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Visualization Analysis and Design
Learn How to Design Effective Visualization SystemsVisualization Analysis and Design provides a systematic, comprehensive framework for thinking about visualization in terms of principles and design choices. The book features a unified approach encompassing information visualization techniques for abstract data, scientific visualization techniques for spatial data, and visual analytics techniques for interweaving data transformation and analysis with interactive visual exploration. It emphasizes the careful validation of effectiveness and the consideration of function before form. The book breaks down visualization design according to three what data users need to see, why users need to carry out their tasks, and how the visual representations proposed can be constructed and manipulated. It walks readers through the use of space and color to visually encode data in a view, the trade-offs between changing a single view and using multiple linked views, and the ways to reduce the amount of data shown in each view. The book concludes with six case studies analyzed in detail with the full framework.The book is suitable for a broad set of readers, from beginners to more experienced visualization designers. It does not assume any previous experience in programming, mathematics, human–computer interaction, or graphic design and can be used in an introductory visualization course at the graduate or undergraduate level.
428 pages, Kindle Edition
First published September 26, 2014
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Displaying 1 - 8 of 8 reviews
April 21, 2018
Let's get this out of the way first: this book is a textbook. My Opinion? This book was incredible. You have no idea how weird I feel saying that I found a textbook incredible.
I was assigned this textbook as part of the W209 Data Visualization & Communication course at UC Berkeley. I do not usually do my readings for courses unless my lecturers are so bad that I have no other choice. Even then, I usually turn to Google first and find my answers there. I started reading this book on a flight as a way to my force myself to get ahead on my studies. And strangely, *I read through the entire flight and continued to read it on the return flight*. Admittedly, I am strongly biased as I am very interested in this material.
About the book itself, it is a textbook and therefore is quite dry. One thing Munzner does particularly well, in my opinion, is organization. The sections and chapters did a great job of building on top of one another. She also includes a graphic at the start of each chapter outlining what the chapter is covering and how the topics relate to one another. I found these extraordinarily helpful and have returned several times to these graphics for reference.
All in all, if you are really interested in data visualization, get this book. It is about as integral to the field as Tufte's work. If you are a student and have this book forced upon you, fear not. It could be a lot worse.
I was assigned this textbook as part of the W209 Data Visualization & Communication course at UC Berkeley. I do not usually do my readings for courses unless my lecturers are so bad that I have no other choice. Even then, I usually turn to Google first and find my answers there. I started reading this book on a flight as a way to my force myself to get ahead on my studies. And strangely, *I read through the entire flight and continued to read it on the return flight*. Admittedly, I am strongly biased as I am very interested in this material.
About the book itself, it is a textbook and therefore is quite dry. One thing Munzner does particularly well, in my opinion, is organization. The sections and chapters did a great job of building on top of one another. She also includes a graphic at the start of each chapter outlining what the chapter is covering and how the topics relate to one another. I found these extraordinarily helpful and have returned several times to these graphics for reference.
All in all, if you are really interested in data visualization, get this book. It is about as integral to the field as Tufte's work. If you are a student and have this book forced upon you, fear not. It could be a lot worse.
May 9, 2017
This book presents very useful bottom-up techniques for designing and implementing visualizations, including data processing, data arrangement, visual encoding, manipulating and polishing views, navigation techniques and some case studies. For each chapter, it hash a nice structure figure that visualize the main points and brief summary that recaps and extends the reading. The main focus is on design other than programming or graphics.
January 12, 2021
A useful overview of the field, covering jargon, technique and application in a readable manner. An excellent introduction for beginners but the density of subjects does not make it easy for readers with a less than strong relation with the field.
September 21, 2019
Clear description of concepts.
November 12, 2022
Es pertinente leer este libro para entender las diferentes visualizaciones que se presentan en la vida, el libro revela información de cómo se crean las visualizaciones, como interpretarlas y descubrir que datos son los utilizados.
December 21, 2015
This is an introductory textbook for data visualization. As someone who didn't really know anything about this topic before my class, it was just right for me. It did suffer from an awful lot of typos and I would have dinged it a half star for that if I could (so, consider this a 3.5).
October 13, 2017
This book gives a framework to think about visualization: how to design and how to analyze.
Want to read
May 10, 2019I loved the opening example of data semantics:
Poetic, really. Does anyone write poetry based on out-of-context dataset rows, just like visual artists might use out-of-context "found objects"? Reminds me a bit of "Numbers" by Mary Cornish.
...suppose that you see the following data:Basil, 7, S, Pear
These numbers and words could have many possible meanings. Maybe a food shipment of produce has arrived in satisfactory condition on the 7th day of the month, containing basil and pears. Maybe the Basil Point neighborhood of the city has had 7 inches of snow cleared by the Pear Creek Limited snow removal service. Maybe the lab rat named Basil has made seven attempts to find his way through the south section of the maze, lured by scent of the reward food for this trial, a pear.
Poetic, really. Does anyone write poetry based on out-of-context dataset rows, just like visual artists might use out-of-context "found objects"? Reminds me a bit of "Numbers" by Mary Cornish.
Displaying 1 - 8 of 8 reviews