Data Visualization: a successful design process

Table of Contents

• Preface

• 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 3: Demonstrating Editorial Focus and Learning About Your Data
• The importance of editorial focus
• Preparing and familiarizing yourself with your data
• Refining your editorial focus
• Using visual analysis to find stories
• An example of finding and telling stories
• 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

• Index