5.2 – Information Visualizationrensink/courses/psyc579/05.2...• “Which Blair” Project –...

February15,2018 Psych549:InformationVisualization 1

5.2–InformationVisualization

Inclasspresentation

Psych549:PerceptionMadisonElliott

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PresentationOutline

1.  Whydowevisualizedata?– Externalcognition– Knowledgecrystallization– Discovery

2.  Howdowevisualizedata?– Limitations– Humancentereddesign– Basicvisualencodingprinciplesandapproaches

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1-Whydowevisualizedata?

•  Externalcognition(Scaife&Rogers,1996)– Usecognitiveartifactsandtheexternalworldtoincreaseourinternalcognitiveabilities

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Whydowevisualizedata?

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6WaysthatVisualizationsAmplifyCognition

1.  Increasingthememoryandprocessingresourcesavailabletotheusers

2.  Reducingthesearchforinformation3.  Usingvisualrepresentationstoenhancethe

detectionofpatterns4.  Enablingperceptualinferenceoperations5.  Usingperceptualattentionmechanismsfor

monitoring6.  Encodinginformationinamanipulable

medium

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Whydowevisualizedata?

•  Knowledgecrystallization(Card,etal.)– Gatherinformation– Makesenseofitwithrepresentationalframework

– Packageresultsforcommunicationoraction

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Levelsatwhichvisualizationcanbeused…

•  Infosphere•  InformationWorkspace•  VisualKnowledgeTools•  VisualObjects

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Discovery/VisualSenseMaking

•  Complexloopsofinteractionsbetweendata,visualization,andcognition

•  Canuseimaginationandexplorationtoleveragevisualizationanddiscovernewideas– useexternalworldtoincreaseourabilitytothink

•  Usevisualizationasexternalmemory

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2-Howdowevisualizedata?

•  Quickhistory…– Originatedlargelyincomputergraphics/statisticalgraphics

–  Developedforsituationswhereaproblemisnotwell-definedenoughforacomputertohandleinabsoluteterms,oralgorithmically

– Earlyrecognitionthatweneedtotakehumanperceptualsystemintoaccountwhendesigningvisualizations

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Howdowevisualizedata?

•  CapacityLimitations:1.  Computational2.  Perceptual/Cognitive3.  Display

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TypesofData

•  Consideratable…– Rows=Items– Columns=Dimensions

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TypesofData

•  Threedimensions:1.  Quantitative2.  Ordered3.  Categorical

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TypesofData

•  Relationaldata…– Graphs

•  Networks(node-linkdiagrams)•  Trees

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HumanCenteredDesign

•  Taskcharacterization•  Taskabstraction• Techniqueandalgorithmdesign• Validation

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HumanCenteredDesign

•  Actuallythreeindividualdesignproblems•  Eachlevelcontainspitfalls&threatstovalidity•  Eachlevelisdependentontheother– Outputsfromupstreamlevelsbecomeinputsfordownstreamlevels

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VisualEncodingPrinciples

•  Marks– Dot=0D– Line=1D– Area=2D– Volume=3D

•  Channels– Position– Size– Color– Shape– Orientation– Motion– Etc…

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FromVisualAnalysis&Design(Munzner,2014)

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FromMackinlay(1986)

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FromVisualAnalysis&Design(Munzner,2014)

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ToolsforColorMapping

•  ColorBrewer–colorbrewer.org•  “WhichBlair”Project–Rogowitz&Kalvin(2001)

•  Vischeck–vischeck.com

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High-leveladvice

•  Avoid3D,if2Dsolutionexists•  Textlabelsshouldbeuseful(canbecrucial)

•  MASSIVEspaceofdesignpossibilities/alternatives– Beawareoftradeoffs(theyareabundant)–  Lotsofresearchandmistakestolearnfrom(i.e.,avoidrandomwalkthroughparameterspace)

–  Iterateandrefine

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vanWijk&vanSelow(1999)

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DesignMantraforInteractivity

“Overviewfirst,zoomandfilter,

thendetailsondemand”–Shneiderman(1996)

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DataReduction

•  Overviews+aggregation(drilldown)•  Filtering+navigation(zooming)•  Focus+context(fisheyelens)•  Dimensionalityreduction(MDS;tSNE)

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Endlessdesignpossibilities

•  Beststartingplaceischeckingoutwhatothershavealreadydone/howtheyhavehandledagivenproblem

•  Additionalreferences…– DesignStudies(developedbyTMunzner)–  IEEEVisualizationconference– PerceptualEdge.com– Eagereyes.org

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Questions?

Thanksforlistening!