Data Visualization: a successful design process


Data Visualization: a successful design process
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Overview
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  • A portable, versatile and flexible data visualization design approach that will help you navigate the complex path towards success
  • Explains the many different reasons for creating visualizations and identifies the key parameters which lead to very different design options
  • Thorough explanation of the many visual variables and visualization taxonomy to provide you with a menu of creative options

Book Details

Language : English
Paperback : 206 pages [ 235mm x 191mm ]
Release Date : December 2012
ISBN : 1849693463
ISBN 13 : 9781849693462
Author(s) : Andy Kirk
Topics and Technologies : All Books, Big Data and Business Intelligence, Data

Table of Contents

Preface
Chapter 1: The Context of Data Visualization
Chapter 2: Setting the Purpose and Identifying Key Factors
Chapter 3: Demonstrating Editorial Focus and Learning About Your Data
Chapter 4: Conceiving and Reasoning Visualization Design Options
Chapter 5: Taxonomy of Data Visualization Methods
Chapter 6: Constructing and Evaluating Your Design Solution
Index
  • Chapter 1: The Context of Data Visualization
    • Exploiting the digital age
    • Visualization as a discovery tool
    • The bedrock of visualization knowledge
    • Defining data visualization
    • Visualization skills for the masses
    • The data visualization methodology
    • Visualization design objectives
      • Strive for form and function
      • Justifying the selection of everything we do
      • Creating accessibility through intuitive design
      • Never deceive the receiver
    • Summary
    • Chapter 2: Setting the Purpose and Identifying Key Factors
      • Clarifying the purpose of your project
        • The reason for existing
        • The intended effect
      • Establishing intent – the visualization's function
        • When the function is to explain
        • When the function is to explore
        • When the function is to exhibit data
      • Establishing intent – the visualization's tone
        • Pragmatic and analytical
        • Emotive and abstract
      • Key factors surrounding a visualization project
      • The "eight hats" of data visualization design
        • The initiator
        • The data scientist
        • The journalist
        • The computer scientist
        • The designer
        • The cognitive scientist
        • The communicator
        • The project manager
      • Summary
        • Chapter 4: Conceiving and Reasoning Visualization Design Options
          • Data visualization design is all about choices
          • Some helpful tips
          • The visualization anatomy – data representation
            • Choosing the correct visualization method
            • Considering the physical properties of our data
            • Determining the degree of accuracy in interpretation
            • Creating an appropriate design metaphor
            • Choosing the final solution
          • The visualization anatomy – data presentation
            • The use of color
            • Creating interactivity
            • Annotation
            • Arrangement
          • Summary
          • Chapter 5: Taxonomy of Data Visualization Methods
            • Data visualization methods
            • Choosing the appropriate chart type
              • Comparing categories
                • Dot plot
                • Bar chart (or column chart)
                • Floating bar (or Gantt chart)
                • Pixelated bar chart
                • Histogram
                • Slopegraph (or bumps chart or table chart)
                • Radial chart
                • Glyph chart
                • Sankey diagram
                • Area size chart
                • Small multiples (or trellis chart)
                • Word cloud
              • Assessing hierarchies and part-to-whole relationships
                • Pie chart
                • Stacked bar chart (or stacked column chart)
                • Square pie (or unit chart or waffle chart)
                • Tree map
                • Circle packing diagram
                • Bubble hierarchy
                • Tree hierarchy
              • Showing changes over time
                • Line chart
                • Sparklines
                • Area chart
                • Horizon chart
                • Stacked area chart
                • Stream graph
                • Candlestick chart (or box and whiskers plot, OHLC chart)
                • Barcode chart
                • Flow map
              • Plotting connections and relationships
                • Scatter plot
                • Bubble plot
                • Scatter plot matrix
                • Heatmap (or matrix chart)
                • Parallel sets (or parallel coordinates)
                • Radial network (or chord diagram)
                • Network diagram (or force-directed/node-link network)
              • Mapping geo-spatial data
                • Choropleth map
                • Dot plot map
                • Bubble plot map
                • Isarithmic map (or contour map or topological map)
                • Particle flow map
                • Cartogram
                • Dorling cartogram
                • Network connection map
            • Summary
            • Chapter 6: Constructing and Evaluating Your Design Solution
              • For constructing visualizations, technology matters
                • Visualization software, applications, and programs
                • Charting and statistical analysis tools
                • Programming environments
                • Tools for mapping
                  • Other specialist tools
              • The construction process
              • Approaching the finishing line
              • Post-launch evaluation
              • Developing your capabilities
                • Practice, practice, practice!
                • Evaluating the work of others
                • Publishing and sharing your output
                • Immerse yourself into learning about the field
              • Summary

              Andy Kirk

              Andy Kirk is a freelance data visualization design consultant, training provider, and editor of the popular data visualization blog, visualisingdata.com. After graduating from Lancaster University with a B.Sc. (Hons) degree in Operational Research, he spent over a decade at a number of the UK's largest organizations in a variety of business analysis and information management roles. Late 2006 provided Andy with a career-changing "eureka" moment through the serendipitous discovery of data visualization and he has passionately pursued this subject ever since, completing an M.A. (with Distinction) at the University of Leeds along the way. In February 2010, he launched visualisingdata.com with a mission to provide readers with inspiring insights into the contemporary techniques, resources, applications, and best practices around this increasingly popular field. His design consultancy work and training courses extend this ambition, helping organizations of all shapes, sizes, and industries to enhance the analysis and communication of their data to maximize impact. This book aims to pass on some of the expertise Andy has built up over these years to provide readers with an informative and helpful guide to succeeding in the challenging but exciting world of data visualization design.

              Submit Errata

              Please let us know if you have found any errors not listed on this list by completing our errata submission form. Our editors will check them and add them to this list. Thank you.


              Errata

              - 4 submitted: last submission 18 May 2013

              Errata type: Others | Page number: 63

              The quote from Amanda Cox should have been "Different forms do better jobs at answering different types of questions." rather than "Different forms do better jobs at answering different questions."

               

              Errata type: Others | Page number: 141

              The line "multiple values series to be layered" must be "multiple series to be layered", that is, the word "values" must be removed.

               

              Errata type: Others | Page number: 70

              The names of Chapter 5 and Chapter 4 are Taxonomy of Data Visualization Methods and Conceiving and Reasoning Visualization Design respectively

               

              Errata type: Typo| Page number: 127

              The word "status" appears twice, it should only appear once.

               

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              What you will learn from this book

              • A comprehensive and contemporary introduction to data driven visualization design and the most effective approaches to tackle any design challenge
              • How to achieve maximum impact with designs that engage on an aesthetic level and perform on a functional one
              • Foundation understanding of the human visual system
              • Identifying the purpose of your visualization and your projects parameters to determine overriding design considerations across your project’s execution
              • How to develop analytical questions and identify a visual narrative as you immerse yourself in your data, familiarizing with its inherent qualities
              • Apply critical thinking to visualization design and get intimate with your dataset to identify its potential visual characteristics
              • Appreciating the importance of an editorial approach to design and best practice approaches for tackling different data types and problem contexts
              • A thorough overview of the anatomy of a data visualization design and a menu of the most important and innovative visualization methods
              • Overview of the essential visualization tools and resources
              • Profile of some of the most impressive and inspiring contemporary visualization projects

              In Detail

              Do you want to create more attractive charts? Or do you have huge data sets and need to unearth the key insights in a visual manner? Data visualization is the representation and presentation of data, using proven design techniques to bring alive the patterns, stories and key insights locked away.

              "Data Visualization: a Successful Design Process" explores the unique fusion of art and science that is data visualization; a discipline for which instinct alone is insufficient for you to succeed in enabling audiences to discover key trends, insights and discoveries from your data. This book will equip you with the key techniques required to overcome contemporary data visualization challenges.

              You’ll discover a proven design methodology that helps you develop invaluable knowledge and practical capabilities.

              You’ll never again settle for a default Excel chart or resort to ‘fancy-looking’ graphs. You will be able to work from the starting point of acquiring, preparing and familiarizing with your data, right through to concept design. Choose your ‘killer’ visual representation to engage and inform your audience.

              "Data Visualization: a Successful Design Process" will inspire you to relish any visualization project with greater confidence and bullish know-how; turning challenges into exciting design opportunities.

              Approach

              A comprehensive yet quick guide to the best approaches to designing data visualizations, with real examples and illustrative diagrams. Whatever the desired outcome ensure success by following this expert design process.

              Who this book is for

              This book is for anyone who has responsibility for, or is interested in trying to find innovative and effective ways to visually analyze and communicate data.

              There is no skill, no knowledge and no role-based pre-requisites or expectations of anyone reading this book.

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