Knowledge Graph

Raw connectivity structured into organized knowledge through semantic graphs.

DIKW Transformation Pipeline

Variables → Network → Graph → Information → Intelligence → Knowledge → Wisdom

Interactive demonstration of structured knowledge emergence

A network is raw connectivity. Entities linked without context, often appearing as chaotic "hairballs" with little insight.

A graph is a network enriched with semantics, types, and properties. Graph = Network + metadata (types, weights, directions).

By adding structure through ontologies like FIBO, we transform noise into queryable knowledge that can answer "who, what, when, where, why."

Neo4j NVL for production-grade graph visualization

React Three Fiber for 3D cosmic backgrounds

Local Neo4j Database

Custom ƒ(xyz) schema extensions

FIBO (Financial Industry Business Ontology)

RDF mapping via rdflib-neo4j

FIBO-based financial ontology and custom ƒ(xyz) schema extensions

Neo4j queries, RDF mapping, and semantic processing pipelines

Member schema, circles, projects, and network relationships

Real-time network metrics, node counts, and relationship statistics

Living systems. Autonomous agents (Fixies) validate, cross-reference, and evolve knowledge through continuous feedback loops.

Humans and AI agents curate the graph. It self-regulates.