Domain Map of Content (MOC) Hub

Template Overview

As a personal Markdown vault grows to thousands of notes, hierarchical folders become brittle. Maps of Content (MOCs) act as dynamic intellectual workbenches, assembling related atomic permanent notes, literature summaries, and project records into clear navigational panoramas. The Domain Map of Content Hub template provides a robust architecture for organizing major fields of study.

Markdown Template Structure

Copy the block below or click Download .md File to add this template directly to your personal vault:

---
title: "MOC: [Domain Name / Major Field of Inquiry]"
date: [YYYY-MM-DD]
moc_type: "Top-Level Domain Map of Content"
curator: "[[Your Name]]"
status: "[Growing / Mature / Evergreen]"
tags: [pkm, moc, map-of-content, knowledge-graph, navigation]
---

# Map of Content: [Domain Name]

> "Maps of Content provide higher-order perspective without imposing rigid folder constraints on your emergent thinking."

## 1. Domain Overview & Foundational Principles
A concise structural overview of this domain, its core intellectual questions, and foundational theoretical frameworks:
- **Core Question:** What are the fundamental constraints and architectural frontiers of this domain?
- **Key Tenet:** Summary of the central organizing thesis.

## 2. Navigational Topic Clusters & Core Sub-Domains
Organize your atomic permanent notes into thematic sub-clusters:

### Cluster A: Foundational Architecture & Mechanics
- [[Permanent Note: Low-Latency Audio Streaming Pipeline]]
- [[Permanent Note: CoreAudio Hardware Abstraction Layer]]
- [[Permanent Note: Lock-Free Atomic Queues on Darwin]]

### Cluster B: Privacy Engineering & Legal Frameworks
- [[Permanent Note: Local Compute Eliminates Third-Party Telemetry]]
- [[Permanent Note: Attorney-Client Privilege in Digital Notetaking]]
- [[Permanent Note: Subpoena Resistance of Sovereign Filesystems]]

### Cluster C: Applied Machine Learning & Neural Acceleration
- [[Permanent Note: Apple Neural Engine Quantization Profiles]]
- [[Permanent Note: Real-Time Factor Benchmarks on M3 Silicon]]

## 3. Active Projects & Applied Research Initiatives
Current active inquiries utilizing notes from this domain:
- [[Project PRD: Zero-Downtime SQLite FTS5 Indexing Migration]]
- [[Manuscript: Peer-Reviewed Systems Paper on Local DSP]]

## 4. Literature & Source Bibliographies
- [[Literature Note: Luhmann's Zettelkasten Communicating with Slip-Boxes]]
- [[Literature Note: Shannon's Mathematical Theory of Communication]]

Filled Real-World Example

Here is a realistic example demonstrating how this template captures actual deliberations:

---
title: "MOC: Sovereign Computing & Local-First Systems"
date: 2026-10-10
moc_type: "Domain MOC"
curator: "[[Julian Thorne]]"
status: "Evergreen"
tags: [pkm, moc, map-of-content, knowledge-graph, navigation]
---

# Map of Content: Sovereign Computing

## 1. Organizing Thesis
Sovereign computing asserts that software should respect human dignity by executing entirely on user-controlled hardware without involuntary telemetry or cloud lock-in.

## 2. Core Note Clusters
- **Filesystem Durability:** [[APFS Extended Attributes]], [[Plain Text Longevity]].
- **Speech Recognition:** [[Whisper Core ML Compilation]], [[Apple Neural Engine Throughput]].
- **Legal Compliance:** [[GDPR Article 25 by Design]].

When to Use and When to Avoid

When to Use

• Use as top-level index hubs for major areas of study, professional domains, or book research.
• Use when you have accumulated 15+ related atomic notes that need structural synthesis.
• Use to navigate your knowledge vault visually using graph view and backlinks.

When to Avoid

• Avoid creating MOCs before you have written actual notes (let structure emerge naturally).
• Avoid for simple daily task lists.

On-Device AI Integration

Summarize your recording in Oyma with this local instruction:

Analyze the notes and themes in your knowledge vault:
1. Identify natural thematic clusters among existing atomic notes.
2. Generate an organized Map of Content (MOC) structure with categorized [[WikiLinks]].
3. Formulate foundational domain questions and suggest missing conceptual bridges.
Output in clean, structured Markdown.

Your data remains securely on your Mac with zero cloud exposure.