Data Visualization Manuela Aparicio Instituto Universitario de Lisboa (ISCTE-IUL)
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Carlos J. Costa Instituto Universitario de Lisboa (ISCTE-IUL)
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Introduction Humanȱmindȱisȱveryȱvisual;ȱdataȱvisualizationȱisȱanȱancientȱneed.ȱ Sinceȱhumansȱstrivedȱforȱsurvivalȱtheyȱdepictedȱhuntingȱstrategiesȱ onȱcavesȱwalls,ȱtheyȱalsoȱkeptȱstatisticsȱofȱhowȱmanyȱanimalsȱandȱofȱ whatȱkindȱtheyȱcaughtȱonȱdwellings.ȱInȱtheȱhistoryȱthereȱareȱofȱ visualsȱalphabets,ȱlikeȱPhaistos,ȱSumerian,ȱAssyrianȱcuneiform,ȱ wereȱbasedȱonȱvisualsȱratherȱthanȱonȱsounds.ȱThen,ȱEgyptiansȱandȱ Mayaȱcivilizations,ȱcreatedȱpictographicȱimagesȱtoȱcommunicateȱ withinȱsocialȱclassesȱandȱacrossȱgenerations.ȱForȱstrategicallyȱ purposes,ȱmapsȱwereȱusedȱtoȱdepictȱaȱkingdoms´ȱrichness.ȱTheȱ mostȱantiqueȱmapȱdatesȱfromȱ2500ȱB.C.ȱfromȱtheȱcityȱofȱGaȱSurȱatȱ Nuziȱ(Mesopotamian)ȱwhichȱdescribesȱtheȱEuphratesȱriverȱsidedȱbyȱ twoȱmountains.ȱHomeroȱmapȱ(Homero,ȱ900BC)ȱorȱPtolemyȱmapȱ (Ptolemy,ȱ200AD)ȱareȱalsoȱveryȱwellȱknownȱasȱtheȱmostȱimportantȱ mapsȱofȱtheȱancientȱworld.ȱInȱtheȱsixteenȱcenturyȱ(1502)ȱinȱtheȱ Portugueseȱdiscoveriesȱtheȱkingdomsȱrichnessȱandȱterritoriesȱwereȱ depictedȱasȱshownȱinȱtheȱCantinoȱmap.ȱLater,ȱinȱtheȱeighteenȱ century,ȱWilliamȱPlayfair,ȱcreatedȱvariousȱtypesȱofȱdiagramsȱtoȱ depictȱstatisticalȱinformation,ȱheȱwroteȱaȱbookȱapplyingȱthoseȱ representationsȱtechniquesȱ(Playfair,ȱ1805).ȱInȱourȱeraȱinȱtheȱ70´sȱtheȱ firstȱinfographicsȱappearedȱinȱjournalsȱandȱmagazinesȱinȱorderȱtoȱ summarizeȱinformationȱandȱcreateȱaȱgreatȱimpactȱinȱaȱmassiveȱway.ȱ Severalȱpractitionersȱandȱacademiciansȱinȱdiverseȱareasȱneedȱtoȱ presentȱdataȱgraphically.ȱFromȱgeographers,ȱtoȱeconomists,ȱ military,ȱstatisticians,ȱengineers,ȱbiologists,ȱtoȱmanyȱothersȱfields,ȱ manyȱprofessionalsȱneedȱtoȱseeȱandȱunderstandȱdataȱgraphically.ȱInȱ
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thisȱcontext,ȱitȱisȱvirtuallyȱimpossibleȱtoȱrelateȱtoȱaȱparticularȱfield.ȱ Onȱtheȱotherȱhand,ȱtheȱuseȱofȱseveralȱdisciplinesȱinȱtheȱdesignȱofȱ dataȱvisualizationȱartifactsȱisȱaȱreality.ȱInȱfact,ȱtheȱuseȱofȱprinciples,ȱ concepts,ȱtechniquesȱandȱtheoriesȱcomeȱfromȱmultipleȱ backgrounds:ȱprogramming,ȱwebȱdesign,ȱsemioticȱorȱpsychology.ȱȱ Theseȱareasȱgiveȱanȱimportantȱcontributeȱtoȱtheȱprocessȱofȱ transformingȱdataȱintoȱunderstandableȱinformation;ȱtheseȱareasȱ complementȱeachȱother.ȱ
Many knowledge fields contribute to data visualization Dataȱvisualizationȱisȱaȱfieldȱthatȱhasȱinputsȱfromȱmanyȱdisciplines.ȱ Psychologyȱstudiesȱdataȱperception,ȱorȱtheȱimpactȱofȱsomeȱelementsȱ onȱperception,ȱsuchȱasȱcolorsȱandȱshapes.ȱComputerȱscienceȱandȱ statisticsȱdevelopedȱseveralȱnewȱareasȱlikeȱmachineȱlearningȱandȱ dataȱminingȱtechniques.ȱGraphicalȱandȱmultimediaȱdesignsȱareȱ criticalȱtoȱbuildingȱinfographicȱdashboards.ȱItȱmayȱbeȱmaterializedȱ inȱtheȱproductionȱofȱinfographicsȱandȱdynamicȱdashboards.ȱTheseȱ dashboardsȱareȱmaterializedȱinȱseveralȱelements:ȱdata,ȱscales,ȱlines,ȱ bars,ȱandȱcoloredȱshapedȱsizes.ȱFewȱ(2004)ȱreferredȱtoȱtheseȱ elementsȱbyȱspecifyingȱthatȱdataȱaimsȱtoȱmeasureȱthingsȱ (quantitativeȱdata)ȱandȱtoȱclassifyȱ(categoricalȱdata).ȱScales,ȱonȱtheȱ otherȱhand,ȱcanȱbeȱnominal,ȱordinalȱandȱinterval.ȱNominalȱscalesȱ haveȱnoȱparticularȱorder;ȱtheyȱcanȱbeȱrepresentedȱtoȱcategorizeȱaȱ populationȱforȱinstance.ȱOrdinalȱscalesȱhaveȱanȱintrinsicȱorder;ȱ usuallyȱnumericalȱandȱintervalȱscalesȱareȱaȱresultȱfromȱquantitativeȱ andȱordinalȱscales.ȱLinesȱareȱusedȱtoȱrepresentȱconnectionsȱorȱseriesȱ ofȱpoints.ȱLinesȱhelpȱtheȱaudienceȱtoȱunderstandȱtheȱtrendȱforȱ example.ȱBarsȱhaveȱaȱvisualȱimpactȱonȱweightsȱofȱsomeȱ phenomena,ȱdividingȱthatȱphenomenaȱinȱgroupsȱandȱgivingȱ differentȱperceptionȱonȱquantitativeȱmeasuresȱorȱquantitativeȱdata.ȱ Theȱuseȱofȱshapesȱandȱcolorsȱalsoȱhelpȱtheȱaudienceȱtoȱinterpretȱ qualitativeȱvalues,ȱratherȱthatȱquantitativeȱdata.ȱAlthoughȱshapesȱ andȱcolorsȱareȱimportantȱinȱinfographics,ȱwhenȱusingȱitȱoneȱmustȱ payȱattentionȱtoȱavoidȱsomeȱpitfalls.ȱForȱexample,ȱtheȱmisuseȱorȱ overusingȱofȱcertainȱcolorsȱmayȱhaveȱaȱcontraryȱeffect,ȱtheyȱmightȱ misleadȱtheȱinterpretation.ȱAnotherȱcommonȱpitfallȱisȱtoȱhighlightȱ theȱunimportantȱinformationȱratherȱthanȱfocusȱtheȱattentionȱonȱtheȱ
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aimȱofȱtheȱmeasuredȱrealityȱ(Fewȱ2012).ȱInȱSIGDOC,ȱthisȱisȱnotȱaȱ newȱsubject.ȱInȱtheȱcontext,ȱofȱdesignȱofȱcommunicationȱandȱ technicalȱdocumentationȱcommunity,ȱseveralȱauthorsȱstudiedȱthisȱ subjectȱe.g.ȱZimmermannȱ(1997);ȱStamey,ȱHoneycuttȱandȱBlanchardȱ (2005);ȱ(Durão,ȱ2014)ȱandȱ(Costa,ȱBofill,ȱBaptista,ȱNeves,ȱ&ȱDurão,ȱ 2014).ȱ
Trends Inȱwhatȱconcernsȱdataȱvisualization,ȱweȱidentifyȱtheȱfollowingȱ trends:ȱtheȱsubjectȱisȱagainȱaȱfashionable,ȱinfographicsȱ generalization,ȱmobility,ȱsocialȱmedia,ȱgeolocalization,ȱdataȱ mashups,ȱbigȱdata,ȱglobalizationȱandȱscienceȱcommunication.ȱThisȱ isȱaȱsubjectȱthatȱisȱanalyzedȱforȱmanyȱyears.ȱInȱfact,ȱgoogleȱsearchesȱ showȱthatȱdataȱvisualizationȱwasȱmanyȱsearchersȱseveralȱyearsȱagoȱ andȱdecreased.ȱNowȱtheȱnumberȱofȱsearchesȱisȱalsoȱincreasingȱ again.ȱWeȱmayȱverifyȱthatȱthereȱisȱaȱuȬshapeȱofȱtheȱGoogleȱsearchȱ graph.ȱNowadaysȱalsoȱscienceȱusesȱinfographicsȱinȱtheȱattemptȱtoȱ reachȱmoreȱpeopleȱandȱtoȱsimplifyȱtheȱcommunication,ȱbridgingȱ differentȱknowledgeȱbackgroundsȱandȱcultures.ȱInȱsmartphones,ȱ iconsȱareȱsimplifiedȱandȱunderstandableȱbyȱmillionsȱofȱusersȱinȱ similarȱways.ȱInfographicsȱimproveȱourȱmobility.ȱNowadaysȱcitiesȱ haveȱmanyȱinfogramsȱtoȱhelpȱpeopleȱinȱtheirȱtransportation,ȱforȱ example,ȱtrafficȱsignals,ȱcomplexȱsubwayȱorȱrailwaysȱmaps.ȱSocialȱ mediaȱproduceȱaȱlargeȱquantityȱofȱdata,ȱmostȱofȱitȱunstructuredȱ data.ȱEveryȱparticipationȱofȱeveryȱpersonȱisȱgeneratingȱdataȱtoȱbeȱ captured,ȱtreated,ȱanalyzed,ȱandȱmanyȱtimesȱdistributedȱandȱ presentedȱvisually.ȱSocialȱmediaȱareȱprovidingȱnewȱdataȱonȱhowȱ peopleȱfeel,ȱalmostȱaboutȱanything.ȱWeȱareȱmobileȱsensorsȱacrossȱ theȱworldȱprovidingȱgeolocatedȱinformationȱaboutȱtraffic;ȱdiseasesȱ spread,ȱplacesȱwhereȱweȱhaveȱbeenȱonȱholidaysȱamongȱotherȱ subjects.ȱMashupsȱcombineȱvariousȱtypesȱandȱsourcesȱofȱ information.ȱInȱourȱsocietyȱweȱhaveȱaȱneedȱtoȱoverviewȱmanyȱmoreȱ informationȱsources,ȱinȱorderȱtoȱdoȱsoȱmashupsȱdisplayȱvisuallyȱ manyȱcombinationsȱofȱfacetedȱinformationȱbits.ȱWithȱtheȱvelocity,ȱ variabilityȱandȱhugeȱvolumeȱofȱdataȱonȱtheȱInternetȱcomingȱfromȱ ourȱeveryȱdetailedȱactivityȱweȱproduceȱaȱhumongousȱquantityȱofȱ data.ȱBigȱDataȱusesȱtheȱmostȱexquisiteȱdashboardsȱtoȱhelpȱusȱonȱ decisionȱmaking.ȱInȱourȱvirtualȱcommunitiesȱandȱdigitalȱsocialȱ
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networks,ȱweȱoftenȱuseȱstandardizedȱsymbols/smileyȱtoȱexpressȱ emotions.ȱIndividualsȱshareȱpicturesȱtoȱletȱtheȱworldȱknowȱourȱ likesȱandȱdislikes.ȱImagesȱareȱlikedȱmanyȱmoreȱtimesȱonȱsocialȱ mediaȱmoreȱthanȱtext.ȱWeȱcommunicateȱthroughȱimagesȱacrossȱ groupsȱofȱdifferentȱcountriesȱandȱyetȱweȱfindȱaȱwayȱtoȱbecomeȱ understandableȱdespiteȱlanguagesȱandȱcultures.ȱScienceȱaimsȱtoȱ solveȱhumankindȱproblemsȱandȱbringȱbetterȱsolutionsȱtoȱourȱworld.ȱ Inȱorderȱtoȱdoȱso,ȱscientistsȱmustȱcommunicateȱwithȱeveryoneȱonȱ simplerȱandȱquickȱbases.ȱWeȱexperienceȱtheȱtrendȱofȱscientificȱ infographicsȱreachingȱeveryȱofȱusȱinȱanȱefficientȱwayȱandȱbringingȱ moreȱunderstandableȱrealitiesȱtoȱeveryone.ȱAȱnewȱtrendȱinȱscienceȱ isȱtoȱproduceȱgraphicalȱabstractsȱandȱmultimediaȱcontentsȱtoȱ accompanyȱtheȱarticles,ȱitȱallowsȱtheȱreaderȱtoȱgetȱanȱoverviewȱofȱ theȱstudyȱinȱaȱglimpse.ȱȱ
Data Visualization Tools Dataȱvisualizationsȱtoolsȱareȱusedȱinȱindustryȱtoȱsupportȱdecisionȱ makingȱandȱalsoȱinȱacademia.ȱInȱtheȱbusinessȱanalyticsȱ visualizationȱareȱmostȱusefulȱtoȱfullyȱmonitorȱallȱtheȱactivitiesȱandȱ alsoȱtoȱundertakeȱdecisionsȱinȱtime.ȱInȱindustry,ȱanalyticsȱisȱveryȱ usefulȱtoȱunderstandȱtheȱcompany’sȱmarketȱposition.ȱAsȱanȱ example,ȱcompetitiveȱintelligenceȱmeasuresȱmultipleȱopinions,ȱ customers,ȱpotentialȱmarket,ȱcompetitors,ȱtoȱreachȱstrategicȱearlyȱ warnings.ȱInȱacademiaȱthereȱareȱexamplesȱofȱdataȱvisualizationȱthatȱ measureȱtheȱmostȱcitedȱjournalsȱbyȱsubjectȱareasȱandȱcategories,ȱbyȱ countriesȱorȱtheȱinstitutionsȱrankingȱȱ
Conclusions Dataȱvisualizationȱchangesȱtheȱwayȱpeopleȱexperienceȱinformationȱ andȱtheȱwayȱweȱlive.ȱInȱwhatȱconcernsȱdataȱvisualization,ȱweȱ identifyȱtheȱfollowingȱtrends:ȱtheȱsubjectȱisȱagainȱaȱfashion,ȱ infographicsȱgeneralization,ȱmobility,ȱsocialȱmedia,ȱgeolocalization,ȱ dataȱmashups,ȱbigȱdata,ȱglobalizationȱandȱscienceȱcommunication.ȱ ThisȱisȱaȱsubjectȱalreadyȱstudiedȱinȱtheȱSIGDOCȱcommunityȱforȱ severalȱyears.ȱNowȬaȬday,ȱdataȱvisualizationȱisȱincreasingȱinȱmanyȱ fields,ȱlikeȱscienceȱcommunication.ȱ
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References Costa, C. J., Bofill, D., Baptista, J., Neves, M., & Durão, R. (2014). Perspectives on Design of Communication. In Proceedings of the International Conference on Information Systems and Design of Communication (pp. 177–177). New York, NY, USA: ACM. doi:10.1145/2618168.2618199 Durão, R. (2014). Communicating Science and Technology Visually. In Proceedings of the International Conference on Information Systems and Design of Communication (pp. 165–165). New York, NY, USA: ACM. doi:10.1145/2618168.2618195 Few, S . (2004). Eenie, Meenie, Minie, Moe: Selecti ng the Right Graph for Your Message, September 18, 2004, Perceptual Edge http://www.perceptualedge.com/articles/ie/the_right_graph.pdf Few, S. (2012). Show Me the Numbers: Designing Tables and Graphs to Enlighten (2nd ed.). Analytics Press, USA. Playfair, W. (1805). An Inquiry into the Permanent Causes of the Decline and Fall of Powerful and Wea. Retrieved October 22, 2014, from http://www.gutenberg.org/catalog/world/readfile?pageno=78&fk_file s=195753 Stamey, J, Honeycutt, T and Blanchard, S. (2005). Edward Tufte meets Christopher Alexander. In Proceedings of the 23rd annual international conference on Design of communication: documenting & designing for pervasive information (SIGDOC '05). ACM, New York, NY, USA, 18-24. DOI=10.1145/1085313.1085322 http://doi.acm.org/10.1145/1085313.1085322 Tegarden, D. (1999). Business information visualization. Commun. AIS 1, 1es, Article 4 (January 1999). Zimmermann, B. 1997. Applying Tufte's principles of information design to creating effective Web sites. In Proceedings of the 15th annual international conference on Computer documentation (SIGDOC '97). ACM, New York, NY, USA, 309-317. DOI=10.1145/263367.263406 http://doi.acm.org/10.1145/263367.263406 ȱ
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