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Rating: 
Summary: Refreshingly Honest
Review: Actually, I found the non-sanitized and sometimes redundant nature of the coverage to be refreshingly honest.This is a book about a new field circling while getting a sense of direction. We very seldom get such an honest look into just how this sort of process happens. Instead, we get the bottom line version where everything obviously inevitably followed from what came before to the predestined conclusion -- in 20-20 hindsight. 5 Stars for this one
Rating: 
Summary: Some good work but the editing could use some work
Review: As one of the authors of one of the papers, I have mixed feelings about this collection. I think there is some fine work included in the volume, which was the output of a series of workhops looking at the interesection of data mining and data visualization. But I think the publisher (which was changed from Springer to MK after a lengthy delay) and the editors made some mistakes in how the collection was put together. First of all, the book includes the abstracts that workshop participants submitted to gain access to the workhop. As another reviewer indicates, these abstracts are typically very short and often contain content that is included in the longer pieces. The abstracts should have been left out, or at least put into an appendix with an explanation. In addition, there should have been a more significant section providing an overview of the field and a discussion of the opportunities available to the combination of mining and visualization. That being said, I think the book is a good addition to the field (ignoring the abstract chapters) and describes some interesting ideas by the leaders in the field. I don't think there is any book out there that tackles this subject matter adequately and hopefully this book will help push the state of the art a bit further.
Rating:
Summary: Editor's note
Review: This book is the result of two workshop whose goals were to open up the dialog between researchers in visualization and data mining, two key areas involved in data exploration. Publication was delayed for many reasons and MK agreed to publish the workshop proceedings. It was difficult to do provide a historical record (thus all the workshop papers) and at the same time elegant content for future readers. A balance was struck - additional tutorials provided, some organization, and edited papers. The result should be viewed in that context: a collection of papers, some of which are tutorial, some idealized positions, some seminal in nature, and some provocative. These are the works of creative and insighful individuals and I am pleased to see them disseminated.
Rating: 
Summary: Did the editors ever look at this?
Review: This is very likely the worst book I have ever seen.
Some chapters are barely longer than one (1! and I
am not kidding!) page and merly point to the one
reference, which is - surprise - written by the same
author. There are also chapters that are bit longer
but highly reduandant to other material in the
book - a section on data visualization shows pretty
much the same pictures and graphs than the one on model
visualization. The book does not even attempt to be
consistent or have any flow besides a rough grouping
into a couple of categories. I find it disturbing that such a bad collection of
obviously non-edited abstracts and papers makes it
into a book. I guess the editors (or publisher?) just
assumed that something with "visualization" and "data
mining" in the title would sell no matter what?
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