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Information Visualization
 
 
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Information Visualization [Hardcover]

Chaomei Chen (Author)
4.0 out of 5 stars  See all reviews (3 customer reviews)

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Book Description

October 21, 2004
Information visualization is not only about creating graphical displays of complex and latent information structures. It also contributes to a broader range of cognitive, social, and collaborative activities. This is the first book to examine information visualization from this perspective. This 2nd edition continues the unique and ambitious quest for setting information visualization and virtual environments in a unifying framework. It pays special attention to the advances made over the last 5 years and potentially fruitful directions to pursue. It is particularly updated to meet the need for practitioners. The book is a valuable source for researchers and graduate students.

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Editorial Reviews

Review

From the reviews of the second edition: "Information visualization is a young academic specialty, having been practiced now for about a decade. … This book … is a survey of the state of the art. … the reader gets a broad overview of many aspects of this field. … can get a good sense of this developing field. In each chapter, Chen provides … . He is clearly excited by his field, and conveys it well in this book."(G. R. Mayforth, Computing Reviews, May, 2005)   In summary Information Visualization is a comprehensive text, providing a comprehensive level of information on what is essentially a limitless topic. Although not an easy read, and certainly not for the layman, the text is nevertheless an excellent tool for the researcher to have to hand. Offering a concise overview of the fundamental concepts, where this text really excels is in its focus on application, and extensive referral to ‘real-world’ examples of Information Visualization, and particularly its use in cross discipline research, If you are a novice in the field, looking for a gentle introduction, look elsewhere. If, however, you know the fundamentals and are looking for a comprehensive survey of the state-of-the-art, essential details on empirical grounding of techniques, and in particular a wealth of application specific information, then this is likely to be the text for you. (Terence Clifton, Informer 17, pp7-8)

Product Details

  • Hardcover: 304 pages
  • Publisher: Springer; 2nd edition (October 21, 2004)
  • Language: English
  • ISBN-10: 1852337893
  • ISBN-13: 978-1852337896
  • Product Dimensions: 9.5 x 6.4 x 0.9 inches
  • Shipping Weight: 1.6 pounds (View shipping rates and policies)
  • Average Customer Review: 4.0 out of 5 stars  See all reviews (3 customer reviews)
  • Amazon Best Sellers Rank: #3,131,230 in Books (See Top 100 in Books)

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7 of 7 people found the following review helpful:
4.0 out of 5 stars cool graphics ideas, January 10, 2007
Chen gives a masterful excursion into how information can be visualised. A major aim is that it is presented in a way that a human can see a large mass of data in a meaningful manner. Hence many techniques are shown in numerous colour diagrams that are an indispensible part of the book. Indeed, the book would lack much meaning without those diagrams!

The display ideas have mostly been developed in the last 15 years. In part due to increasing computational power and graphics, that makes such displaying feasible. But another driving force has been the Web. And within this, the Virtual Reality Markup Language. Various proponents, like Blaxxsun, have built VRML worlds in which data can be shown. And in which users can browse. Often in a multiuser mode.

One lesson from the text is that simulated annealing is simply too computationally intensive for deciding how to make a graph with #nodes > 100 or so. It's certainly a nice idea. But sadly only for smaller graphs.

There is an interesting discussion on topic analysis and display. A harder problem than "merely" dealing at the document level. But the results shown seem rather limited. Much more work is needed here.

If you are from physics, you should note that an extensive, protracted example of superstring research was used by Chen. He showed his own research in how key papers could be found via co-citation analysis and graphing. This was to tackle the general problem of trying to find trends and paradigm shifts in scientific research.
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4 of 4 people found the following review helpful:
4.0 out of 5 stars Essential Reference, Slightly Disappointing for Me Personally, August 21, 2008
I had already decided to grade this a four instead of five, in part because it makes me cranky when world-class authors such as the author of this book neglect other world-class pioneers because of their unwillingness to do a proper search outside their own narrow boundaries. I refer of course to Dick Klavens, Brad Ashford, and Katy Borner, whose Maps of Science are online and spectacular. Even Eugene Garfield, the inventor of citation analysis, gets short shrift.

That aside, the book is an essential reference. While it makes the needed point, that first generation visualization was about showing structure and relationships, and second generation visualization needs to be more dynamic and depict evolutionary and revolutionary changes and mutations (and I would add, provide early warning of anomalies and emergent patterns).

The last chapter, 8, on Detecting Abrupt Changes and Emerging Trends, is very interesting, but heavy on mathematics, and lacking in great detail, which reminds me this is really an overview text, and should be valued in that light. Two examples of fraud detection that I have personally seen as representative of the power of visualization include Dr. Bert Little's discover of $79 million in crop insurance fraud among roughly seven insurance agents and 20+ specific farmers; and the brilliant work of Dr. Simon J. Pak and Dr. John S. Zdanowicz who found $5o billion a year in import-export tax fraud (and Colombian coffee cans marked one pound and weighing 1.5 pounds) through their exploitation of public Department of Commerce databases.

This book has been assigned to our senior working technical person along with three others listed below.
A New Ecology: Systems Perspective, Sven Jorgensen et al (Elsevier, 2007), not on Amazon that I could find
Handbook of Data Visualization (Springer Handbooks of Computational Statistics) (Springer Handbooks of Computational Statistics)
Information Visualization: Beyond the Horizon
Building Trustworthy Semantic Webs

For myself, I put the book down thinking to myself, citation analysis is all well and good, but how do we integrate co-visualization of content, geospatial, money (e.g. "true costs" of each aspect or attribute)?

I continue to admire the work of Peter Morville, such as Ambient Findability: What We Find Changes Who We Become. His name does not appear in the index either. See also: Keeping Abreast of Science and Technology: Technical Intelligence for Business
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10 of 13 people found the following review helpful:
4.0 out of 5 stars Full of Ideas, August 30, 2006
This review is from: Information Visualization (Hardcover)
This is a beautiful book, with many color images. While it includes a large number of excellent figures, and covers a wide range techniques and systems, the text is not, however, a good starting point for a newcomer to the field. (See Card, et al, "Readings in Information Visualization" for a starting point.) This book should be used as a pointer to the literature, which provide the missing details. It covers a wide range techniques, and is worth having.
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Inside This Book (learn more)
First Sentence:
Information visualization as a distinctive field of research has less than ten years of history, but has rapidly become a far-reaching, interdisciplinary research field. Read the first page
Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
spatial tightness, knowledge domain visualization, graph drawing techniques, graph drawing aesthetics, information visualization design, web locality, information visualization community, information visualization research, spatial user interface, information visualization systems, generalized similarity analysis, drawing undirected graphs, elementary perceptual tasks, hyperbolic tree browser, abstract information space, top ten articles, pivot nodes, mapping scientific frontiers, first superstring revolution, salient nodes, uniform edge lengths, information visualization techniques, detecting abrupt changes, hyperbolic views, second superstring revolution
Key Phrases - Capitalized Phrases (CAPs): (learn more)
Data Mountain, Nuclear Physics, University of Maryland, Physical Review, Roanoke Island, Science Watch, Star Trekys, Del Negro, United States, Lost Colony, Tamara Munzner, Time Tube, International Conference, Las Vegas, Lothar Krempel, Mark Derthick, Pacific Northwest National Laboratory, Physics Letters, University College London, Windows File Explorer, Younger Dryas, American Statistical Association, Battelle Memorial Institute, Biol Chem, Exploratory Data Analysis
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