Data Science Foundations: Geometry and Topology of Complex Hierarchic Systems and Big Data Analytics

Fionn Murtagh

September 7, 2017 by Chapman and Hall/CRC
Reference - 206 Pages - 55 B/W Illustrations
ISBN 9781498763936 - CAT# K28995
Series: Chapman & Hall/CRC Computer Science & Data Analysis


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    • Takes an approach based on the geometry and topology of complex hierarchic systems.
    • Provides a good balance of rigour, mathematics, and computational thinking.
    • Features case studies from various fields, including social media, psychoanalysis, and cosmology.
    • Data sets and software code, mostly in R, can be downloaded from the book website:



"Data Science Foundations is most welcome and, indeed, a piece of literature that the field is very much in need of…quite different from most data analytics texts which largely ignore foundational concepts and simply present a cookbook of methods…a very useful text and I would certainly use it in my teaching."
- Mark Girolami, Warwick University

Data Science encompasses the traditional disciplines of mathematics, statistics, data analysis, machine learning, and pattern recognition. This book is designed to provide a new framework for Data Science, based on a solid foundation in mathematics and computational science. It is written in an accessible style, for readers who are engaged with the subject but not necessarily experts in all aspects. It includes a wide range of case studies from diverse fields, and seeks to inspire and motivate the reader with respect to data, associated information, and derived knowledge.