Unified Knowledge Graph

Project Summary

A system to capture, map, and visualize the structural connections between all domains of learning and life. The core thesis: all domains share fundamental patterns — formal grammars, wave mechanics, graph theory, boolean logic, feedback loops — and mapping these connections accelerates learning by enabling transfer.

The system builds on three existing platforms: the association engine (379 keys, 602+ edges), the competency domains (13 domains with microskills), and the codex (37 categories). What’s missing is timestamped competency snapshots, cross-domain transfer edges with dates, and a visualization layer that renders the graph and growth trajectory over time.

Domains (Initial)

Domain Surface Structural Pattern

Mathematics

Algebra, logarithms, set theory, percentages

Abstract structures, proofs, logical deduction

Music

Violin, scales, resonance, sympathetic vibration

Wave mechanics, harmonic series, logarithmic ratios

Language

Spanish, syntax, morphology, rhetoric, persuasion

Formal grammars, compositional semantics

Computer Science

Unix, networking, programming, C, syscalls

Formal grammars, state machines, graph traversal

Physics

RF communication, wave propagation, electromagnetism

Wave mechanics, frequency coupling, standing waves

Literature & Philosophy

Don Quijote, rhetoric, ethics, humility

Narrative structure, logical argumentation, epistemology

Health

Exercise, diet, energy, meditation, sleep

Feedback loops, homeostasis, systems regulation

Security

802.1X, ISE policy, cryptography, OWASP

Trust models, formal verification, access control (set theory)

Infrastructure

Networking, Linux, automation, deployment

State machines, idempotency, convergence

Connecting Structures

The visualization system will map these recurring structures across domains:

  • Formal grammars — Chomsky hierarchy governs both awk pattern syntax and Spanish verb conjugation

  • Wave mechanics — violin string resonance, RF propagation, and STP convergence are all standing wave phenomena

  • Boolean logic — find predicates, ISE authorization rules, and rhetorical syllogisms share the same compositional structure

  • Feedback loops — ctime inode updates, metabolic homeostasis, and musical ear training all rely on tight observation-correction cycles

  • Graph theory — association engine edges, network topologies, and knowledge dependency graphs are the same mathematical object

  • Logarithmic scales — musical intervals (octave = 2:1), decibel measurement, and human perception all operate logarithmically

Status

Component Description Status Notes

Phase 0: Data Model

Define competency snapshot schema, transfer edge format, domain taxonomy

🟡 In progress

Initial capture

Phase 1: Collection

Timestamped competency snapshots, cross-domain edge capture

❌ Not started

Needs snapshot schema

Phase 2: Storage

Extend association engine YAML or new data store

❌ Not started

Evaluate: YAML vs SQLite vs JSON

Phase 3: Visualization

matplotlib/Python graphs — growth curves, transfer maps, domain heat maps

❌ Not started

Core deliverable

Phase 4: Camps

Structured intensive learning periods with pre/post snapshots

❌ Not started

Depends on Phase 1-3

Phase 5: Cross-Study

Automated transfer edge detection from codex, worklogs, git history

❌ Not started

Advanced — mine existing data
Field Value

PRJ ID

PRJ-2026-05-unified-knowledge-graph

Author

Evan Rosado

Created

2026-05-27

Updated

2026-05-27

Status

Draft

Category

Personal / Learning Analytics

Priority

P1