cognitive/docs/guides/ai_file_organization.md

AI-Oriented File Organization

---

title: AI File Organization Guide type: guide status: stable created: 2024-02-06 tags:

• organization
• structure
• ai
• metadata related:
• ai_documentation_style
• knowledge_organization
• machine_readability

---

Overview

This guide defines the file organization structure optimized for AI processing, knowledge graph construction, and intelligent navigation of the cognitive modeling system.

Directory Structure

Root Organization

cognitive_modeling/
├── docs/                    # Documentation root
│   ├── concepts/           # Core concepts
│   │   ├── atomic/        # Fundamental concepts
│   │   ├── composite/     # Combined concepts
│   │   └── meta/         # Meta-concepts
│   │
│   ├── implementations/   # Implementation details
│   │   ├── core/         # Core implementations
│   │   ├── extensions/   # Extended features
│   │   └── integrations/ # System integrations
│   │
│   ├── knowledge_base/   # Knowledge representation
│   │   ├── ontology/     # Domain ontologies
│   │   ├── graphs/       # Knowledge graphs
│   │   └── embeddings/   # Neural embeddings
│   │
│   ├── ml_artifacts/     # Machine learning artifacts
│   │   ├── models/       # Model specifications
│   │   ├── training/     # Training configurations
│   │   └── evaluation/   # Evaluation metrics
│   │
│   └── validation/       # Validation framework
│       ├── tests/        # Test specifications
│       ├── metrics/      # Quality metrics
│       └── reports/      # Validation reports

File Naming Conventions

Pattern Specifications

file_patterns = {
    'concepts': {
        'pattern': '{category}_{name}_{version}.md',
        'example': 'belief_updating_v1.md'
    },
    'implementations': {
        'pattern': 'impl_{system}_{component}_{version}.md',
        'example': 'impl_inference_engine_v2.md'
    },
    'knowledge': {
        'pattern': 'kb_{domain}_{concept}_{type}.md',
        'example': 'kb_cognitive_belief_ontology.md'
    },
    'ml': {
        'pattern': 'ml_{task}_{model}_{version}.md',
        'example': 'ml_classification_transformer_v1.md'
    }
}

Metadata Structure

file_metadata:
  naming:
    prefix: string        # Category prefix
    body: string         # Main identifier
    version: string      # Version identifier
    extension: string    # File extension
  processing:
    priority: integer    # Processing priority
    dependencies: list   # File dependencies
    validation: string   # Validation requirements

Directory Metadata

Directory Configuration

directory_config:
  concepts:
    index_required: true
    graph_required: true
    validation_required: true
  implementations:
    index_required: true
    tests_required: true
    documentation_required: true
  knowledge_base:
    ontology_required: true
    embeddings_required: true
    graph_required: true

Processing Instructions

processing_config:
  parallel_processing: boolean
  dependency_checking: string
  validation_level: string
  caching_strategy: string

Knowledge Organization

Concept Hierarchy

graph TD
    A[Root Concepts] --> B[Atomic Concepts]
    A --> C[Composite Concepts]
    B --> D[Properties]
    B --> E[Relations]
    C --> F[Patterns]
    C --> G[Systems]

Implementation Structure

graph LR
    A[Core] --> B[Components]
    B --> C[Interfaces]
    B --> D[Implementations]
    D --> E[Extensions]
    D --> F[Integrations]

File Templates

Concept File Template

# Concept: {name}

#BEGIN_METADATA
version: string
category: string
complexity: string
#END_METADATA

#BEGIN_CONTENT
content: string
#END_CONTENT

#BEGIN_VALIDATION
validation: object
#END_VALIDATION

Implementation File Template

# Implementation: {name}

#BEGIN_METADATA
version: string
system: string
component: string
#END_METADATA

#BEGIN_SPECIFICATION
specification: object
#END_SPECIFICATION

#BEGIN_VALIDATION
validation: object
#END_VALIDATION

Validation Rules

Directory Validation

# @directory_validation
{
    "required_files": ["index.md", "README.md"],
    "required_metadata": ["version", "status"],
    "required_structures": ["graph", "validation"]
}

File Validation

# @file_validation
{
    "naming_convention": bool,
    "metadata_complete": bool,
    "content_valid": bool,
    "links_valid": bool
}

Integration Guidelines

Knowledge Graph Integration

# @graph_integration
def integrate_knowledge():
    """
    Integration steps:
    1. Parse directory structure
    2. Extract metadata
    3. Build relationships
    4. Validate graph
    """
    pass

Machine Learning Pipeline

# @ml_pipeline
def process_documentation():
    """
    Processing steps:
    1. Extract features
    2. Generate embeddings
    3. Train models
    4. Validate results
    """
    pass

Best Practices

Organization Principles

1. Hierarchical Clarity

   • Clear parent-child relationships
   • Logical grouping of related content
   • Consistent depth levels

2. Metadata Management

   • Complete metadata at all levels
   • Consistent metadata schema
   • Regular validation

3. Processing Optimization

   • Efficient file access patterns
   • Optimized for parallel processing
   • Caching-friendly structure

Related Documentation

• ai_documentation_style
• knowledge_graph_structure
• validation_framework
• ml_integration_guide

References

• file_organization_patterns
• metadata_standards
• processing_optimization
• validation_methods