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1、IsWhatYouSee,WhatYouGet?GeospatialVisualizationsAddressScaleandUsabilityAashishChaudharyandJeffBaumesUnlimitedgeospatialinformationnowisateveryone’sfingertipswiththeproliferationofGPS-embeddedmobiledevicesandlargeonlinegeospatialdatabases.Tofullyunderstandthesedata
2、andmakewisedecisions,morepeopleareturningtoinformaticsandgeospatialvisualization,whichareusedtosolvemanyreal-worldproblems.Toeffectivelygatherinformationfromdata,it’scriticaltoaddressscalabilityandintuitiveuserinteractionsandvisualizations.Newgeospatialanalysisandv
3、isualizationtechniquesarebeingusedinfieldssuchasvideoanalysisfornationaldefense,urbanplanningandhydrology.WhyHavingDataIsn’tGoodEnoughAnymorePeoplearerealizingthatdataareonlyusefuliftheycanfindtherelevantpiecesofdatatomakebetterdecisions.Thishasbroadapplicability,f
4、romfindingamovietowatchtoelectedofficialsdecidinghowmuchfundingtoallocateforanagingbridge.Informationcaneasilybeobtained,buthowcanitbesorted,organized,madesenseofandactedon?Thefieldofinformaticssolvesthischallengebytakinglargeamountsofdataandprocessingthemintomeani
5、ngful,truthfulinsights.Ininformatics,twomainchallengesarisewhencomputerstrytocondenseinformationdowntomeaningfulconcepts:disorganizationandsize.Someinformationisavailableinneat,organizedtables,readyforuserstopullouttheneededpieces,butmostisscatteredacrossandhiddeni
6、nnewsarticles,blogpostsandpoorlyorganizedlists.Researchersarefeverishlyworkingonnewwaystoretrievekeyideasandfactsfromthesetypesofmessydatasources.Forexample,servicessuchasGoogleNewsusecomputersthatconstantly"read"newsarticlesandpostsworldwide,andthenautomaticallyra
7、nkthembypopularity,groupthembytopic,ororganizethembasedonwhatthecomputerthinksisimportanttoviewers.ResearchersatplacessuchastheUniversityofCalifornia,Irvine,andSandiaNationalLaboratoriesareinvestigatingthenextapproachestosortthroughlargeamountsofdocumentsusingpower
8、fulsupercomputers.Theotherobstacleisthesheervolumeofdata.It’sdifficulttouseinformaticstechniquesthatonlyworkondataoflimitedsize.Facebook,Googlean
