    rdfs:range fxyz:GovernanceProposal .

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Fixie Integration

AI agent schema with capabilities and permissions:

fxyz:Fixie a owl:Class ;
    rdfs:subClassOf fibo:Agent ;
    rdfs:label "Digital Agent (Fixie)" .

fxyz:agentType a owl:DatatypeProperty ;
    rdfs:domain fxyz:Fixie ;
    rdfs:range [ owl:oneOf ( "Personal" "Public" "OnPremise" ) ] .

fxyz:capabilities a owl:ObjectProperty ;
    rdfs:domain fxyz:Fixie ;
    rdfs:range fxyz:AgentCapability .

fxyz:permissions a owl:ObjectProperty ;
    rdfs:domain fxyz:Fixie ;
    rdfs:range fxyz:PrivacyControlMatrix .

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Temporal Schema

Time-based relationships integrated with Solana Proof-of-History for immutable event ordering and temporal querying capabilities.

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Temporal Properties

• PoH Integration: Solana slot numbers for cryptographic event ordering
• Block Timestamps: Immutable time anchoring to blockchain
• Relationship Evolution: How connections change over time
• State Transitions: Member progression and status changes
• Event Causality: Cause-effect relationship mapping

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Query Capabilities

• Historical Queries: Graph state at any point in time
• Trend Analysis: Relationship evolution patterns
• Causal Inference: Event impact analysis
• Predictive Modeling: Future state projections
• Audit Trails: Complete change history with verification

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Temporal Relationship Example

{
  "@context": "https://fxyz.network/ontology/transaction",
  "type": "FinancialRelationship",
  "source": "member:alice",
  "target": "member:bob", 
  "relationship": "CONFIDENTIAL_TRANSFER",
  "amount": {
    "currency": "FLORIN",
    "value": "encrypted_with_elgamal",
    "proof": "zk_proof_hash"
  },
  "temporal": {
    "timestamp": "2024-12-20T14:22:15Z",
    "pohSlot": 123456789,
    "blockHash": "5eykt4UsFv8P8NJdTREpY1vzqKqZKvdpKuc147dw2N9d"
  },
  "validation": {
    "fixieValidated": true,
    "peerWitnesses": ["member:charlie", "member:dave"],
    "complianceCheck": "PASSED"
  }
}

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RDF & Neo4j Integration

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RDF Standards

Our ontologies follow W3C standards for maximum interoperability:

• rdflib-neo4j: Direct RDF to Neo4j graph mapping
• SPARQL Queries: Standard semantic web query language
• Linked Data: URIs for global resource identification
• Schema Validation: SHACL constraint checking and validation

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Neo4j Enhancement

While maintaining RDF compatibility, we leverage Neo4j’s native capabilities:

• Cypher Queries: Graph-native query language for performance
• Performance Optimization: Native graph algorithms and indexing
• Real-time Updates: Live data synchronization and streaming
• Vector Embeddings: AI/ML integration for semantic search

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Schema Evolution

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Versioning Strategy

Ontologies evolve with the network while maintaining backward compatibility:

• Semantic Versioning: Major.minor.patch version control
• Migration Scripts: Automated data transformation tools
• Deprecation Paths: Graceful transition for obsolete concepts
• Extension Points: Designed flexibility for future concepts

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Community Governance

Schema changes follow the same governance process as network decisions:

• Proposal Process: RFC-style documentation and review
• Expert Review: Technical validation by ontology experts
• Community Consensus: Member voting on significant changes
• Implementation Timeline: Coordinated rollout across applications

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Validation & Quality Assurance

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Automated Validation

• SHACL Constraints: Automated constraint checking
• Consistency Rules: Logical consistency validation
• Performance Testing: Query performance benchmarks
• Integration Tests: Cross-system compatibility verification

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Manual Review Process

• Expert Review: Domain expert validation
• Use Case Testing: Real-world scenario validation
• Documentation Review: Clarity and completeness checks
• Community Feedback: Member input and suggestions

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Implementation Guidelines

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Best Practices

• URI Design: Consistent, resolvable URI patterns
• Documentation: Comprehensive annotation and examples
• Testing: Thorough validation before deployment
• Performance: Optimized for common query patterns

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Development Workflow

1. Concept Identification: New concept requirements
2. Ontology Design: RDF/OWL modeling and documentation
3. Validation: Automated and manual testing
4. Integration: Neo4j mapping and performance optimization
5. Deployment: Staged rollout with monitoring

The ontology-driven approach ensures that all data and relationships in the ƒXYZ network are semantically rich, queryable, and compatible with global financial standards while enabling the advanced features unique to our decentralized architecture.