Data Science Foundations. Geometry and Topology of Complex Hiera...

This book describes solid and supportive foundations for the data science of our times, with many illustrative cases. Core to these foundations are mathematics and computational science. Our thinking and decision-making in regard to data can follow the insightful observation by the physicist Paul Dirac that physical theory and physical meaning have to follow behind the mathematics (see Section 4.7). The hierarchical nature of complex reality is part and parcel of this mathematically well-founded way of observing and interacting with physical, social and all realities. Quite wide-ranging case studies are used in this book. The text, however, is written in an accessible and easily grasped way, for a reader who is knowledgeable and engaged, without necessarily being an expert in all matters. Ultimately this book seeks to inspire, motivate and orientate our human thinking and acting regarding data, associated information and derived knowledge. This book seeks to give the reader a good start towards practical and meaningful perspectives. Also, by seeking to chart out future perspectives, this book responds to current needs in a way that is unlike other books of some relevance to this eld, and that may be great in their own specialisms.