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Networks are all around us. Our brain is a network of cells, and cells themselves are networks of molecules. Societies are networks of people, and on a larger scale, food webs and ecosystems are networks of species. Networks are not just prevalent in nature but also in many manmade structures, like power grids, transportation systems, and the Internet. Network diagrams are generally made of two types of elements, nodes and connections. A node is an individual element and connections show relationships between the nodes. Visualizations help us to understand different types of networks, and the visualization of information can go well beyond the common bar chart or pie chart. In October 2005, Manuel Lima, an interaction designer and researcher, founded VisualComplexity.com, a comprehensive repository of complex network visualizations. From an initial collection of roughly 80 projects, the website quickly grew to encompass over 700 projects, with a goal to facilitate a critical understanding of a spectrum of network visualization methods. The assortment of projects -- often referred to as "map of maps" -- in this area is astounding. From representing networks of friends on Facebook or Twitter, to depicting interactions amongst proteins in a human cell, the target is truly diversified. There are visualizations mapping the ties between students, researchers, authors, politicians, developers, musicians, and terrorists; or charting the links amongst companies, institutions, web servers, web pages, blogs, emails, neurons, cities, and words. Some require hours of rendering and complex algorithms to produce, others are simply drawn by hand or using a specific drawing software. Never before we felt so strongly the notion of living in a highly interdependent world, where everything appears to be connected to everything else. This book is much more than a mere physical reproduction of VisualComplexity.com. In the tradition of Edward Tufte, Lima analyzes, collects, and presents some of the most interesting examples of information graphics in a single volume, focusing on the long tradition of mapping complex networks. The largest part of the book is a visually rich showcase of some of the most compelling contemporary examples, as well as an analysis of the range of future prospects (as discussed by leading figures in network sciences, including Christopher Kirwan, Fabien Girardin, Nathan Yau, Andrew Vande Moere, JoAnn Kuchera-Morin, Eric Rodenbeck, David McConville).