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Visualizing Data: Exploring and Explaining Data with the Processing Environment
 
 

Visualizing Data: Exploring and Explaining Data with the Processing Environment [Kindle Edition]

Ben Fry
3.8 out of 5 stars  See all reviews (17 customer reviews)

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Product Description

Enormous quantities of data go unused or underused today, simply because people can't visualize the quantities and relationships in it. Using a downloadable programming environment developed by the author, Visualizing Data demonstrates methods for representing data accurately on the Web and elsewhere, complete with user interaction, animation, and more.

How do the 3.1 billion A, C, G and T letters of the human genome compare to those of a chimp or a mouse? What do the paths that millions of visitors take through a web site look like? With Visualizing Data, you learn how to answer complex questions like these with thoroughly interactive displays. We're not talking about cookie-cutter charts and graphs. This book teaches you how to design entire interfaces around large, complex data sets with the help of a powerful new design and prototyping tool called "Processing".

Used by many researchers and companies to convey specific data in a clear and understandable manner, the Processing beta is available free. With this tool and Visualizing Data as a guide, you'll learn basic visualization principles, how to choose the right kind of display for your purposes, and how to provide interactive features that will bring users to your site over and over. This book teaches you:

  • The seven stages of visualizing data -- acquire, parse, filter, mine, represent, refine, and interact
  • How all data problems begin with a question and end with a narrative construct that provides a clear answer without extraneous details
  • Several example projects with the code to make them work
  • Positive and negative points of each representation discussed. The focus is on customization so that each one best suits what you want to convey about your data set
The book does not provide ready-made "visualizations" that can be plugged into any data set. Instead, with chapters divided by types of data rather than types of display, you'll learn how each visualization conveys the unique properties of the data it represents -- why the data was collected, what's interesting about it, and what stories it can tell. Visualizing Data teaches you how to answer questions, not simply display information.

About the Author

Ben Fry received his doctorate from the Aesthetics + Computation Group at the MIT Media Laboratory and was the 2006-2007 Nierenberg Chair of Design for the Carnegie Mellon School of Design. He worked with Casey Reas to develop Processing, which won a Golden Nica from the Prix Ars Electronica in 2005. Ben's work has received a New Media Fellowship from the Rockefeller Foundation, and been shown at the Museum of Modern Art, Ars Electronica, the 2002 Whitney Biennial and the 2003 Cooper Hewitt Design Triennial.


Product Details

  • Format: Kindle Edition
  • File Size: 3192 KB
  • Print Length: 384 pages
  • Page Numbers Source ISBN: 0596514557
  • Simultaneous Device Usage: Unlimited
  • Publisher: O'Reilly Media; 1 edition (December 17, 2008)
  • Sold by: Amazon Digital Services
  • Language: English
  • ASIN: B0028N4WJC
  • Text-to-Speech: Enabled
  • Average Customer Review: 3.8 out of 5 stars  See all reviews (17 customer reviews)
  • Amazon Best Sellers Rank: #96,432 Paid in Kindle Store (See Top 100 Paid in Kindle Store)
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Customer Reviews

17 Reviews
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Average Customer Review
3.8 out of 5 stars (17 customer reviews)
 
 
 
 
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115 of 127 people found the following review helpful:
3.0 out of 5 stars Mixed feelings, February 3, 2008
By 
Salvatore R. Mangano (Oyster Bay, NY United States) - See all my reviews
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This book allowed me to quickly create some simple applications using the processing API. So, in that respect, the book was successful. However, the book falls short in three respects.

1) One would expect a book with the title "Visualizing Data" to be crammed with pictures showing many different data visualizations. However, this book has relatively few. Every colleague of mine who passed by my desk and picked up the book had the exact same reaction.

2) The processing language is touted as a means for people unfamiliar with programming to get up to speed with visualization. However, I would be very surprised if anyone with little programming experience would get much out of this book.

3) Don't expect to use this book as a reference for the processing language. It is basically just a collection of half explained examples. Consider for example the function smooth(). This function appears in almost every example but forget about trying to find an explanation of what the function does in the book.

The book is probably worth buying to get up to speed quickly but plan on spending a significant amount of time sifting through the processing.org website and other online resources before being able to get anything non-trivial done. And if you don't already know Java then don't expect to accomplish anything even modestly complex without a lot of outside help.
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46 of 51 people found the following review helpful:
2.0 out of 5 stars Little more than a Processing Environment tutorial, February 20, 2008
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Based on the title and publisher's writeup I was expecting the book to provide in-depth coverage of various visual metaphors for understanding and manipulating data, such as "Designing Interfaces" by Tidwell, another O'Reilly book that I am very pleased with.

Unfortunately it would be more appropriate if the title (Visualizing Dta) and sub-title (Exploring and Explaining Data with the Processing Environment) were switched. This book is primarily a tutorial on using the Processing Environment (http://processing.org), showing you how to create various interactive charts and composed primarily of code examples.

In addition, the visualizations presented in the book are far from aesthetically pleasing. The Processing Environment has the capability to create visualizations that are not only functional, but beautiful as well. You can find a collection of visualizations at http://www.visualcomplexity.com, many of which were created with the Processing Environment.

In summary I am granting a 2-star rating because the book does not deliver the expected coverage of data visualization design and even in its explanation of the Processing Environment does not provide exemplary visualizations.
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44 of 52 people found the following review helpful:
5.0 out of 5 stars Outstanding, January 22, 2008
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This is an exceptionally good book on a specialist topic by one of my design heroes. Where most data visualization books present either pages of (often quite ugly) charts and diagrams, but with no tools to create them, Fry manages here to combine both programming skills and a real understanding of design. It's the rare book that manages to do two disciplines really well. Though it's full of code, Visualizing Data is so much more than a technical manual.

This is definitely a programming book; I agree with another reviewer here that if you're already comfortable with Java you'll find this much easier going. But Fry builds his code examples up sensibly, and explains what's going on. A smart Flash developer or Processing dabbler (like me) really won't have any trouble following along. The examples move from simple plotting of points, to time-based animation, to complex correlation, and into more complex visualizations. And it's not just drawing pixels: there are long and useful sections on data acquisition techniques, approaches to parsing and formatting data. Luckily, Fry's a really good writer, and is able to keep these topics from getting dull.

But the great thing about Visualizing Data is that it's also a *design* book--a real one--with thoughtful considerations about use of color, typography, and the "feel" of interaction. Fry's data visualizations are worthy of being in any of Edward Tufte's books. I nearly stood up and cheered when Fry took a few paragraphs in the middle of a code explanation to talk about why the em-dash character and non-lining numerals made the typography of a particular example better. That level of detail is, I think, totally absent from any other book like this.
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The process of understanding data begins with a set of numbers and a question. &quote;
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Why was the data collected, what's interesting about it, and what stories can it tell? &quote;
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But great information visualization never starts from the standpoint of the data set; it starts with questions. &quote;
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