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Motivation
DataVisualizations
RendezView Interface
research
edinburghdata.intensive
Acknowledgments
Theprimaryvisualizationisa,implementedusingThree.js5 and
GeoJSON2 data.GeospatialdataisrepresentedintheX-Y(red/blue)dimensions,whiletemporaldataisrepresentedintheZ(green)dimension.Eachcubemappedontoprepresentsamatchingrowfromthedatabase.
The showsthefrequencyofkeywordsandhashtagsusedinconjunctionwiththesearchedonkeyword.Itupdatestoincludetheaggregateofallwordfrequencyinformationwhenmultipleboxesareselected.ThiswasimplementedusingD3.js1.
The consistsofnodesandlinks,wherenodesarekeywordsandlinksaregeospatial-temporalintersectionsbetweenkeywords.Thewidthofthelinksshowstheflowquantity,whichisthemeasureoftheintersectionoftheboxesinthe3Dmap.ThisisbasedonaD3Sankeyplugin.
Todevelopaweb-basedinterfaceforvisualdatamining3 toextendthefunctionalityofthepreviousSophy4 framework:• Implementmultiple,interactivedata
visualizations:geo-spatial,time,&topicdata.• Improveuserinteractioncoupledwithdata
miningprocesses:datafiltering,selection,aggregation,etc.
RendezView:AnInteractiveVisualMiningToolforDiscerningFlockRelationships
inSocialMediaDataMelissaBica1 and Kyoung-SookKim2
1DepartmentofComputerScience,UniversityofColorado,Boulder,CO2ArtificialIntelligenceResearchCenter,AIST,Tsukuba,Japan
2
3
4
1
FutureImprovements
• Connectiontolivedatabase.• Sankeydiagramfunctionalityandinteractionwith3Dmap,includingoptiontoviewlinkwidthsaccordingtovariousaggregationtypes.
• Front-endperformanceimprovements.
Figure1. TheabovescreenshotshowstheUIlayout,design,andfunctionalitiesoftheRendezView framework.(1) Theuserinputstheiroptionsforfiltering thedatatodisplay.(2) Databaseentriesthatmatchtheselectedfiltersarerepresentedonthe3Dmapascubes.Eachcube’sposition,dimensions,andcolorcorrespondtogeospatial,temporal,and/ortopicmetadata.(3) Additionalvisualizationsappearwhenboxesareclickedon.Theseincludeawordcloud,a2Dmaptomoreclearlyshowgeospatialdimensions,andlabelsdisplayingthetimerangeoftheselecteddata.(4) ASankeydiagramshowsflockrelationships betweenkeywords.Theusercanclickonlinksbetweenkeywordstodisplaygeospatialtemporalintersectionsofthosekeywordsonthe3Dmap.
Summary
References
[1]D3:http://d3js.org/[2]GeoJSON:http://geojson.org/[3]Keim D.InformationVisualizationandVisualDataMining.2002.[4]KSKim,HOgawa,ANakamura,IKojima.Sophy:aMorphologicalFrameworkforStructuringGeo-referencedSocialMedia.2014.[5]ThreeJS:http://threejs.org/
TheauthorsofthisprojectthankthePartnershipinInternationalResearchandEducation(PIRE)program,theOpenScienceDataCloud(OSDC),theNationalInstituteforAdvancedIndustrialScienceandTechnology(AIST),andtheNSFfortheirsupport.Additionally,wethankDr.BobGrossman,Dr.MariaPatterson,andDr.JasonHaga fortheirguidance.
RendezView isaninteractive datavisualizationframeworktoshowflockpatterns andrelationships incomplexdata,particularlydatafromsocialmediaplatformssuchasTwitter.“Flock”referstotheclusteringofsimilardata.Themultipleinteractivevisualizationsallowuserstoassessmanylevelsofrelationshipsintheirdataandeasilydetectpatternsthatwouldnotbeevidentinadatabasealone.ItisbuiltinHTML5,CSS,andJavaScript.
InteractiveVisualDataMining
Figure2. RendezView isatoolforvisualdatamining:theprocessofdetectingpatternswithinbigdatausingvisualizations.Thisdiagramshowshowdataisrepresentedandtheinteractionsbetweenthevisualizations.
UseCases
RendezView canbeusedtoinvestigatedifferentsocialphenomenaoverageographicregion,suchasinformationflowindisastersandothercrisisevents,patternsinworkandhiring,ortrendsinpoliticaldiscourse,byiterativelyusingresultsfromeachvisualizationtoinformsubsequentinteractionswiththedata.Asanexample,asocialscientistcancomparetheflockpatternofjobpostingsbetweentheeastandwestcoastsintheUSbysearchingonthekeyword“work.”Theresearcherlooksatwhichkeywordshaveasimilarpattern,suchas“apply”and“hire.”TheSankeydiagraminformsthenextkeywordsearchbasedonstrongspatiotemporalco-occurrencefrequencywiththeoriginal.