This is a very good book! It’s a thought piece about a range of ideas that couples information across several disciplines and across large timeframes. As the title suggests, it’s illustrations range from the big bang to big data. It’s not a textbook, though it would be good reading for students in data-driven graduate programs. It’s not a discussion of databases or data structures; it is a discussion of the dynamic relationship between the information society and the storage, retrieval, dissemination, and usage of information.

Schuster is the editor of this 11-chapter book, and each chapter is written by one or more of 16 established authors from universities across Europe, the US, and Japan. The authors’ subject areas include mathematics, medicine, engineering, linguistics, philosophy, sociology, education and pedagogy, data analytics, and political science. This mix makes the book most interesting.

The book is presented in six parts, including an introduction. The remaining five are “The World of Large and Small Systems,” “The World of Living Things,” “The World of Intelligent Machines and Finiteness,” “The World of Networks, Clouds, and Big Data Processing,” and “The World of Society and Philosophy.” Each chapter addresses an interesting and lively discipline example. Each chapter includes a discussion of data acquisition, storage management, and analysis where appropriate.

To give the reader a sense of the book’s breadth, the chapters discuss the following areas:

• “Expanding Beyond the Solar System”: discusses the detection of extrasolar planets;
• “Information in Quantum Theory”: considers quantum computation, teleportation, and cryptology;
• “The Potential of Plants and Seeds in DNA-based Information Storage”: discusses DNA basics, plant material, DNA synthesis and cloning, and coding such;
• “Memory Processing in the Nervous System”: covers neuroscience and memory;
• “From Computing Machines to Learning Intelligent Machines”: presents a chronological development of Turing’s thoughts;
• “Finite Information Agency”: includes mathematical modeling and a set of scenarios for finite information spaces;
• “Distributed and Connected Information in the Internet”: contains a broad discussion of “Internet” data, linked data, text data, social data, and so on;
• “Custom Hardware Versus Cloud Computing in Big Data”: presents a broad discussion of high-performance computing solutions and applications, such as genomics, digital pathology, surveillance, and the Internet of Things (IoT), among others;
• “Information Overload in a Data-Intensive World”: discusses this topic, as well as alleviating its “symptoms”; and
• “Causal/Informational Theories of Mental Content”: discusses information-based theories, including Wisconsin semantics, Dretske’s response, and Fodor’s asymmetrical causal dependency of meaning.

Each chapter has an extensive and good-quality bibliography. A quick citation search of the references suggests that the resources are well cited. This is a well-written book. The depth in several of the chapters requires some background in mathematics, physics, and medicine. It’s not a quick read--the level of detail slows the reader--but it is an enriching read. The cross-disciplinary approach makes it very interesting.