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Book Description
Looking at Data Through the Eyes of Experts
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About the Author
Julie Steele is an Editor at O'Reilly currently working on titles related to Python, SQL, PHP, web frameworks and CMS, databases (relational and non-relational), big data and cloud computing, and data visualization. She's also interested in data transparency and open government, and recently completed a master's degree in political science at Rutgers University.Noah Iliinsky has spent the last several years thinking about effective approaches to creating diagrams and other types of information visualization. He also works in interface and interaction design, all from a functional and user-centered perspective. Before becoming a designer he was a programmer for several years. He has a master's in Technical Communication from the University of Washington, and a bachelor's in Physics from Reed College.
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Product details
Paperback: 418 pages
Publisher: O'Reilly Media; 1 edition (July 1, 2010)
Language: English
ISBN-10: 1449379869
ISBN-13: 978-1449379865
Product Dimensions:
7 x 0.7 x 9.2 inches
Shipping Weight: 1.8 pounds (View shipping rates and policies)
Average Customer Review:
4.2 out of 5 stars
13 customer reviews
Amazon Best Sellers Rank:
#406,864 in Books (See Top 100 in Books)
I feel the major areas where good visualization adds value is - avenues of knowledge discovery, information presentation or simply context exploration where one does not know beforehand what insights data may reveal or the extent of relationships between data points. It can be debated that good visualizations could possibly increase cognitive resources available to our minds and decrease conceptual load that has to be dealt with at one time. Visual analytics is an invaluable tool for divergent thinking as well. Coming up with good visualizations is hard but its impact can be immediate and convincing. The visual impact is probabaly more because visual pathways have higher bandwidth at the systems level directly to our reptilian brain whereas logical reasoning resides on the neocortex. Sometimes we just have to see to believe.The book does an excellent job of visiting various applicable domains. There is enough variety to keep you occupied. Its covers visualizing social datasets(link-node), hierarchical datasets(trees), categorical datasets(relational), time-varying datasets and other most commonly found datasets in scientific and information visualizations. Most chapters are well written with plenty of visuals. If you are an ardent fan of visuals you probabaly have seen everything in this book at one place or another. I think a significant part of the information is derived from papers or other well known publications. You can find almost anything by taking the visualcomplexity website as a starting point. However, the book can save you the research and is an excellent introductory text to expand your knowledge on visualizations. That being said, I feel its little expensive for its size and as most content is there on the web already, O'Reilly should have listed it at slightly lesser cost. In case you are not going to buy, its a 5-star book no doubt.
The essays in this book are really interesting and thought provoking.
Beautifull illustrations
Visualization is the graphic presentation of data -- portrayals meant to reveal complex information at a glance. Think of the familiar map of the New York City subway system, or a diagram of the human brain. Successful visualizations are beautiful not only for their aesthetic design, but also for elegant layers of detail that
Haven't finish it yet but looks good so far..
Like all of O'Reilly's Beautiful Series this collection offers an excellent overview of the subject matter it describes; it is carefully edited to provide smooth reading of insights of multiple experts on telling a clear simplifying visual story with data. These viewpoints, war stories and insights from multiple practitioners is as beautiful as any of Edward Tufte's works but provides more practical insight into the process of converting raw uninterpreted data on a complex problem into a computer generated visual story. Each of these data points and illustrations give new insight into the process of converting data complexity into a simplified and explanatory visual presentation. Insights into the process of exploiting software methods for showing this story are also given in sufficient depth something else that would not be gained from other Tuftean works on Information Design. The heavy coated stock and color corrected illustrations in this deceptively compact volume fully illustrate the variety and beauty of the authors visualization examples.I found all of the illustrated chapters and differing expert viewpoints on visual storytelling with data extremely valuable. A slight nit I would have with this phenomenal work is that I would have placed Jessica Hagy's chapter entitled Visualization: Indexed derived from her blog on visual storytelling first because of its explanatory power. But, perhaps the editors felt that a different emphasis was appropriate in that this is an O'Reilly collection emphasizing Visual Storytelling with The Computer as the Preeminent Tool.A Beautiful Coffee Table Book that will serve both scientists and graphic artists.--Ira LaefskyMSE/MBAHCI and IT Consultant formerly on the Senior Staff of Arthur D. Little Inc. and Digital Equipment Corporation
It is cool to have a book about various real life data visualization cases. Some of the articles are hard to read while some others are inspiring. This book kind of opens the door for me into Processing. And the beauty of some of the diagrams just gave me some new idea about how to put my own data onto computer screen. Currently I would give Processing a try and at the mean time stick to R for a while.A particularly interesting chapter is about postmortem visualization. Not saying I am going to become a CSI, but reading it at least give me a hope about combining the thing I learn and the profession I want to join.
As a software developer, I often struggle with how to best present data to a user in a meaningful way. This book explores a variety of scenarios and datasets, and, how people far smarter than I created unique ways to express that data in new and interesting ways. One of the best parts of this book is the explanations of what worked and what didn't, and the principles behind creating visualizations that express concepts cleanly and concisely.If you have any interest in this field, I can't recommend this book highly enough. Fantastic, useful information.
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