Mark Asch: “A Toolbox for Digital Twins: From Model-Based to Data-Driven”

Digital twins have recently become very popular in various application fields, including engineering, medicine, economy, and Earth science.They combine computational models with data from an individual physical object or system in order to make predictions and improve decision-making.The book A Toolbox for Digital Twins: From Model-Based to Data-Driven by Mark Asch provides an extensive overview of the mathematical methods used in digital twins.The interplay of mathematical models and available data is central to digital twins in general and therefore to the book in particular.Some of the major challenges addressed in the book are: How to find a suitable trade-off between the complexity and the efficiency of mathematical models? How to extract relevant information from the available data? How to combine the available data and mathematical models so that the digital twin can use the best of both to support decision-making?On purpose, the book does not provide plug-and-play digital twins which may be used right away and do not require expert knowledge of the user.It is argued that such digital twins are typically based on coupled ordinary differential equations which are too simple and lack important features such as dynamic self-updating based on measured data.Instead, the reader is provided with a basic understanding of the most important tools to be able to use them in a concrete application context.Nevertheless, the book includes many examples with source code, which are summarized in a toolbox available on the author's GitHub account.In addition, there are many references to