Taxonomy Distribution Report

Overview

• Total Concepts: 200
• Number of Taxonomies: 12
• Average Concepts per Taxonomy: 16.7

Distribution Summary

Category	TaxonomyID	Count	Percentage	Status
GRAPH	GRAPH	42	21.0%	✅
QUERY	QUERY	26	13.0%	✅
Foundation Concepts - Prerequisites	FOUND	25	12.5%	✅
ALGO	ALGO	17	8.5%	✅
SUPPLY	SUPPLY	16	8.0%	✅
PERF	PERF	15	7.5%	✅
SOCIAL	SOCIAL	15	7.5%	✅
PATTERN	PATTERN	15	7.5%	✅
KNOW	KNOW	10	5.0%	✅
Advanced Topics	ADV	10	5.0%	✅
FIN	FIN	5	2.5%	ℹ️ Under
HEALTH	HEALTH	4	2.0%	ℹ️ Under

Visual Distribution

GRAPH  ██████████  42 ( 21.0%)
QUERY  ██████  26 ( 13.0%)
FOUND  ██████  25 ( 12.5%)
ALGO   ████  17 (  8.5%)
SUPPLY ████  16 (  8.0%)
PERF   ███  15 (  7.5%)
SOCIAL ███  15 (  7.5%)
PATTERN ███  15 (  7.5%)
KNOW   ██  10 (  5.0%)
ADV    ██  10 (  5.0%)
FIN    █   5 (  2.5%)
HEALTH █   4 (  2.0%)

Balance Analysis

✅ No Over-Represented Categories

All categories are under the 30% threshold. Good balance!

ℹ️ Under-Represented Categories (<3%)

• FIN (FIN): 5 concepts (2.5%)
• Note: Small categories are acceptable for specialized topics
• HEALTH (HEALTH): 4 concepts (2.0%)
• Note: Small categories are acceptable for specialized topics

Category Details

GRAPH (GRAPH)

Count: 42 concepts (21.0%)

Concepts:

• 1. Labeled Property Graph
• 1. Nodes
• 1. Edges
• 1. Properties
• 1. Labels
• 1. Schema-Optional Modeling
• 1. Schema-Enforced Modeling
• 1. Index-Free Adjacency
• 1. Traversal
• 1. Graph Query
• 1. Pattern Matching
• 1. Multi-Hop Queries
• 1. Aggregation
• 1. Path Patterns
• 1. Constant-Time Neighbor Access
• ...and 27 more

QUERY (QUERY)

Count: 26 concepts (13.0%)

Concepts:

• 1. OpenCypher
• 1. GSQL
• 1. Statistical Query Tuning
• 1. GQL
• 1. Cypher Syntax
• 1. Match Clause
• 1. Where Clause
• 1. Return Clause
• 1. Create Statement
• 1. Merge Statement
• 1. Delete Statement
• 1. Set Clause
• 1. Graph Patterns
• 1. Variable Length Paths
• 1. Shortest Path
• ...and 11 more

Foundation Concepts - Prerequisites (FOUND)

Count: 25 concepts (12.5%)

Concepts:

• 1. Data Modeling
• 1. World Models
• 1. Knowledge Representation
• 1. RDBMS
• 1. OLAP
• 1. OLTP
• 1. NoSQL Databases
• 1. Key-Value Stores
• 1. Document Databases
• 1. Wide-Column Stores
• 1. Graph Databases
• 1. CAP Theorem
• 1. Tradeoff Analysis
• 1. Schema Design
• 1. Hash Maps
• ...and 10 more

ALGO (ALGO)

Count: 17 concepts (8.5%)

Concepts:

• 1. Breadth-First Search
• 1. Depth-First Search
• 1. A-Star Algorithm
• 1. Pathfinding
• 1. Traveling Salesman Problem
• 1. PageRank
• 1. Community Detection
• 1. Centrality Measures
• 1. Betweenness Centrality
• 1. Closeness Centrality
• 1. Graph Embeddings
• 1. Graph Neural Networks
• 1. Link Prediction
• 1. Graph Clustering
• 1. Connected Components
• ...and 2 more

SUPPLY (SUPPLY)

Count: 16 concepts (8.0%)

Concepts:

• 1. Web Storefront Models
• 1. Product Catalogs
• 1. Recommendation Engines
• 1. Bill of Materials
• 1. Complex Parts
• 1. Supply Chain Modeling
• 1. IT Asset Management
• 1. Dependency Graphs
• 1. Network Topology
• 1. Configuration Management
• 1. Impact Analysis
• 1. Root Cause Analysis
• 1. Regulatory Compliance
• 1. Data Lineage
• 1. Master Data Management
• ...and 1 more

PERF (PERF)

Count: 15 concepts (7.5%)

Concepts:

• 1. Hop Count
• 1. Indegree
• 1. Outdegree
• 1. Graph Indexes
• 1. Vector Indexes
• 1. Full-Text Search
• 1. Composite Indexes
• 1. Graph Metrics
• 1. Performance Benchmarking
• 1. Synthetic Benchmarks
• 1. LDBC SNB Benchmark
• 1. Graph 500
• 1. Query Cost Analysis
• 1. Join Operations
• 1. Scalability

SOCIAL (SOCIAL)

Count: 15 concepts (7.5%)

Concepts:

• 1. Social Networks
• 1. Friend Graphs
• 1. Influence Graphs
• 1. Follower Networks
• 1. Activity Streams
• 1. User Profiles
• 1. Relationship Types
• 1. Sentiment Analysis
• 1. Natural Language Processing
• 1. Fake Account Detection
• 1. Human Resources Modeling
• 1. Org Chart Models
• 1. Skill Management
• 1. Task Assignment
• 1. Backlog Management

PATTERN (PATTERN)

Count: 15 concepts (7.5%)

Concepts:

• 1. Subgraphs
• 1. Anti-Patterns
• 1. Time-Based Modeling
• 1. IoT Event Modeling
• 1. Bitemporal Models
• 1. Graph Quality Metrics
• 1. Model Validation
• 1. Schema Evolution
• 1. Data Migration
• 1. ETL Pipelines
• 1. CSV Import
• 1. JSON Import
• 1. Data Loading
• 1. Bulk Loading
• 1. Incremental Loading

KNOW (KNOW)

Count: 10 concepts (5.0%)

Concepts:

• 1. Concept Dependency Graphs
• 1. Curriculum Graphs
• 1. Ontologies
• 1. SKOS
• 1. Acronym Lists
• 1. Glossaries
• 1. Controlled Vocabularies
• 1. Taxonomies
• 1. Note-Taking Systems
• 1. Action Item Extraction

Advanced Topics (ADV)

Count: 10 concepts (5.0%)

Concepts:

• 1. Distributed Graph Databases
• 1. Graph Partitioning
• 1. Sharding Strategies
• 1. Replication
• 1. Consistency Models
• 1. Graph Visualization
• 1. Interactive Queries
• 1. Real-Time Analytics
• 1. Batch Processing
• 1. Capstone Project Design

FIN (FIN)

Count: 5 concepts (2.5%)

Concepts:

• 1. Financial Transactions
• 1. Fraud Detection
• 1. Anti-Money Laundering
• 1. Know Your Customer
• 1. Account Networks

HEALTH (HEALTH)

Count: 4 concepts (2.0%)

Concepts:

• 1. Healthcare Graphs
• 1. Provider-Patient Graphs
• 1. Electronic Health Records
• 1. Clinical Pathways

Recommendations

• ✅ Good balance: Categories are reasonably distributed (spread: 19.0%)
• ✅ MISC category minimal: Good categorization specificity

Educational Use Recommendations

• Use taxonomy categories for color-coding in graph visualizations
• Design curriculum modules based on taxonomy groupings
• Create filtered views for focused learning paths
• Use categories for assessment organization
• Enable navigation by topic area in interactive tools

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Report generated by learning-graph-reports/taxonomy_distribution.py