Knowledge Graph
Everything is a network — but not everything is useful until you structure it. Transform raw connectivity into organized knowledge through semantic graphs.
DIKW Transformation Pipeline
Variables → Network → Graph → Information → Intelligence → Knowledge → Wisdom
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Network ≠ Graph
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."
Tech Stack
Visualization
Neo4j NVL for production-grade graph visualization
React Three Fiber for 3D cosmic backgrounds
Database
Local Neo4j Database
Custom ƒ(xyz) schema extensions
Ontology
FIBO (Financial Industry Business Ontology)
RDF mapping via rdflib-neo4j
Dynamic Knowledge Network
Our graphs are living systems that update in real-time through autonomous agents (Fixies). They don't just store data — they validate, cross-reference, and evolve knowledge through continuous feedback loops.
Unlike static databases, ƒ(xyz) knowledge graphs are self-regulating networks where both humans and AI agents collaboratively curate truth.