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Reality Mining: Using Big Data to Engineer a Better World

Nathan Eagle and Kate Greene
Publisher: 
MIT Press
Publication Date: 
2014
Number of Pages: 
199
Format: 
Hardcover
Price: 
24.95
ISBN: 
9780262027687
Category: 
General
[Reviewed by
Tom Sinclair
, on
11/6/2014
]

The idea behind data mining goes back to the 1960s. At that time, it was considered useless to search through datasets looking for patterns without formulating an initial hypothesis. The practice came into its own in the late ‘80s and early ‘90s when companies like retail giant Wal-Mart used their customer and sales data to make strategic business decisions.

Data science is a booming business these days. The scramble for competitive advantage has advanced the state of tools and techniques but there is legitimate concern that ethics has become an after-thought.

The dark side of data mining dominates the news these days. There’s even a prime-time TV series where data mining leads to a dystopian surveillance state. Reality Mining reminds us that new technology can also have far-reaching positive social benefit, though the dark side gets better ratings.

From the introduction:

The goal of this book, then, is to explore the positive potential of Big Data — specifically, to show how Reality Mining can be used to engineer better social systems.

The authors begin at the scale of the single individual and move up through neighborhoods/organizations, cities, countries and finally the world to show the benefits of data analysis at each level of resolution. This is similar to the documentary Powers of Ten, which the authors reference in the introduction. The book is very readable, with plenty of guidance on ethical data collection, tools and techniques as well as dealing with privacy issues at each level.

This would make an excellent reference for a graduate data mining course but you could certainly design a course with this book as the primary source as well. The writing is brisk and very readable and the authors manage to avoid the dry language and phrasing of most texts on this topic.


Tom Sinclair has a B.S./M.S. in Mathematics and Computer Science from Loyola University of Chicago and has over twenty years’ experience in the technology industry and higher education. He is the author of a Linux networking textbook and is a freelance writer and I.T. consultant. In addition, he teaches undergraduate math and blogs about math education at http://wehatemath.wordpress.com.

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