Spatial-temporal Variation based Innovation History Visualization: A Case Study of the Liquid Crystal Institute at Kent State University [email protected],[email protected],UnitedStatesofAmericaYinZhangauthor.email@domain.comKentStateUniversity,UnitedStatesofAmericaXinyueYexinyue.ye@gmail.comKentStateUniversity,[email protected],UnitedStatesofAmerica
Innovationbegantakingrootasatermassociated
with scienceand industry in thenineteenthcentury,matchingtheforwardmarchoftheIndustrialRevolu-tion, although the language of that period focusedmorestronglyontheinvention,particularlytechnicalinvention(Green,2013).Nowadays,innovationisde-finedsimplyasa“newidea,device,ormethod”(Wik-ipedia). In the Big Data era, innovation history re-searchnotonlyshowstherawdatabutalsodemon-stratesandrevealsthedeeprelationshipsofdataandhowtheinnovationwasgenerated.
Thispostermainlydescribesaninnovationhistoryanalysis system, integrating and visualizing multi-source and isomerism data in a static and dynamicrepresentationmanner,consideringspatial-temporalfactors. A case study of the Liquid Crystal Institute(LCI) at Kent State University is presented. LiquidCrystalInstitute(LCI)wasfoundedin1965byGlenn
H.Brown,achemistryprofessoratKentStateUniver-sity.Thebirthplaceofliquidcrystaldisplays(LCD),theLCIistheworld’sfirstresearchcenterfocusedonthebasicandappliedscienceof liquidcrystals.Thedra-maticriseoftheliquidcrystaldisplay(LCD)industrythrough the subsequent 40 years has fundamentallychangedourmodernlife.
As shown in Figure 1, to research the innovationhistoryofLCI,therearevarietiesofdatasourcesintheformsofaudio,video,digitalizedimages,textfromthewebsite, annual reports from1965-2013, interviewswith key researchers in LCI, booklets from LCI’s 50yearanniversarythatcoverssignificantscientistsandimportantevents,aswellasbiennialInternationalLiq-uid Crystal Conference (ILCC) materials about thelargestacademicmeetinginthefieldofliquidcrystalsthatwasstartedbytheLCIfoundingdirectorGlennH.Brown in 1965. At the data processing level, datasearchingrulesrelatedtothepublications,grants,andpatentsareappointed.Fortext,textminingtools,suchasOpenCALAISandCogitoIntelligenceAPI,areusedto extract people, locations, and event informationfromannualreports,bookletsetc.Aftertheinitialpro-cessingof rawdata,dataare then imported intooursystem, including publications records, grants, pa-tents, inventions,researchers(suchasresearchstaff,post-doctoral fellows, visiting scholars, etc.), specialevents,spin-offs,andconferences.
Figure 1. Structure of LCI innovation system
AsarguedbyRobertE.Williams(Williams,1987),
locationcanbethecriticallinktointegratingdatafromvarioussourcesandwithvariousattributesofaplace.Usinglocationsasthekeylink,anylocation-relatedde-scription,fromtheformalcoordinatesofplacestotheinformalabstractionofplaces,canbeunderstoodbyusingGISandvarioustypesofBigData.Thus,thesys-temgeocodedthedatawhichhaslocationinformation.Besidestraditionaldatastatisticsmethods,withgeo-locateddata, spatial statisticsalgorithmscanalsobe
importedtooursystemtofindthespatialcorrelationofdata.
Data visualizations are used to demonstrate theworldwideimpactofLCIrelatedscientists, technolo-gies,andevents.Unlikeothertools,suchasthe“His-torical Data Exploration Tool” (Škvrňák and Mertel,2016),thissystemwillstaticallyvisualizetime,spaceandnetworkvariables,whilstalsoconsideringthedy-namicnetworkchangesineachperiod.Furthermore,spatial-temporalanalysisalgorithmswillbeimportedtodisplaythespatialandtemporalpatternofLCIde-velopment.Figure2showsvisualizationresultsbasedonthegatheredandprocesseddata.Itisdevelopedbymodern web technologies (html5 canvas, javascript,d3–seeBostocketal,2011;timeglider).Inthecentertop, there’s a timeline integrating important facultymembers, inventions, personal prizes, spin-offs, andothergreateventssince1965.
Figure 2. Main interface of innovation history research
system
Scientific collaboration is a complex social phe-nomenon in a search that has been systematicallystudied since the 1960s (Noldus and Van Mieghem,2015).OneofthegoalsofdevelopingthissystemistofindouthowtheLCIcanbesosuccessfulinliquidcrys-talfieldresearchanddevelopment.Fromtheviewofresearch collaborations, it may demonstrate the an-swers.Thus,thesystemprocessesthedatarelatedtopapers,patentsandgrants,andvisualizethecollabo-rationnetworksshowninFig.3.Ontheleftofthefig-ure,itdemonstratesthenetworks,inwhicheachnodeindicatesanauthor(inventororgrantrecipient)andeach link indicates the collaboration.On the right, itpresentsthedetailedinformationofresearcherwhenclickingonthenode.
Figure 3. Collaboration visualization of patent awardees
This systemcanbeusednotonly to further rele-vanthistorical researchbutalso toserveasaproto-typetodemonstratethepotentialforlinkingdifferentvisualizationtechniquestoprovidefunctionsfacilitat-ing historical data exploration. Furthermore, it pro-videscollaborationnetworkanalysisenvironmenttodigoutnewfindingsininnovationhistory.
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