book

Designing Data Visualizations

by Noah Iliinsky, Julie Steele

September 2011

Beginner to intermediate

114 pages

2h 51m

English

O'Reilly Media, Inc.

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How This Book Is OrganizedWhat We Mean When We Say…Figures Used by PermissionSee the Color Figures OnlineAttributions and PermissionsSafari® Books OnlineHow to Contact UsAcknowledgments
ComplexityInfographics versus Data VisualizationInfographicsData VisualizationExploration versus ExplanationExplorationExplanationHybrids: Exploratory ExplanationInformative versus Persuasive versus Visual ArtThe Designer-Reader-Data TrinityInformativePersuasiveVisual Art
DesignerWhy Are You Here?ReaderYou Are Creating This for Other PeopleThey Are Not YouContextual Considerations for the ReaderContext of UseData
Knowledge Before StructureAvoiding TMI
Choosing Appropriate Visual EncodingsNatural OrderingColor is not orderedDistinct ValuesRedundant EncodingDefaults versus Innovative FormatsReaders’ ContextTitles, tags, and labelsColorsColor blindnessDirectional orientationCompatibility with RealityDirection and realityPatterns and ConsistencySelecting StructureComparisons Need to CompareSome Structures Are Just Inherently BadSome Good Structures Are Often AbusedKeep It Simple (or You Might Look) Stupid
Position: Layout and AxesPosition Is Your Most Powerful EncodingConsider placement firstThe Meaning of Placement and ProximitySemantic Distance and Relative ProximityAbsolute PlacementRepresentation of Physical SpaceLogical Relationships versus Physical RelationshipsPatterns and Grouped ObjectsPatterns of Organization (and More!)Specific Graphs, Layouts, and Axis StylesQuantitative and comparative formatsRelational formatsSpatial formatsAppropriate Use of Circles and Circular LayoutsGood uses of circles and circular layoutsBad uses of circles and circular layouts

ColorLeverage Common Color AssociationsCognitive Interference and the Stroop TestColor TheorySpatial perception of colorRGB versus CMYKSizeConveying SizeComparing SizesText and TypographyUse Text SparinglyFonts and HierarchiesBeware of All CapsAvoid Drop ShadowsShapeCultural ConnotationsIconsIllusionsLinesWhen Not to Use LinesKeys versus Direct Labeling of Data PointsPitfalls to Avoid3DPiesGradientsDrop ShadowsAny Excel DefaultsConclusion
Tools Reading List 
Determine Your Goals and Supporting DataConsider Your ReaderSelect Axes, Layout, and PlacementEvaluate Your Encoding EntitiesReveal the Data’s RelationshipsChoose Titles, Tags, and LabelsAnalyze Patterns and Consistency

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About the Authors

Noah Illinsky has spent the last several years thinking about effective approaches to creating diagrams and other types of information visualization. He also works in interface and interaction design, all from a functional and user-centered perspective. Before becoming a designer he was a programmer for several years. He has a master's in Technical Communication from the University of Washington, and a bachelor's in Physics from Reed College.

Julie Steele is an Editor at O'Reilly currently working on titles related to Python, SQL, PHP, web frameworks and CMS, databases (relational and non-relational), big data and cloud computing, and data visualization. She's also interested in data transparency and open government, and recently completed a master's degree in political science at Rutgers University.