Graph Data Modeling - Table of Contents
Chapter 1: Introduction to Graph Data Modeling
What is a Graph Data Model?
Why is Graph Data Modeling Important?
The Knowledge Triangle
Models and Algorithms
Case Study: Page Rank
Chapter 2: Graph Data Modeling Concepts
Nodes and Edges
Properties
Property Data Types
Simple Types
Complex Types
Paths
Dependencies
Modeling Customers
Defining Customer
Customers as Individuals
Customers as Companies
Customers as Organizations
Example: Selling to schools, governments and social networks
Modeling Products
Modeling Space
Modeling Time
The DateTime Structure
Time Trees
Years
Months
Days
Hours
Minutes
Seconds
Milliseconds
Financial Time
Exceptions
Daylight Savings Time
Modeling Concepts
Knowledge Graphs
SKOS
Business Glossaries
Taxonomies
Ontologies
The Concept Node
Labels
Broader and Narrower Concepts
Schemas
Modeling Language
Modeling Words
Modeling Sentences
Modeling Paragraphs
Modeling Documents
Document Processing Pipelines
Case Study: WordNet
Synonyms
Opposites
Modeling Fraud
Anti-Money Laundering
Finding Unusual Relationships
Modeling Healthcare
Modeling Patients
Modeling the Spread of Infectious Disease
Modeling Healthcare Costs
Modeling Value-Based Care
Entity Resolution
The Challenges of Connecting Data
Modeling Scenes
The Scene Graph
Modeling Business Rules
Decision Trees
Validation Rules
Modeling Security Threats
Modeling Business Processes
Modeling Events
Event Mining
Modeling Learning
Learning Graphs
Modeling Causality
Causal Graphs
Systems Thinking
Causality and Data Flows
Data Governance
Data Stewards
Domains
Data Matching
Schema Matching
Data Mapping
Model Evolution
What New Areas Should You Model?
The Edge of Chaos
The Economics Benefits of Model Complexity
Reference Frames
Architecture of the Human Brain
The Monty Python Framework