Digital Twins for Software Engineers

Part I — The Big Picture

• Chapter 1 -- Why Anyone Pays for a Digital Twin: Value, Markets, and Real Deployments (pdf)
• Chapter 2 -- Twin, Shadow, Model, Simulation: What a Digital Twin Actually Is -- and Isn't (pdf)
• Chapter 3 -- The Anatomy of a Twin: A Reference Architecture in Software Terms (pdf)

Part II — Modeling and Simulation Literacy

• Chapter 4 -- Just Enough Modelling: Physics-Based, Data-Driven, and Hybrid Models (pdf)
• Chapter 5 -- Just Enough Simulation: State, Time, Solvers, and Co-Simulation (pdf)
• Chapter 6 -- Simulators: How Each Kind of Model Gets Solved (pdf)
• Chapter 7 -- Should You Trust the Twin? Calibration, Credibility, and V&V (pdf)
• Chapter 8 -- Where AI Fits: Machine Learning as a Model, a Service, and a Risk (pdf)

Part III — Building the Twin

• Chapter 9 -- Connecting the Physical: Sensors, Protocols, and Streaming Data (pdf)
• Chapter 10 -- Data Engineering for Twins: Time Series, Context, and Provenance (pdf)
• Chapter 11 -- Twin Services: Visualization, Monitoring, Prediction, and Decision Support (pdf)
• Chapter 12 -- Platforms and Composability: Buying, Building, and Assembling from Parts (pdf)
• Chapter 13 -- Standards and Open Source: What Exists So You Don't Build It Twice (pdf)
• Chapter 14 -- Running Twins in Production: Deployment, Evolution, and the Twin's Own Lifecycle (pdf)
• Chapter 15 -- Twins at Scale: Ecosystems (pdf)