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Visual complexity [Anglais] [Relié]

Manuel Lima
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Visual complexity + Data Flow : Design graphique et visualisation d'information + Data Flow 2: Visualizing Information in Graphic Design
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Détails sur le produit

  • Relié: 240 pages
  • Editeur : Princeton Architectural Press (1 septembre 2011)
  • Langue : Anglais
  • ISBN-10: 1568989369
  • ISBN-13: 978-1568989365
  • Dimensions du produit: 26,9 x 21,8 x 2,5 cm
  • Moyenne des commentaires client : 2.0 étoiles sur 5  Voir tous les commentaires (1 commentaire client)
  • Classement des meilleures ventes d'Amazon: 245.265 en Livres (Voir les 100 premiers en Livres)
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Couverture | Copyright | Table des matières | Extrait | Index
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Commentaires client les plus utiles
1 internautes sur 1 ont trouvé ce commentaire utile 
2.0 étoiles sur 5 catalogue 10 février 2014
Par Etienne
Livre remarcablement illustré. La chose triste c'est qu'il a été pensé plus comme un catalogue de représentations possible que comme un livre opérationnel!
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Commentaires client les plus utiles sur (beta) 4.2 étoiles sur 5  19 commentaires
45 internautes sur 53 ont trouvé ce commentaire utile 
1.0 étoiles sur 5 Nice pictures but no explanations 4 janvier 2012
Par David S. Mazel - Publié sur
As the world becomes more connected, whether through email, social web sites, chat, or instant messaging, there is now a need to understand this interconnectivity. These networks could be computer networks, the connectedness of genes and chromosomes, proteins, or even citations of papers. The need is not new because networks are not new. There have been networks connecting people through phone calls and postal letters, for example. What is new is the many different methods of connection and the size of networks. Given these large networks, how might you go about understanding their properties? Further, how might you go about gaining insight into the types of connections, the strong versus weak connections, the permutations of connections and other such features of networks?

If you were to try to simply list the connections, say in a table that showed a person and who he sent email to, that table would quickly grow. You would have gained little insight to the network except maybe to see just how vast it is. The natural method, then, is to find a graph, a picture, of the network. In Visual Complexity, Manuel Lima starts to show us different pictures we can use to see networks.

He begins with a short history of networks and graphs some dating back centuries. If you gain nothing else from that you will at least see that the need for insight is quite old. Lima does a satisfactory job of describing this history and his illustrations are excellent supports for the text. He then goes on to show more examples and as he does so, the textual explanations slowly fall away. In fact, by page 97 (out of a total of 272 pages) there is very little text but lots of pictures.

If you had to pick a point where the book fails, it's page 97 at the start of chapter 04 (his numbering includes a leading zero) entitled "Infinite Interconnectedness." At this point Lima simply shows network diagrams of nations, authors and papers, email messages, proteins. Lima goes on a roll so that at Chapter 05 we have pictures of the "European Academic Network", campaign donation networks, and even a diagram of James Joyce's language usage. The topics are quite varied, but the pictures are impossible to read and there's no explanation as to how one can understand these hideous and over blown graphics. They are cramped, impossible to read, and impossible to understand. The pictures deserve explanations and details as to how you can understand them and see what it is the creators are trying to say. Unfortunately, Lima does not tell us what the graphics mean, how we should understand them, and what, if anything, there is to be gained by looking at them.

It's a shame that Lima let his readers down. I would think that there is much to learn from the selected graphs and much to take away for our own use. But, Lima does not say and with the pictures as they are, we are left on our own with no way to interpret the information.

With all due respect to Lima, before you buy this book, you should look to the books on graphics and data display by Edward Tufte. There you'll find fantastic graphs and pictures with detailed explanations so that you can learn how to make your own work better. Lima' book won't do that for you.
32 internautes sur 38 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Indispensable! 17 septembre 2011
Par Maria Isabel Meirelles - Publié sur
Format:Relié|Achat vérifié
As a practitioner and educator in information design I am writing to recommend strongly Visual Complexity by Manuel Lima. The field had been lacking analytical resources until this book beautifully filled the gap. It is well researched and well written with copious well chosen examples. It provides an in-depth and broad view of the history, theories and methods of visualizing data, mostly focusing on network visualizations. Furthermore, it proposes a methodology for visualizing data which can be very helpful especially for beginners.

I have been following Lima's site for several years and have been suggesting it to my students as a resource. My excitement upon learning about the book immediately led me to reserve a copy of it. The book amazed me with its rigor and the quality of its research. I have to say that I learned a good amount from it which, of course, made me very happy!

I would like to end by recommending that Visual Complexity be an essential reference to all of us who work in visualizing data, from all fields of knowledge, not only designers. Above all, it is a must-have for communication design college students (and instructors). It will be a required book in all of my information design courses. I am certain Visual Complexity will impart both inspiration and information to all who read it.
8 internautes sur 8 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Great Prelude to Lima's Trees Book 15 mars 2014
Par Let's Compare Options - Publié sur
This first in Lima's series on graphic networking information presentation, wonderfully sets the stage for his next blockbuster-- his trees book you can see here: The Book of Trees: Visualizing Branches of Knowledge.

The classic in this field is by Tufte: Visual Explanations: Images and Quantities, Evidence and Narrative. Unlike Visual Complexity, Tufte gives detailed explanations of the creation and meaning of his visualizations.

Lima has been praised and panned for the hardcover version of this book. The pans cite too many pictures and too little words, the praise cites the same thing! So, before you invest, two things:

1. Use the generous Amazon/ publisher look inside feature. Authors and publishers who allow this want satisfied readers and I applaud them!

2. If you're into presentation, art and think like a digital artist, this book is for you. If you're an excel/ table/ linear algebra/matrix type, you'll find this wanting.

In other words, if you are looking for interesting depictions, rather than details of how they got there or what they mean, this is well worth your investment.

I have an advance copy of trees, and Manuel/Princeton listened to the past reviews and added a lot more information, both current and Lima's traditional historic, on not just the graphic what, but the how and why. It is still not a "how to" manual (you'd be better off getting a combinatorics programming or Excel graphics book for that!) but gives both artists and presenters another great encyclopedia. Tufte (above) on the other hand, gives both good AND bad examples-- showing how NOT to present your data.

As a programmer, I obviously am into presentation and trees with completely different motives-- data structures and how they interact with alogrithmic solutions. Even if you're into the nuts and bolts of big data like I am, you'll still enjoy this by superimposing your own solutions on the graphics here and in trees. It also will help you with your users, who as I'm sure you know, will come to you with presentation questions as well. There even is a "big data" CEO job popping up paying high 6 and a lot of stock-- the "CDSO" or "Chief Data Science Officer." As a library science type, I hope this trend continues for all my cyber librarian friends-- go for it, and dust off that XML tome!!
22 internautes sur 28 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Visually gorgeous, intellectually stunning 15 septembre 2011
Par Justin M - Publié sur
Format:Relié|Achat vérifié
People interested in and fascinated by gorgeous data and network visualization will love this book.

Lima has done a masterful job of researching and showcasing some of the most beautiful visualizations in the world. However he has actually gone much, much further.

The book contains deep original research on the origins of visual representation, the emergence of networks and network thinking, as well as exploring a new syntax for mapping complex systems. All of this makes for something far more sophisticated than a compendium of pretty infographics -- even though aesthetes will be very much satisfied! -- instead it is an ambitious and intellectually significant dive into the very heart of networks, the desire to understand data, and the practice of discerning insights from their visualization.

A particular highlight are the jaw-dropping comparisons between Jackson Pollock's art and network visualizations in the chapter on 'Complex Beauty'. Lima compares one Jackson Pollock painting with a computer-generated model produced by an IBM supercomputer mapping millions of neuron connections in the brain. The two images, side-by-side, are eerily similar. It gives you the tingling sensation that Pollock's work was less raw artistic explosions and more a representation of what he was 'seeing' deep inside into his brain.

All up, an immensely valuable contribution to an exciting and emerging phenomenon. Brilliant for people interested in beautiful visualizations and perfect for those wanting to delve a little deeper into what's really going on.

'Visual Complexity' is taking pride of place on top of my coffee table.
13 internautes sur 16 ont trouvé ce commentaire utile 
5.0 étoiles sur 5 Inspirational and Informative 15 septembre 2011
Par T. McCall - Publié sur
Format:Relié|Achat vérifié
As an infographics designer and data visualization artists for nearly 20 years, I've been a big fan of Manuel Lima's webiste I was excited to find his new book here on Amazon and it's been a pleasure to absorb. Not only do I find it to be a great resource, I find it to be full of inspiration and have added it to our company library at My employees are often fighting over access to the book. I highly recommend it!
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