Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/44589
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dc.contributor.advisorKuijpers, Bart-
dc.contributor.authorBOLLEN, Erik-
dc.date.accessioned2024-11-04T10:57:33Z-
dc.date.available2024-11-04T10:57:33Z-
dc.date.issued2024-
dc.date.submitted2024-10-30T09:44:53Z-
dc.identifier.urihttp://hdl.handle.net/1942/44589-
dc.description.abstractIn thisthesis,weadaptandextendthetheoryoftheexistingpropertygraphdatabases to modeltransportationnetworks,wherenodesandedgescancontaintemporalproperties that aretimeseries,resultinginPropertyGraphswithTimeSeries.Weproposealanguage based onregularpropertygraphlogicforqueryingthesePropertyGraphswithTimeSeries, in whichtime-seriesandmeasurementpatternsmaybecombinedwithgraphpatternsto describe,retrieveandanalysereal-lifesituations.Further,wedemonstratethemodeland language inpracticebyleveragingtheGraphPatternMatchingLanguageasabridgebetween theory andpractice.TheproposedgraphmodelisimplementedinNeo4jwithagraph- embeddedstructureforthetimeseries.ByleveragingNeo4js’queryengine,werealise the querylanguagewithatranslationlayer.Usecasesexplorequestionsthathydrology researchersposeinthecontextofthe“InternetofWater”,electricalengineerscanposeon localdistributiongridsandrailwaymanagersconsiderindailyoperationmanagement.In addition totheanalyticalcapabilitiesprovidedbythequerylanguageandmathematical expression implementedinexistingdatabasesystems,amoreOLAP-likeaggregationand exploration mechanismisresearched.Withadefinedhierarchystructure,aggregationtrees can bebuiltontopoftheoriginaldata,allowinguserstoexploredataindifferentspaceand time levelcombinations. This way,wewanttoprovideaunifieddatamanagementsolution,includingstorageand data analysiscapabilities,thatcanbeusedbydomainexpertswithgeneraldatabaseknowl- edge. Indoingso,reducingtheset-uptimeandmaintenanceneededinresearchprojects using sensornetworksthattrytosolvetransportationnetwork-relatedresearchquestions.-
dc.language.isoen-
dc.titleGraph Database Solutions for Managing and Analysing Spatio-Temporal Data in Transportation Networks-
dc.typeTheses and Dissertations-
local.bibliographicCitation.jcatT1-
local.type.refereedNon-Refereed-
local.type.specifiedPhd thesis-
local.provider.typePdf-
local.uhasselt.internationalno-
item.fulltextWith Fulltext-
item.contributorBOLLEN, Erik-
item.embargoEndDate2029-10-17-
item.fullcitationBOLLEN, Erik (2024) Graph Database Solutions for Managing and Analysing Spatio-Temporal Data in Transportation Networks.-
item.accessRightsEmbargoed Access-
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