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Visual Complexity: Mapping Patterns of Information
Our ability to generate information now far exceeds our capacity to understand it. Finding patterns and making meaningful connections inside complex data networks has emerged as one of the biggest challenges of the twenty-first century. In recent years, designers, researchers, and scientists have begun employing an innovative mix of colors, symbols, graphics, algorithms, and interactivity to clarify, and often beautify, the clutter. From representing networks of friends on Facebook to depicting interactions among proteins in a human cell, Visual Complexity presents one hundred of the most interesting examples of information-visualization by the field's leading practitioners.
272 pages, Hardcover
First published July 19, 2011
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1,416 people want to read
About the author
Manuel Lima
14Ìýbooks63ÌýfollowersA Fellow of the Royal Society of Arts and nominated by Creativity magazine as “one of the 50 most creative and influential minds of 2009,â€� Manuel Lima is the founder of VisualComplexity.com, Design Lead at Google, and a regular teacher of data visualization at Parsons School of Design.
Manuel is a leading voice on information visualization and has spoken at numerous conferences, universities, and festivals around the world, including TED, Lift, OFFF, Eyeo, Ars Electronica, IxDA Interaction, Harvard, Yale, MIT, the Royal College of Art, NYU Tisch School of the Arts, ENSAD Paris, the University of Amsterdam, and MediaLab-Prado Madrid. He has also been featured in various magazines and newspapers, such as Wired, the New York Times, Science, Nature, Businessweek, Creative Review, Fast Company, Forbes, Grafik, SEED, étapes, and El PaÃs.
His first book, Visual Complexity: Mapping Patterns of Information, has been translated into French, Chinese, and Japanese. His second, The Book of Trees: Visualizing Branches of Knowledge, covers eight hundred years of human culture through the lens of the tree figure, from its entrenched roots in religious medieval exegesis to its contemporary, secular digital themes.
With more than twelve years of experience designing digital products, Manuel has worked for Codecademy, Microsoft, Nokia, R/GA, and Kontrapunkt. He holds a BFA in Industrial Design and a MFA in Design & Technology from Parsons School of Design. During the course of his MFA program, Manuel worked for Siemens Corporate Research Center, the American Museum of Moving Image, and Parsons Institute for Information Mapping in research projects for the National Geospatial-Intelligence Agency.
Manuel is a leading voice on information visualization and has spoken at numerous conferences, universities, and festivals around the world, including TED, Lift, OFFF, Eyeo, Ars Electronica, IxDA Interaction, Harvard, Yale, MIT, the Royal College of Art, NYU Tisch School of the Arts, ENSAD Paris, the University of Amsterdam, and MediaLab-Prado Madrid. He has also been featured in various magazines and newspapers, such as Wired, the New York Times, Science, Nature, Businessweek, Creative Review, Fast Company, Forbes, Grafik, SEED, étapes, and El PaÃs.
His first book, Visual Complexity: Mapping Patterns of Information, has been translated into French, Chinese, and Japanese. His second, The Book of Trees: Visualizing Branches of Knowledge, covers eight hundred years of human culture through the lens of the tree figure, from its entrenched roots in religious medieval exegesis to its contemporary, secular digital themes.
With more than twelve years of experience designing digital products, Manuel has worked for Codecademy, Microsoft, Nokia, R/GA, and Kontrapunkt. He holds a BFA in Industrial Design and a MFA in Design & Technology from Parsons School of Design. During the course of his MFA program, Manuel worked for Siemens Corporate Research Center, the American Museum of Moving Image, and Parsons Institute for Information Mapping in research projects for the National Geospatial-Intelligence Agency.
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Displaying 1 - 27 of 27 reviews
December 5, 2013
The subtitle of this book should be - Visualization done wrong. This book seems to be all about dumping raw data into one frame and hope to wow readers. The result, giant hairball with no discernible pattern - fail. Miniscule, unreadable and overlapping labels - fail. No legend, no description of what visual elements like color, size, weight is encoding - fail. There are over a hundred graph show cased. Most graph, often unreadable hairball, occupying a full page. It is accompany by a description of about one to three sentences. In most case I cannot figure out from the minimal description what is the underlying data they are trying to depict. Compare this to O'Reilly's Beautiful Visualization, which use an entire chapter for each topic. Not only do they have the final visualization, there are a lot of explanation on the data and quite importantly, the process used to make sense of the data. This book has pretty much nothing but colorful graphs.
The are several dozen of visualization around the theme of social network. After glancing at all these pictures, I cannot say I have garner any insight at all. Out of the entire book there might be a dozen graph I considered useful.
So my conclusion - this is visualization done wrong.
The are several dozen of visualization around the theme of social network. After glancing at all these pictures, I cannot say I have garner any insight at all. Out of the entire book there might be a dozen graph I considered useful.
So my conclusion - this is visualization done wrong.
August 4, 2012
I hate to down-rate this book, because it is very well researched and well written, but I just wasn't able to be as excited about this as I have been with Edward Tufte's books, to which this one is compared by one of the blurb writers. Part of the problem is that this book deals solely with visual representations of networks - an interesting genre, I'm sure, but one that stands more in the realm or art than science unless you drill down pretty far into the details of the network analysis and the techniques used to produce the visualization.
Lima does at one point present a 'syntax' of network representations - interesting, I suppose, but presented too superficially to be of actual use to the would-be practitioner.
By the latter part of the book I was just flipping pages, eager to get to the end, hoping to see something that would engage my attention. Didn't happen.
Update: after reading the other reviews of this book on goodreads, I want to add that, like them, I did not get any deeper knowledge or insight into the underlying data by looking at the visualizations. Contrast that with the graphics, and the approach to visualization, offered by Tufte, and you can understand my disappointment with this book. Tufte generally shows before and after representations of data, and has clear, consistent principles on which to evaluate or create a visualization. The foremost principle is that of conveying as much information as possible; aesthetics are important, but secondary, and artistic merit barely deserves consideration. But what are we to make of a network graph that allegedly represents millions of nodes and tens of millions of connections? Where is the information content? How does such a graph (represented visually) advance our understanding? I would claim that in nearly all cases, it does not.
Lima does at one point present a 'syntax' of network representations - interesting, I suppose, but presented too superficially to be of actual use to the would-be practitioner.
By the latter part of the book I was just flipping pages, eager to get to the end, hoping to see something that would engage my attention. Didn't happen.
Update: after reading the other reviews of this book on goodreads, I want to add that, like them, I did not get any deeper knowledge or insight into the underlying data by looking at the visualizations. Contrast that with the graphics, and the approach to visualization, offered by Tufte, and you can understand my disappointment with this book. Tufte generally shows before and after representations of data, and has clear, consistent principles on which to evaluate or create a visualization. The foremost principle is that of conveying as much information as possible; aesthetics are important, but secondary, and artistic merit barely deserves consideration. But what are we to make of a network graph that allegedly represents millions of nodes and tens of millions of connections? Where is the information content? How does such a graph (represented visually) advance our understanding? I would claim that in nearly all cases, it does not.
January 9, 2013
If you want a coffee table book on data visualization that is heavy on aesthetics and philosophical noodling, but light on practical value, then this book is for you. There are many pretty pictures, but most of them make no sense and offer little to no insight. It seems to have a good representation of the different types of visualizations that are popular but next to no advice on why one type is better than another type for any particular purpose. Personally I would prefer less flowery delivery and more analysis of why a Segmented Radial Convergence is more appropriate in certain cases than an Organic Rhizome or Centralized Burst. There is no such analysis anywhere in this book.
I picture this thing sitting conspicuously on the coffee table of half the dot-com infoviz nerds in San Francisco, next to their vaporizer and etsy coffee mug.
I picture this thing sitting conspicuously on the coffee table of half the dot-com infoviz nerds in San Francisco, next to their vaporizer and etsy coffee mug.
September 18, 2015
Great book making for a great read replete with beautiful pictures. In short, I want it for my own library. It was the ideal companion to the complexity studies I am currently engaged in. The history of the tree being used as a visualization technique in the history of knowledge and how it is being abandoned for the network visualization technique of the nodes and links model is very enlightening. It then goes into the ubiquitous nature of the interconnected network model. The book comes stocked with so many beautiful pictures of how information is being mapped and visualized and towards the end it leads to amazingly beautiful artistic renditions of modern artists. A great read and visualization tool for anyone interested in complexity and interconnected networks studies.
December 24, 2024
Good curation of graphs but wish he made more arguments with them. He doesn’t even reference/analyze a lot of the visuals included�
So close to being historical but not quite there—maybe it wouldve helped if his visual research extended a bit more beyond the maps from his own website
So close to being historical but not quite there—maybe it wouldve helped if his visual research extended a bit more beyond the maps from his own website
July 11, 2012
"Meeting the needs of global society does not require infinite economic growth but an understanding of and respect for the regenerative limits of the biosphere."
Manuel Lima is an ecological optimist, and he believes that collecting, connecting, presenting and integrating data is the key to human survival. He thinks we can overcome human selfishness and greed through visualization, through networkism--"the net has no center"--a complex open system that mimics natural processes, rather than the hierarchical organization we are used to employing to construct our world.
It's a beautiful idea, although I'm not as optimistic as he is.
I took this book out of the library for the visuals, which are amazing and often stunningly beautiful. And as sometimes happens with these things, I read a bit of the text, then more, and eventually all of it. Wide-ranging to say the least, starting with tree models and the history of mapping connections and ending with his outline for saving the world through artistry. In-between Lima covers such things as phrenology and the eerie similarity between Jackson Pollack's drip paintings and the growth of trees or neuron connections. He talks about our need to control and shape the endless stream of data that is our environment now, that defines who we are. Not just the information itself, but the time and space through which this information travels.
The illustrations are dazzling, and the author mentions "...the urge for creating visualizations that have more decorative than informative qualities." For me, that is a huge problem--I couldn't "read" or understand most of them as conveyers of knowledge. I realize that the systems they explain are interconnected and complex--that is easy to see. But it would be difficult for me to use them to either inform myself or make decisions based on what they say. It could be that they can only be interpreted by specialists, which is actually OK, but I would like to see attempts to portray some of these concepts in a way that reaches a larger audience.
Or maybe reading these new maps needs to be taught as a subject in school, so at least the next generation is fluent in the language they speak.
But back to my original reason for looking at Lima's book: wow! Even the archival tree-maps that he begins with are beautiful. By the time you reach the visualization of Lisbon's traffic or the chromosonal relationships within one genome you will be on sensory overload (in a good way). This is a keeper--a book to return to and also think about many times, in many ways.
And I hope his vision comes true.
Manuel Lima is an ecological optimist, and he believes that collecting, connecting, presenting and integrating data is the key to human survival. He thinks we can overcome human selfishness and greed through visualization, through networkism--"the net has no center"--a complex open system that mimics natural processes, rather than the hierarchical organization we are used to employing to construct our world.
It's a beautiful idea, although I'm not as optimistic as he is.
I took this book out of the library for the visuals, which are amazing and often stunningly beautiful. And as sometimes happens with these things, I read a bit of the text, then more, and eventually all of it. Wide-ranging to say the least, starting with tree models and the history of mapping connections and ending with his outline for saving the world through artistry. In-between Lima covers such things as phrenology and the eerie similarity between Jackson Pollack's drip paintings and the growth of trees or neuron connections. He talks about our need to control and shape the endless stream of data that is our environment now, that defines who we are. Not just the information itself, but the time and space through which this information travels.
The illustrations are dazzling, and the author mentions "...the urge for creating visualizations that have more decorative than informative qualities." For me, that is a huge problem--I couldn't "read" or understand most of them as conveyers of knowledge. I realize that the systems they explain are interconnected and complex--that is easy to see. But it would be difficult for me to use them to either inform myself or make decisions based on what they say. It could be that they can only be interpreted by specialists, which is actually OK, but I would like to see attempts to portray some of these concepts in a way that reaches a larger audience.
Or maybe reading these new maps needs to be taught as a subject in school, so at least the next generation is fluent in the language they speak.
But back to my original reason for looking at Lima's book: wow! Even the archival tree-maps that he begins with are beautiful. By the time you reach the visualization of Lisbon's traffic or the chromosonal relationships within one genome you will be on sensory overload (in a good way). This is a keeper--a book to return to and also think about many times, in many ways.
And I hope his vision comes true.
July 5, 2012
Lima is a passionate guide to visualization. He begins with a brief history of attempts to visualize complex information (many of them religious in nature) and moves into the computer age briskly, covering a number of essential concepts regarding data and Big Data, networking, and the internet. The strongest part of the book is the section cataloging the multiple forms that new visualizations take, with examples of each and lots of references that enable one to find the live versions online (an irony of this volume is that many of the best visualizations are interactive and can be viewed better via computer than on the page).
At the same time as I loved seeing these fabulous examples of how to move beyond the graph and pie chart, I often found myself entirely stupefied at what I was seeing and not really understanding whether or not I now knew something more as a result of having seen the data presented in a certain format. Sure, the images (such as this one by Chris Harrison visualizing biblical cross references: ) are somehow organically pleasing in the way that top grade micrographic images are (see, e.g., ), but do I glean great knowledge than I would have via close readings or careful scrutiny of data tables? My knee jerk reaction, as a fan of these visualizations is, "Of course I do," but I am actually hard put to demonstrate how that is the case.
At the same time as I loved seeing these fabulous examples of how to move beyond the graph and pie chart, I often found myself entirely stupefied at what I was seeing and not really understanding whether or not I now knew something more as a result of having seen the data presented in a certain format. Sure, the images (such as this one by Chris Harrison visualizing biblical cross references: ) are somehow organically pleasing in the way that top grade micrographic images are (see, e.g., ), but do I glean great knowledge than I would have via close readings or careful scrutiny of data tables? My knee jerk reaction, as a fan of these visualizations is, "Of course I do," but I am actually hard put to demonstrate how that is the case.
January 19, 2016
Excellent overview and research of the history and evolution of graph visualizations.
September 4, 2022
Loved a lot of the methods of organizing information throughout this book. I took a vast amount of notes on the strategies abd vocabulary used to help explain data visualization. Maual Lima, to me, has an elogant writing style and a clear understanding of explaining the subject matter and the hiatory behind it. My only gripes that kept this from being a 5* was the large amount of pictures that filled most of the book, which was not a huge issue as it seems thats what the point of this book. (An art book but in the form of data maps) but the main issue i had was the hyper optimistic attitude he has at the end about how data gathering could help save the world and change it for good. Yes, a lot of good can come from many things, but not everyone has similar goals. He proposes a lot of radical ideas about how to interweave data collection into our daily lives. Well we are getting there, and guess what? People are using it to make money and control those who arent aware of their biology being manipulated. Anyways, its still a good book, what i described is just the last few pages. Definitely check it out if you want to learn about the history and a brief introduction to data vusualization.
This entire review has been hidden because of spoilers.
September 22, 2018
The book starts off strong with a history of the tree as the leading metaphor for knowledge and classification. Lima then presents the development of complexity theory and the emerging metaphor of the network.
After this introduction, the rest of the book is driven by network visualizations. While there are plenty of meaningful and provocative examples, there's a surprising lack of explanation for these new forms of visual display. Many of the visualizations are very complex and not meant for printed reproduction (most are meant for digital display).
I finished the book feeling that I had studied the surface of something amazing, but didn't know that much more about its inner workings. Granted, since complexity theory and network visualizations are still so new, the book's drawbacks are understandable. This book is therefore still of great value to the field.
After this introduction, the rest of the book is driven by network visualizations. While there are plenty of meaningful and provocative examples, there's a surprising lack of explanation for these new forms of visual display. Many of the visualizations are very complex and not meant for printed reproduction (most are meant for digital display).
I finished the book feeling that I had studied the surface of something amazing, but didn't know that much more about its inner workings. Granted, since complexity theory and network visualizations are still so new, the book's drawbacks are understandable. This book is therefore still of great value to the field.
October 13, 2024
4,5 stars; excellent book on design with many inspiring, stunning examples, be sure to also check out; , , and .
August 13, 2017
Very nicely designed, glossy overview of network visualization approaches, as of a few years back. Insightful history and analysis as well as the pretty pictures. But, left me with the feeling that, with a few exceptions, plotting networks with more than a couple of dozen nodes is pointless, and that perhaps there are better ways of finding and providing insights from connectivity data. Very few of the images came with captions that said, "and thus, we learned an impactful fact", or "and thus, were minds changed." For non-network visualization, this sort of impact statement is very common. So perhaps this book should be read as a cautionary tale?
November 11, 2018
I really liked the book when I first browsed through it at a tech meetup: the reason why I ordered the book later.
However, after spending more time reading the book, I found that the vivid visualizations lack practical application that I was searching for - I would say wow, this graph looks very interesting, but then I would struggle in understanding the message behind most visualizations in the book.
However, after spending more time reading the book, I found that the vivid visualizations lack practical application that I was searching for - I would say wow, this graph looks very interesting, but then I would struggle in understanding the message behind most visualizations in the book.
August 16, 2020
A entertaining and instructive book. Has been compaired to Tufte's work which is partially true but less instructive. Lima illustrates the outlines of a new informational narrative but lets the reader draw their own conclusions on utility and functionality. I liked it and the examples were well chosen.
November 27, 2019
The complexity of information systems is fascinating but often difficult to comprehend. Lima's work describes the structure of information systems. Some of the graphics here are mind-boggling. This book acts as a fine companion or follow-up to Lima's similar work on "trees" and "circles."
December 5, 2017
A great history and analysis of very cool maps. Not just geographical maps.
July 31, 2019
Beautifully written and thoughtful Beautifully presented. But how do I use it?
November 23, 2022
Very well explained, great examples. A mandatory for infographics academic works/projects.
June 24, 2013
This is not an easy book to rate, given that it's partially a guide to understanding data visualization and partially an enthralling coffee-table-esque tome (that still needed to be carried to and from coffee shops so I could read it).
Lima writes in an engaging manner and his work in explicating what visualizations should do and are good for is well done. I could almost wish for a bit more text, actually, some of his thoughts and interpretations of the many visualizations within. Seeing him "read" them would have made a very good primer to data visualization even better.
Lima writes in an engaging manner and his work in explicating what visualizations should do and are good for is well done. I could almost wish for a bit more text, actually, some of his thoughts and interpretations of the many visualizations within. Seeing him "read" them would have made a very good primer to data visualization even better.
July 16, 2012
Great book on network knowledge and visualization of complex data. He includes several chapters on the historical view of information partitioning from the 1500's to today that includes attempts at categorizing all knowledge and led to methodologies such as the Dewey Decimal system. He then spends the rest of the book on really beautiful visualizations of big data by groups that have posted there projects to his web site.
March 18, 2015
The author does a good job of tracing the history of network visualization and how cultural and scientific shifts have demanded new forms of articulation. The second half of the book forms a picture gallery broken down by theme and graph type. I found this part to be challenging - not least because of tiny type and hard to make sense of graphs. But ultimately this becomes an exercise in aesthetics because too often the methods used to come by the visualizations are just too pithy.
October 30, 2015
Ah. This was "visualization of networks" and only that (as opposed to "patterns of information" which sounds immenesly more interesting). Not what I was looking for, and from a relatively quick scan it is pretty poor material even if visually appealing. Back to Tufte it is, then.
Read
February 13, 2013After the first chapters I felt I was encountering the same ideas only slightly restated. It did inspire me to re-read Tufte.
June 9, 2013
Just read the blog!
October 6, 2014
not the easiest book to browse; but a good overview of how to display information. a variant and extension on tufte's thoughts.
Read
August 10, 2015Damn fine
Read
February 11, 2016A gorgeous book with a thoughtful history of the art/science of network visualization.
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