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As a network of connected sensors to transform data into knowledge, Urban Platforms have been rooted in several smart city projects. However, this has often resulted in them being no more than IoT dashboards. More recently, there has been an increased interest in supporting the data governance and distributed architecture of Urban Platforms in order to adjust these with the administrative structure in a specific city. In addition, Urban Platforms also deal with data roaming between different stakeholders including other cities, different government levels, companies and citizens. Nevertheless, the first deployments have led to an inflexible "smart cities in a box" approach that does not help with building digital skills and causes vendor lock-in to products that do not scale. There is a need to start with simple and widespread urban services through a collaborative joint cross-border, hands-on effort. In order to meet the level of interoperability, international standards should be adopted. The aim of an Urban Open Platform (UOP), introduced in this paper, is to support not only data acquisition but also various types of data processing: data is aggregated, processed , manipulated and extended within the city context. Conceptually, special attention has been put on scalability, roaming and reliability in urban environments. This article introduces the UOP uniquely in the cross-border data exchange context of two European capital cities, Helsinki and Tallinn, and validates it with 10 real-life urban use cases.
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Appl.Sci.2022,12,700.https://doi.org/10.3390/app12020700www.mdpi.com/journal/applsci
Article
UrbanOpenPlatformforBorderlessSmartCities
RalfMartinSoe
1
,TimoRuohomäki
2
andHenryPatzig
1,
*
1
FinEstCentreforSmartCities,TallinnUniversityofTechnology,Ehitajatetee5,19086Tallinn,Estonia;
ralfmartin.soe@taltech.ee
2
ForumViriumHelsinki,Unioninkatu24,00130Helsinki,Finland;timo.ruohomaki@forumvirium.fi
*Correspondence:henry.patzig@taltech.ee
Abstract:Asanetworkofconnectedsensorstotransformdataintoknowledge,UrbanPlatforms
havebeenrootedinseveralsmartcityprojects.However,thishasoftenresultedinthembeingno
morethanIoTdashboards.Morerecently,therehasbeenanincreasedinterestinsupportingthe
datagovernanceanddistributedarchitectureofUrbanPlatformsinordertoadjustthesewiththe
administrativestructureinaspecificcity.Inaddition,UrbanPlatformsalsodealwithdataroaming
betweendifferentstakeholdersincludingothercities,differentgovernmentlevels,companiesand
citizens.Nevertheless,thefirstdeploymentshaveledtoaninflexible“smartcitiesinabox”ap
proachthatdoesnothelpwithbuildingdigitalskillsandcausesvendorlockintoproductsthatdo
notscale.Thereisaneedtostartwithsimpleandwidespreadurbanservicesthroughacollaborative
jointcrossborder,handsoneffort.Inordertomeetthelevelofinteroperability,internationalstand
ardsshouldbeadopted.TheaimofanUrbanOpenPlatform(UOP),introducedinthispaper,isto
supportnotonlydataacquisitionbutalsovarioustypesofdataprocessing:dataisaggregated,pro
cessed,manipulatedandextendedwithinthecitycontext.Conceptually,specialattentionhasbeen
putonscalability,roamingandreliabilityinurbanenvironments.ThisarticleintroducestheUOP
uniquelyinthecrossborderdataexchangecontextoftwoEuropeancapitalcities,Helsinkiand
Tallinn,andvalidatesitwith10reallifeurbanusecases.
Keywords:smartcity;dataplatform;dataanalytics;dataproduct;digitaltwin;datamesh
1.Introduction
Thispaperismotivatedbythechallengethatthecapabilitiestocollectanduseurban
datasourcesarelow,whileatthesametimethevolumeofdataisconstantlyincreasing.
Thisalsoappliestotechnicalcompetencesfordataprocessinganddataanalysis.Thisis
accordingtoasurveyconductedwithEstonianmunicipalities(https://taltech.ee/en/finest
centreforsmartcities#p34631,accessedon6January2022)inaEuropeancountrywith
oneofthemostadvanceddigitalpublicservices,accordingtothepanEuropeanDESI
Index,whichprobablypointstotheglobalnatureofthischallenge.Inthislight,wehave
investigatedwhichdatacollectionandanalysistoolscitiescouldusetodealwiththis
problem,startingwithusecasesinEstoniaandFinland.Inaddition,theissueismuch
morecomplexwhenwestartanalysingcrossbordercitiesandtheirdataexchange,call
ingforresearchbasedsolutions.Therefore,themaincontributionofthispaperisanat
tempttobringthelevelofanalysisfromthesinglecityUrbanPlatformtothemultiple
citieslevel.
Data,includingthemeansofprocessingit,isnotanewphenomenonforcities—this
hasbeenatthecentralofurbangovernancesincetheindustrialrevolutionbeganinthe
19thcentury[1].Therefore,thekeyquestionishowitischanginginthecontextofdigital
technologiesthatareredrawingthebordersbetweencities,countriesandcompanies;at
leastthevirtualborders.Thispaperinvestigateshowdatacanbeexchanged,bothwithin
onecityandalsoacrosscitiesandtheirstakeholders.Digitaltechnologybreakthroughs
suchasFacebook,Skype,GoogleandLinkedInhaveclearlychangedtheunderstanding
Citation:Soe,R.M.;Ruohomäki,T.;
Patzig,H.UrbanOpenPlatformfor
BorderlessSmartCities.Appl.Sci.
2022,12,700.https://doi.org/10.3390/
app12020700
AcademicEditors:GianniPantaleo
andPierfrancescoBellini
Received:11November2021
Accepted:4January2022
Published:11January2022
Publisher’sNote:MDPIstaysneu
tralwithregardtojurisdictional
claimsinpublishedmapsandinstitu
tionalaffiliations.
Copyright:©2022bytheauthors.Li
censeeMDPI,Basel,Switzerland.
Thisarticleisanopenaccessarticle
distributedunderthetermsandcon
ditionsoftheCreativeCommonsAt
tribution(CCBY)license(https://cre
ativecommons.org/licenses/by/4.0/).
Appl.Sci.2022,12,7002of14
oftheworldmap:ifoneisonline,therearenoborders,atleastinonlinecommunications
services.Ontheotherhand,thepictureisdifferentifzoomedintourbanlevelswhereeach
departmentineachmunicipalitytailorsitsownelectronicservices.Localservicesareof
tendevelopedinisolationwithminimalattemptstocodesigntheservicesjointlywith
otherkeystakeholders(othercities,differentgovernmentlevels,companies,citizens,etc.).
Furthermore,digitalurbanservicesareoftendevelopedandanalysedfromthe“closed
borders”perspective,disregarding,forexample,everydaycommutersfromotherregions
andthefactthat,atleasttechnologically,servicesanddatacanbescaledoverinstitutional
borders[2].
AccordingtoEickeretal.[3],anUrbanPlatform(UP)isakeysoftwareinfrastructure
forurbanplanningandmaintenance,designedtohandleandanalyselargedatasetsfrom
differentdomains.Theauthorsarguethatthemaindrivershouldbetohelpcitiesfollow
zerocarbonstrategiesviatheinclusionofallmajorsectorsofCO2generation.Similarly,
Hernándezetal.[4]seetheendgoalofthedigitalisationofcitiesistobecomemoreenvi
ronmentallyfriendly,whichasaprocesscanbeachievedviatheOpenStandardizedUr
banPlatformwiththemainfunctionalitiesofdataingestion,analyticsandservices.Badidi
&Maheswaran[5]andChengetal.[6]putthedeploymentofsensorsasbeingmorecentral
inUrbanPlatforms’applications,withtheendgoaltoimprovethequalityoflife.The
widergoalistoenablethetransitionofcitiestomoresustainablesystems(lessCO2,more
energyefficient,moreenvironmentallyfriendly,etc.—allbetterforthecitizen).Neverthe
less,therearestillstructuralobstaclessuchasopennessandinteroperabilityinthoseUr
banPlatforms.TheissueisbroughtoutbyLee,Mackenzie,Smith,&Box[7],whomapped
100urbandatapracticesthatcontributeto“platformurbanism”bynotingaconcerndy
namicofcityadministratorstobe”lockedin”tospecificcorporateproductsandinterests.
Inaddition,Badidi&Maheswaran[5]arguethatdatainteroperabilityandintegrationis
themostchallengingsmartcityproblem.
Ingeneral,theliteratureonbigdataclassifiessourcesunderthreebroadcategories:
opportunisticsensing,purposelysensingandcrowdsensing[8].Opportunisticsensing
leveragesdatarunningonexistingsystems,suchasatelecommunicationnetwork,but
canbeusedtobetterunderstanddifferentsystems.Inotherwords,dataiscollectedfor
onepurposeandusedforanother.Thisapproachtodatacollectionismadepossible
largelybythefactthatmobilephoneshavebecomeubiquitous(www.itu.int/ITU
D/ict/material/Telecom09_flyer.pdf,accesson06January2022)—citizensreplacetheneed
forpurposebuiltsensors,contributingrealtimedatathroughtheirportabledevices.
Othertypicaldataprovidersincludecreditcardcompaniesrecordingusertransactions,
taxifleetsreportingvehicleGPSs,etc.Incontrasttoopportunisticsensing,purposely
senseddatasetsarederivedfromadhocsensornetworksconfiguredtostudyaspecific
phenomenon.Thankstoadvancesinmicroelectronicssensors,computationsarebecom
ingincreasinglyaffordableanddistributed,aphenomenonoftenreferredtoas“smart
dust”.Hence,networksofremotesensingagentscannowbeembeddedinthecityfabric
toextractlargeamountsofinformation.Thisdataischannelledintocentralcontrolsta
tionswhereitisaggregated,analysedandusedtomakedecisionsonhowthemonitored
terrainshouldberegulatedandactuated.Here,theresultingdatasetstendtobemore
uniform,withthestateduseandactualendusescenariosbetteralignedtodecodevarious
flowswithinthecity.
Ineverycity,thecompletestorycannotbetoldbyfiguresanddataalone.Toade
quatelyassessasituation,thevoiceofthecitizenmustbeheard.Eachurbanitecanbe
thoughtofasahumansensor,capableofreportingontheirexperienceofthecitythrough
contentsharingplatformssuchasFlickr,Twitter,FacebookorWikipedia[9].Theseac
tionsofferauniqueviewofhowcitizensnavigatetheirenvironment,bringingclarityto
pointsofattractionorspontaneousmigration.Thisapproachdescribesthethirddata
sourceknownascrowdsensing.Thecrowdbecomesadistributednetworkofsensorsthat
allowsunderstandingthedynamicpatternsofthecityandtheexperiencesofitscitizens
Appl.Sci.2022,12,7003of14
ataquasirealtimerate.Intheabsenceorfailureoftopdownsensornetworks,thisgrass
rootsapproachtosensingleveragesthemillionsofnewlycyberconnectedcitizenstoco
ordinatehumanactivityonanunprecedentedscale.Integratedcitiesperformwithunpar
alleledefficiency(whetherresources,transportationorinfrastructure),enabledbydigi
tallycontrolledcircuitryandvirtualoperatingsystems,ultimatelytransformingurban
spaceintoanopenlivinglab.
However,thequestionremainstowhatextentUrbanPlatformsattractparticipation
ofcitizensintheprovisionofbetterservices.Inonestudy,citizeneparticipationwaspos
itivelyassociatedwiththeclearancerateofurbanservicerequests,althoughtheeffectsize
ofparticipatoryserviceperformancevariesbetweendifferenttypesofcityservices—there
wasmoreinvolvementincomplexproblemscomparedtosimpleroutineservices[10].
Importantly,UrbanPlatformscanalsobeindependentfromthedirectroleofthecitygov
ernment.Velsberg,Westergren,&Jonsson[11]focusontheconceptof“smartness”inthe
contextofserviceprovision,reflectingtheambitionofthepublicsectortobecomemore
agileandresilientwhenapplyingnoveltechnologiessuchastheInternetofThings—also
centraltoUrbanPlatforms.
TheInternetofThings(IoT)isaconceptforconnectingvarioussensorstotheInternet
usingbigdataanalytics[12]withapplicationsinsmartcities[13];itcan,atleasttheoreti
cally,improvetheurbanservicesandreduceresourcesconsumption[14].Therearealso
papersthattakeamorecriticalorrealisticapproachbyclaimingthatbuildinglargescale
smartcityIoTplatformsremainsempiricallychallenging[15],inadditiontochallengesof
howtosolvetheprivacyrightsofresidents[16].
AccordingtoBarns[17],platformsplayagrowingstrategicroleinthedailylivesof
citiesviamatchmakingbetweensubjects,whetherformobility,accommodation,shop
pingandevendating,makingtheseplatformswiderdataecosystemsofusers,producers
andconsumers.Nevertheless,thereisalackofresearchinunderstandingtheoperational
modeloftheUrbanPlatformthathasdifferentgoalsthatalsocanbeinconflict,e.g.,city
internaloperationandserviceversuspublishingpublicdata[18].
Thisrestofthispaperisstructuredasfollows:Section2providesanoverviewofthe
visionandarchitectureofUrbanPlatforms,viaintroducingtheconceptoftheUrbanOpen
Platform;Section3appliesthistotheusecaseofthecitiesofTallinnandHelsinki;and
Section4wrapsupwithdiscussionandconclusions.
2.UrbanOpenPlatform:VisionandArchitecture
2.1.TheVisionofUrbanOpenPlatform
ThevisionoftheUrbanOpenPlatform(initiallydevelopedbyCarloRattiAssociati,
underthelabelofUrbanOperatingSystemin2016fortheH2020projectFinEstTwins)is
quitesimple.Deployinganetworkofsensorsthatcancapturerealtimedatafromamyr
iadofoccurrencesinthecityandconnectingsuchsensorstoanurbaninformationsystem
helpstobetteranalyseandtransformsuchdataintoknowledge(seeFigure1).Asaresult,
newtypesofurbanefficiencies,productsandservicesforcitydwellerscanbecreated.In
turn,userscanaccessanopenaccessdigitalservicesdeliveryplatformviaasmartphone
orlaptopallthewayuptodigitallyenhancedinfrastructuressuchasresponsivepublic
spaces,intelligenttransportsystemsorsmartenergyinfrastructure.Thecitybecomesa
permanentplatformforinteraction,providingauniquemixofservicestoeachuser.Fur
thermore,bygivingusersthecapabilitytodeveloptheirownsolutionsandservices,a
moreinclusiveandbottomupmodelofbothsocialandeconomicdevelopmentwillbe
createdwhilejumpstartinglocaldynamics.
Organisationsthatdesignsystemstendtoreflecttheorganisationalstructureinthe
architecture[19].Inadiverseorganisationsuchasacity,thishascausedchallengesin
boththeenterpriseandthedataarchitecture.Commondatawarehouseshavehadalim
itedscope,suchassupportingfinancialandHRfunctions,whiletheoperationalsystems
Appl.Sci.2022,12,7004of14
remainontheirown.Whendataplatformshavebeencreatedtosupportadvancedana
lyticsandbusinessintelligence,theoverallenterprisearchitecturehasbeensplitintotwo
mainfunctions:anoperationalplane(operationalsystems,oftenlegacy)andanalytical
plane(datawarehouses,datalakes,BI).Thelinkbetweenthetwoplaneshastypically
beenanETLprocessdefinedforeachdatapipe.Thelargertheorganisation,themore
challengingthisapproachhasbeentogovernandmaintain.Thevastamountofdatacom
inginfromIoTandautomationsystemshasalsoraisedtheconcernwhetheritisfeasible
tostoreeverythingonacentraldatalake.
AnUrbanOpenPlatformshiftsthefocusfromcentricdataplatformstowardscross
organisationalcapabilitiesandempoweringdomainspecialistswithdataacquisitionand
manipulationfunctions.Citiescannotforeseeafuturewherehundredsofdataengineers
wouldbeemployedtomanagethenewdatapipelinesrequiredforsituationalawareness.
TheplatformisacollectionofcomponentswithconnectorsandAPIsthatcanbe“wired”
togetherindifferentwaystomeetthevariousandevolvingdataintegrationandcontext
enhancementneeds.Thesetasksshouldnotrequireprogrammingexperiencebutbeavail
ablefordomainspecialistsasauserfriendly,selfserviceplatform.Thedivisionsandde
partmentsofthecitiescancontinuemaintainingtheirowndatamartsandlakes,butpol
icymanagementandadvanceddatacatalogueswithdiscoveryoptionsmakeitpossible
toadoptthelayersofdatagovernancebothattheunitandenterpriselevels.Thedata
analyticsintheoperationalplanearesupportedbystreamprocessingcapabilitiesand
datavirtualisation.Withthisapproach,itismorefeasibletoanalyselargeamountsof
data,suchasthecurrentstateofcitystreetlights,withouthavingtocreateamassivetime
seriesdatastore.Forthistobeachievable,thefollowingpropertiesmustbeinherentto
thesystem:
Figure1.TheUrbanOpenPlatform.
Architecture:Thedatamanagementlayerprovidesstandardisationandastorage
functionfortheplatform,facilitatingtheanalysisoflongtermsensordata.TheUOP
wouldbetheprimaryconductorofvariousdatastreamsusedbythevariousdigitalser
vicesbetweentwocities.
Appl.Sci.2022,12,7005of14
Integratingdatastreams:Ubiquitoussensorsandsensornetworkssuchasbuilding
automationsystemsareincreasinglyprovidingdatasourcesofdifferentcontents,formats
andqualities.Integratingdiversedatasourcesallowsdevelopingapplicationsthatwould
notbepossiblebyusingasinglesensornetwork.Whenintegratingdatafromheteroge
neoussources,syntactic,schematicandsemanticdiversitiesofthedataschemasarechal
lengingproblems.ThepastworkonIoTplatformshasevolvedintogenericcapabilities
supportingrealtimestreamandeventprocessing.ThroughanUOP,datafromdiverse
sourcesistranslatedintoacommonlanguage,APIsandvisualinterface.Thecapabilities
shiftthefocusfromrawdataacquisitiontowardsreusable,highqualitydataproducts.
Dataprocessingfunctionality:TheUOPwillofferbusinesses,citizensandgovern
mentssituationalawarenesswiththeabilitytocombinerealtimedatafromacrosssome
datastreamstocreateanuptotheminutepictureofurbanmaterialflowsanddynamics.
Inaddition,carryingdatafromproviderstoconsumers,theUrbanOpenPlatformwill
allowclientstoquicklyprocess,manipulateandvisualisethedataofdatastreams.With
thehelpofopenAPIs,applicationscanalsobepublishedandsharedamongusers.
Scalabilityandflexibility:Agiledevelopmentprocesseshavedramaticallychanged
thewaytechnologyisbeingimplemented.Shortercyclesallowsocietytoconstantlyadapt
tochangeornewconditions.Whenapplicationsandservicesaredevelopedinanagile
fashion,thearchitectureshouldbeevolvingaswell.Fordetal.[20]seethearchitectureas
aconstanteffortthatcanreactbothtochangingrequirementsbutalsotofeedbackfrom
programming.TheUOPwillbedesignedtomeetcurrentneedswithoutcompromising
theabilityoffuturegenerationstomeettheirs.Atthemoment,wecanassumethereare
hundredsofdatastreams,andwithindividualscontributing,thisnumbereasilyrisesinto
thethousands.Takingintoaccounttheoverallinputloadandthenumberofpotential
clients,aquickapproximationindicatesthatwecouldeasilyreachonemillionmessages
persecond.AnUrbanOpenPlatformwillbedesignedtoinitiallydealwithasmallload
but,atthesametime,itwillneedtobedesignedtoscaletohundredsofmachinesto
accommodatetheadditionalload.
Inhabitantsasactors:Trulysmartcitieswillemergeasinhabitantsandtheirmany
electronicdeviceswillberecruitedasrealtimesensorsofdailylife,agentsforsensingand
reportingtheirindividualexperience.Offeringarealtimeviewofhowhuman,material,
digitalandfinancialresourcestravelthroughthelandscapeoftheirdailyliveswillper
ceptuallyexpandeachcitizen’ssphereofresponsibilityfromthedomesticspacetothe
spaceofthecity,withthecitybecomingthesmartmeterofallthesefactors.Inadigitally
augmentedsmartcity,civiczonescanbetransformedintoresponsiveenvironments
throughtechnologicalmediation.Thiswouldchangethepassiveinhabitantsofthecityto
activeparticipantsofspatialscenariosandthepublicspacesfromareasoftransittourban
destinations.
2.2.UrbanOperatingSystemasaDataPlatform
InrelationtoUrbanPlatforms,therehasbeengrowinginterestinbettersupporting
thedatagovernanceanddistributedarchitecturetobestfittheneedsofhowcitiesoperate
organisationwise.Citiesareoftenseenasasingleentitywithasinglevoice,butthisis
notthecaseintermsoftheICTtoolsandplatformsthatcitiesoperateon.Thedepartments
andunitshavehadalotofindependenceintheirchoicesofsystems.Onecoreelementof
theUOPisitsabilitytohandlelegacydatasourcesandavarietyofdataformats.How
ever,thedataintegrationcapabilityisastandardrequirementonanydataplatformand
doesnotdependonnewinnovation.Forexample,theextracttransformload(ETL)isa
processthathasbeenaroundsincetheearly1970s.Whatismoredifficulttotackle,how
ever,isthegovernance,ownershipandroutesofthedatabetweenthecitydepartments,
platformsandsystemswithmultiplestakeholders.
ThepublishingofopendataonUrbanPlatformshasalsobroughtinproductthink
ing,i.e.,seeinganddevelopingtheurbandataasaproduct[21].Ingeneral,datasetsfit
wellwiththedefinitionofproduct:anythingthatcanbeofferedtoamarketforattention,
Appl.Sci.2022,12,7006of14
acquisition,useorconsumptionthatmightsatisfyawantorneed[22].Dataproductsare
ownedbyproductownerswhomayhaveawiderinterestindefiningthe“features”of
theproduct,includingdataquality,context,documentationindatacatalogues,etc.Data
productisseenasaresultofvaluedrivenanalysisthatgeneratesaddedvaluefromthe
underlyingdata(https://www.oreilly.com/radar/whatisdatascience,accessedon12
June2018)andiswellalignedwithservicedesignconcepts.Thekeymechanismofvalue
creationistocreateinsightsoutofdatausinganalyticalmethods.
Somerecenttermsintroducedindataplatformdiscussionaredatameshanddatapipe
lines.DatameshwasintroducedasaconceptbytechnologyconsultantZhamakDehghani
(https://martinfowler.com/articles/datamonolithtomesh.html,accessedon7January
2022).Herkeymessagewasthatdataplatformsbasedonthecentraldatalakearchitecture
havecommonfailuremodesthathavepreventedthemfrombeingscaledupandwidely
used.Hersuggestionwastoconsiderdatadomainswithahigherpriority,toapplyplat
formthinkingtocreateselfservicedatainfrastructureandtotreatthedataasaproduct.
2.3.TheUOP’sWorkingConcept
TheUOP’sworkingconceptappliedinthispaperisbasedonthepreviousworkof
theEuropeanInnovationPartnershiponSmartCitiesandCommunities(EIP–SCC).EIP–
SCChasdefinedsixActionClustersasitskeypriorityareas,including“IntegratedInfra
structuresandOpenData”.AgeneralobservationisthatUrbanPlatformsareaprerequi
sitetosupportfasttakeupofsmartsolutionsincitiestoallowmanystakeholderstopar
ticipate.ItisalsoexpectedthatUrbanPlatformswouldhaveakeyroleintheintegration
ofthirdpartyvendorsolutions.
TheUrbanPlatformvisionofEIP–SCCisthatby2025,300millionEUcitizenswill
beservedbyplatformswithintheircitiesand,intheshortterm,acceleratetheadoption
ofUrbanPlatformsthroughaneasytoimplementtemplateapproachandcrosssector
collaboration.Meanwhile,thecloudplatformswillhavepickedupandthepublicsector
willhavestartedtomovetheirservicesintoAWS,GoogleorMicrosoftAzurecloudser
vices.
UrbanPlatformsareexpectedtoformacorebuildingblockbywhichcitiesbetter
managethecurrentexplosioninthevolumeofcitydataandmoreeasilysharethisdata
betweencityservicesinordertoprovidemeaningfulservicestotheirresidents.Itshould
benotedthoughthattheUPisnotasingleITsystemorserver.Itisacollectionofsmart
cityservicesthatcommunicateinternallyandexternallywithharmonisedAPIs.Theplat
formshouldbedistributedanddecoupledforvariousreasons.Thecityorganisational
complexitydoesnotsupporttheideaofasingleowner,singleadministrativeplatform
buttheoperationalmodelsshouldbebasedonagovernancemodelthattakesthisinto
account.
TheUrbanPlatforminitiativewassupportedbylaunchingamemorandumofun
derstandingthathad85signatories,includingbothcity‐andsmartcityrelatedvendors.
In2016,itwasestimatedthattheUPswerefragmented,haduncertaintiesonthedemand
sideandwerelackinginteroperabilityandcommonstandardsfromthesupplierside.At
themoment,thereisstillworkrequiredonalltheseareas.
TheUrbanPlatformconcepthasevolvedthroughseveralHorizon2020andEuro
peanRegionalDevelopmentFund(ERDF)fundedprojectssuchasbIoTope,mySMART
Life,Select4CitiesandSynchroniCity.Inmanyoftheprojects,theusageofUrbanPlat
formshasfocusedonbeinganIoTplatformwithdashboards.Thesupportofspatialdata
andlargescaledatautilisationhavebeensomewhatlimitedandmanyofthepilotswere
experimentalplatformproductsthatwerenotreadynorintendedtobeinfullscalepro
ductionuse.Thelimitedvisionofthescopealsomissedtheopportunitytosupportcities
insomeoftheirnewdatarelatedresponsibilities,suchasmaintainingInfrastructurefor
SpatialInformationinEurope(INSPIRE)compliantdataservicesandprovidingsupport
forSustainableEnergyandClimateActionPlan(SECAP)reporting.TheUrbanPlatform
shouldalsonotbeseenasamonolithic,singleservicebutasadistributedanddecoupled
Appl.Sci.2022,12,7007of14
collectionofservicesthatcancomplementcities’existingdataplatforms.InbothHelsinki
andTallinn,akeyquestionishowcantheUrbanPlatformbuildontopoftheMicrosoft
Azuredatalakesanddatawarehousesthatbothcitieshavealreadyinvestedin.
2.4.UOPArchitecture
WhiletheUrbanOpenPlatformisanimplementationoftheEspressopreferencear
chitecture,basedontheH2020ESPRESSOproject,someareashaveevolvedoverthe
years.TheEspressoarchitecturewasseentodrivetowardsamonolithic,independenten
tityapproach,yetthemarkettrendsaremovingtowardsserverless,microserviceandna
noservicearchitecture.Themoderncloudarchitecturemakesithardertodescribetheen
tityasalayeredcapabilitymatrix.Eventhetypical“hamburgermodel”ofIoTplatforms
withsouthbound,datalakeandnorthboundismisleadinginmanyways,especiallyin
eventdrivenarchitecturethatIoTplatformsoftenare.Theplatformisexpectedtosupport
notonlydataacquisitionbutalsovarioustypesofdataprocessing.Dataisaggregated,
processed,manipulatedandextendedwithcontext.Bydefault,anydatacanhaveaspatial
reference—notonlyasorigindefinedwithcoordinatesbutalsowiththeabstractcity
modelfeatureasanorigin.Inaddition,realtimedatacomesinmanyforms.Compared
tootherimplementationsofanurbandataplatform,theUOPplatformisnotexpectedto
directlysupportIoTsensorconnections.Itisassumedthatnowadayspracticallyalllarge
scaleinstallationswouldconnecttotheplatformthroughgatewaysthatthesensorscon
nectwithautomationfieldbusnetworkssuchasBACnetinbuildingautomation.
TheplannedhighlevelarchitectureoftheUrbanOpenPlatform,illustratedinFigure
2,followstheconventionsofpreviousprojectssuchasH2020ESPRESSO,H2020Synchro
niCityandH2020mySMARTLife.Specialattentionhasbeenputonscalabilityandrelia
bilityinlargescaleproductionenvironments.ThenewdatastrategiesfromHelsinkiand
Tallinnhavecontributedtotheplanningandexistingenterprisearchitectureandpro
videdguidelinesonrelevantexistingtechnologiesandservicestoadoptandengage.In
bothcities,thecentraldataplatformsarebasedonMicrosoftAzure,whichnowisalsothe
basisoftheUrbanOpenPlatform.
Figure2.Componentdiagramforusecasebuildingautomationsystems.
Theopennessanddistributednatureoftheplatformcomesfromcomponentsbeing
definedforspecificfunctionality.Asanexample,thedatafusionstagecanbeimple
mentedasanETLprocess,adataintegrationtaskcreatedwithApacheCamel,datavirtu
alisationproductorsoftwarerobotics.ThebrokeringstageintheUOPisbasedonApache
Kafka,butitcouldbereplacedwithRabbitMQorcommercialbrokerorESBproducts.An
essentialfeatureoftheUOPconceptisthatthedatacataloguesanddataprocessingfunc
tionsareconnectedwiththebrokerandrouterstageandnotonthedatalake.Withthis
Appl.Sci.2022,12,7008of14
approach,dataisprocessedwhileinmotion.Thisapproachsupportsrealtimeanalytics
andvisualisationandsituationalawareness,butalsothedistributednatureoftheplat
formsincetherecanbeseveraldatabases,datamartsandlakesinsteadofonecentraldata
warehouseaccordingtotheneedsofeachbusinesscase.
Thismodularapproachalsoallowscitiestochoosevendorsandproductsthatthey
alreadyoperatewith.Theroleofopensourceisalsoaquestionthatrequiresfeasibility
analysis.IfthecityisalreadyoperatingonMicrosoftAzureorRedHatOpenStack,the
addedvalueofintroducingnewproductsdevelopedaspartofaninnovationprojectcan
bequestionableandthematurityofsuchproductscanevencauseadditionalrisks.
Duetothespatialnatureofpublicsectordataandthedigitaltwins,theprimaryAPI
fortheUOPwillbetheOGCAPIFeatures.
3.CaseStudyofTallinnandHelsinki
Thispaperappliesaqualitativecasestudymethodwheredataiscollectedfrompri
marysources(researchandinnovationprojectdeliverables,conductedbyauthorsthem
selves)andsecondarysources(previousresearchandinnovationdeliverables,suchasre
searchpapersandprojectreports).AcoremethodistovalidatetheproposedUOPcon
ceptempiricallywithreallifeandrealtimesensingusecasesimplementedinthecityof
Helsinki,withthepotentialtobereplicatedinTallinnandothercitiesglobally.
TallinnandHelsinki(twonorthernEuropecapitals)wereselectedforthefollowing
reasons:proximity(thetwocitiesarejust80kmapartbysea),highlevelcommutingfre
quency(therewere8millionpassengersbetweenTallinnandHelsinkipreCOVID19,
whereasEstonia’sentirepopulationisjust1.3million)anddigitalisation.(Finlandhasa
verystrongdigitalindustry,stronglyrootingfromNokia.Estonia,ontheotherhand,is
highlyappreciatedbecauseofitselectronicgovernment.)Economically,thecitiesarenot
the“inthesameleague”.EstoniaisapostSovietcountrystilltryingtocatchupwhereas
Finlandisawelldevelopedwesterncountry,makingthecitiesmoreheterogeneouswith
abiggerpotentialforascaleup.
3.1.DataExchangePlatformfortheCrossBorderRegion
Localgovernmentsaremoreandmoreexpectedtobeparticipatory,horizontaland
collaborativewiththehelpofdigitaltechnologies.Forexample,Lee&Lee[23]criticise
theprovider’sviewpointinprovisionofurbanserviceswhereorganisationstructuresare
constructedfortheconvenienceofadministration,insteadofcitizen,thusmakingtheser
viceprovisionvertical(e.g.,departmentsofmobilityandenvironmentandtheirdatabases
arefullydisconnected).Therefore,TallinnandHelsinki(andEstoniaandFinland,respec
tively)provideaninterestingcase,astheirpublicsectordatabasesareinterconnected(in
thecaseofEstonia)orthereareplanstoconnectthem(inthecaseofFinland),which
makesinterandintracitydataexchangepossible.Itshouldbenotedthatachievingthis
assumesachangeinorganisations’managementpracticesandlegalsetups.Whileprac
ticallycomplex,especiallywhenconsideringsocialandpoliticalresistancetochange,itis
notimpossible.
Thoughinitiatedtopdown,Estoniaasacountryisaninterestingexampleofthehor
izontalexchangeofdata,asthereisclosetofullinteroperabilitybetweenpublicsector
databasesviathedataexchangelayerXRoad,bothwithindepartmentsinonecityand
acrossallnationalcities.Forexample,thenationalpopulationregistry(whichstemsfrom
thepopulationregistryofTallinn)isfullyintegratedwithallcitiesandothergovernment
actorsinEstonia.Therefore,citiescannotkeeptheirownpopulationregistries,asthereis
onelivedatabaseforallresidentsinEstonia,andeverymunicipalitymustintegratetheir
servicesbasedonthiscentralregistry(e.g.,registrationofnewordepartingresidents).It
isimportanttonotethatXRoadisnotextraordinarybecauseofitstechnologicalfeatures
(thereareplentyofsimilarlogicenterpriseservicebusplatformsavailable)butmainly
becauseitisacaseofsuccessfulimplementation,bothorganisationallyandlegally.Essen
tially,itisarulebasedapproach,andalltheserulesneedtobedefined(e.g.,whocan
Appl.Sci.2022,12,7009of14
makeinquiriestothepopulationandtheotherthousanddatabasesandhow).Inthisper
spective,XRoadisusedasalighthousesolutionthroughoutthearticle,indicatinghow
thetwincities(HelsinkiandTallinn)couldconceptuallybenefitfromit[2,24]).TheX
RoadplatformisshowninFigure3.Briefly,inEstonia,over3000governmentsector(in
cludingallcities)databasesareinterlinkedviatheInternetusingthetransportlayer.
InspiredbyXRoad(http://epl.delfi.ee/news/eesti/soomevotabkasutuselemeiex
teesusteemi?id=67359844,accessedon6January2022(inEstonian)),Finlandisalsoim
plementingitsdataexchangelayer,withbothcountriesagreeingtodevelopafederated
solution.In2017,thisresultedintheformationofajointorganisation,TheNordicInstitute
forInteroperabilitySolutions,whichhasthemissiontodevelopfederatedegovernance
solutionsconnectingEstonianXRoadtechnologywithitsFinnishcounterpart(Palve
luväylä).Thefirstpilotsbasedonthesefederatedtwocountrydataexchangelayersare
liveandfocusontheexchangeofbusinessandpopulationdata(seespecificusecases:
PopulationRegistryandBusinessregistry).Inaddition,therearealsousecaseofsolutions
thatworkonlyinonecity/country,e.g.,SmartMetersinEstoniaandEnvironmentalSer
vicesinHelsinki.
Figure3.TheXRoadplatform.Source:EstonianInformationSystemAuthority.
Ifthefederationofdataexchangelayersbetweentwocountries(seeFigure4)was
fullyimplemented,thiswouldofferanexperimentalsettingforajointcrossbordereser
vicebetweenthetwocapitals(italsoappliestoallcitiesinEstoniaandFinland).Cur
rently,thetwocitiesstilloperateasdigitalislandsbutthefederationofdataexchange
platformscouldeffectivelyleadtojointdigitalservicesbasedonrealtimedatarequests
fromurbanandgovernmentaldatabases,hencealsobenefitingthecommutersandmacro
regions.Continuingwiththeexampleofpopulationregistry,apersonmovingfromTal
linntoFinlandcouldautomaticallymeanerasingresidencestatusinTallinnandtransfer
ringittoHelsinki.Again,theimplementationoffederateddataexchangelayersisnot
onlyatechnologicalchallenge,butthemainassumptionisthatthisispoliticallydesirable
(multiplepartiesagreeonhowdatacanbeexchangedandaremotivatedtodoso,thatis,
createnovelinstitutions).
Appl.Sci.2022,12,70010of14
Figure4.Federationofdataplatforms.Source:EstonianInformationSystemAuthority.
Thenextstepforsmartcitiescouldbetheintegrationofvarioussensordatabyim
plementinganopenandinteroperableplatformforconnectedsensorsorarangeofenti
ties.Thatis,inadditionto“citizenbased”databases,therecouldbeinterconnectedregis
tries,bothpublicandprivate,forentitiessuchasunitymeters(gas,electricity,water),
vehicles(cars,buses,trains,etc.),homeappliances,heating,lightingandwastemanage
mentsystems,weatherforecastdata,etc.InEstonia,thereisafirststeptowardsthis,
namelytheEstfeedplatform,whichconnectscloseto600,000electricityusers,withmost
endusersabletotracetheirenergyconsumptionviaconnectedmetersovertheInternet
[25].Thisplatform,runningonXRoad,linksdatasourcesandapplicationsandprovides
auserinterfaceforcustomerstoseeandmanagetheirenergyconsumptiondataand
rights.Forperfectlyfederatedsmartcities,suchafederationcouldbethenextstep,after
havingintegratedthepublicregistries.
3.2.AISolutionsfortheCrossBorderRegion
Conceptually,federateddataplatformscouldautomateprocessesradicallywiththe
applicationofartificialintelligence.Theterm“Kratt”(magicalcreatureinoldEstonian
mythology,atreasurebearer)wasintroducedinEstoniainreferencetopracticalapplica
tionsbasedonartificialintelligencetechnologies(inthenarrowmeaningofartificialin
telligence)performingaspecificfunction.ForthevisonofKratttobecomereality,several
technologicalchallengesneedtoberesolvedasmentionedinKratt’svisionpaper
(https://www.kratid.ee/visionpaper,accessedon6January2022).Inthecontextofthispa
per,mostrelevantareissueswithinteroperability.Atthisstage,itisnotevenclearwhat
willbethenecessaryinteroperabilityframework.Securedataexchangeprotocolandgov
ernancewillbenecessarytojointheAIapplicationsandvirtualassistants’functionto
getherandtransparentlybetweengovernmentagencies,betweenprivateandpublicsec
torsandalsoacrossborders.Therearealsolegacyissuesasthedevelopmenthastobe
builttakingintoaccounttheexistingEstoniangovernmentalinteroperabilityframework
andXRoaddataexchangefoundations.
Anotheraspectthatneedstobedevelopedisasocalleddigitaltwinofpeople.Itis
importanttonotethatthistwinwouldnotduplicateallofpeople’sdatabutratherwould
holddataonconsents,interactionsandotherpreferencesforpublicservicesthatpeople
havemadeasthebasisformachinetomachineinteractionandqueries.Thefutureofdig
italgovernmentthatisinteroperablewillbesubjecttoconstantchangeasbotsoragents
willbeaddedanditerated.So,theunderlyingdatasetsandITsystemshavetobeflexible
andreadyforconstantfurtherdevelopment.Thatvisioninmind,itwouldmakesenseto
Appl.Sci.2022,12,70011of14
startwithamicroservicebasedsetupofITsystemstoensureflexibilityofdevelopment
andfastscalingcapability.Evenmoreimportantisthedevelopmentofadataexchange
basedonamessagingroomsetup,whichcouldbecomeanadditiontotheEstoniancur
rentXRoadbaseddataexchange.AtthisstageitisunclearwhetherXRoad’ssynchro
nousconnectionsaresufficienttosupportparallelworkingofmanyAIapplicationsat
once.
Estoniahasmadeanexcellentefforttomakedifferentdatasetsopenlyavailableto
encouragethedevelopmentofcommercialornonprofitdigitalsolutions,conductre
searchormakedatadrivendecisions.Asof1April2021,therewere793datasetsavailable
ontheEstonianopendataportal(https://avaandmed.eesti.ee/,accessedon6January
2022).ForthesuccessfuldevelopmentofKrattAI,theavailabilityandqualityofopendata
willplayasignificantrole.Itisunclearhowmuchdataisrequiredtotrainthemachine
learningalgorithm,butdependingonthecomplexityoftheproblem,itisrealisticthat
thousandsofdatapointsmaybeneeded.Inthecaseofmachinelearning,itisaprerequi
sitethatthetrainingdataisnotbiasedtowardscertaindecisions,isofhighqualityand
completeandismarkedaccordingly.WiththeUOP,valueinthecontextofthedatawill
beimproved.Nodataisperfectbutifitcomeswithinstructionsaboutusability,itcanstill
addvalue.
InFinland,theconceptAurorahasmanycommondenominatorswithKratt’sinitia
tiveinEstonia.Thereexistsaninteresttocollaboratebetweenthesetwodevelopments—
atleastexchangingideasandexperiences,butalso,ifpossible,developingjointtechnical
solutions.ThatwouldcreatethepotentialforinteroperabilitybetweenEstonianandFinn
ishnationalAIbasedeservices.Thus,thevirtualassistantswouldoperateacrossborders
andhelptocreateEstonianandFinnishcommondigitalspace.Estonia–Finlandunited
digitalspaceisalreadyoneofEstonia’sdigitalpolicyprioritiesandwouldcontinueinthis
wayevenintimesofAI,especiallyinthecontextthatFinlandandEstonia’sdataexchange
layerswereconnectedtooneanotherinFebruary2018.Additionally,in2019,thenational
businessregistersandtaxboardsinEstoniaandFinlandweremovingtowardscoopera
tionthatwouldallowtheagenciestoexchangedatainamoreaccurateandefficientway
byusingXRoadTrustFederation.InEuropeanenergycooperation,digitalsolutionsare
beingdevelopedtobuildsmartgridsandtoenabletheeffectiveuseofrenewableenergy.
Newcrossborderservicesarebeingdevelopedinboththepublicandprivatesectors
(https://sites.utu.fi/bre/estoniaandfinlanddigitalforerunnersincrossbordercoopera
tion/,accessedon6January2022).
3.3.HelsinkiRealLifeUOPUseCasesintheBetaStage
TheworkingconceptoftheUOPisdemonstratedviareallifeusecasesthathave
beenselectedtosupportthecurrentinterestsofthecities.Thebetastageusecaseshave
beendevelopedbasedonrealdatafromtheHelsinkicityoperationsandhavebeense
lectedbasedontheavailabilityofdatafromvarioussensors.Itshouldbenotedthatnot
allthedataisopen.Inthenextstage,datasourcesfromTallinnareplannedtobedefined
andutilisedasfeasible.Inthebetastage,nodashboards,applicationsandserviceshave
beencreatedtoutilisethedata.
TheconductedcaseshelptovalidatetheUOPworkingconceptandalsohelpthefirst
pilotcitytohavemorestructuredaccesstodifferentsensordatainthevariedfieldsof
governance,energy,mobilityandbuiltenvironment.
4.DiscussionandConclusions
ThispaperintroducedavisionoftheUrbanOpenPlatformthatgoesbeyondtypical
IoTplatformswithadashboard.TheUOPasaconceptalsoinvolvesagovernanceaspect
ofdataplatforms,ascitiesasinstitutionsareverycomplexwhere“onesizefitsall”solu
tionsdonotautomaticallyapply.Inaddition,wealsobringtothediscussionthefree
roamingofdatabetweenkeystakeholdersofacitythatcanbeothercities,companies,
universities,governmentagencies,etc.Conceptually,anUOPcanexchangedataacross
Appl.Sci.2022,12,70012of14
differentstakeholders,similartohowXRoaddataexchangelayerworksinthecaseof
Estonia.However,freeurbandataroaminginnotasimpletaskbutatruewickedproblem
whereoperational,technical,legalandalsoethicalchallengesneedtobesolved.Inaddi
tion,citieswithoutstrongdatagovernancepoliciestendtobealsolockedintospecific
contractsandvendors.Moreoftenthannot,citieshaveaccessbarrierstothedataowned
bydifferentcitydepartmentsthemselves.Forexample,publictransportusageorcity
streetconstructiondataisoftennotaccessibletocitycivilservantsinrealtime,even
withinonecity.Therefore,weneedtostartwithsmallstepstomakedataroamingpossi
ble.
InthecaseoftheUOP,weanalysedthedataroamingpotentialbetweentwonearby
butheterogeneousEuropeancities,HelsinkiandTallinn.First,wemappedservicesthat
arecurrentlyavailablebetweenthetwocitiesduetothesimilaritiesofdataexchangelay
ersandthepotentialtofederatethem.Forexample,populationregistriesandbusiness
registriescanexchangedatainrealtimeandthereisavalidconsentprocedureforthisvia
federatedXRoads.However,inordertotesttheconceptwithreallifesensordatabased
ontheinterestsandusecasesofthecityofHelsinkiinthebetastage.Therefore,theUOP
asaconceptwasvalidatedviaintegrationof10usecasesthatpullrealtimedatafrom
varioussensorsinthecityenvironment.This,simplyput,showcasesthatthedifferent
institutionalbarrierscanbeovercomeforbetterdataroaminginthecaseofIoT.
SmartcityisoftenlinkedtotheInternetofThingsandsensors[26,27],whereasplat
formshavebeendevelopedthatenabletoconnectdifferentthematicaldatabases[28],alt
houghtheseconceptsoftendonotcommunicateandsyncwitheachother.Inthisper
spective,severalauthors[26,27]aimtodevelopjointprotocolsandarchitectureforlinking
varioussensorstotheInternet.Thisprovidestheabilitytoremotelymanagedevicesbased
onrealtimedatacomingfromsensors[27]thathavebecomecontributorsoflarge
amountsofdata[29,30].Veryoften,citiesareclaimedtobesmartcitieswhentheyopen
upmoredata,includingdatafromwirelesssensornetworks[30].Nevertheless,thecity
innovatorsshouldnotonlyfocusonICTdataorinfrastructurebutonhowtocreatevalue
forcitizens.Conceptually,thecombinationofpowerfulandsmallmicroprocessors,smart
mobiledevices,lowcostsensing,dataanalytics,cloudtechnologiesandadvancedcon
nectivitysetsaconceptualframeworkforautomaticallyconnectingentities[31].
Furthermore,averyimportantlessonlearntisthatasuccessfulsmartcityimplemen
tationisalessspecificsoftwareproductorvendorspecificbutaddressesactualurban
challenges.Therefore,varioussoftwaresolutionsforIoTinsmartcities,suchasKaftaor
FMEETappliedinourusecases,shouldbetakenasapotentialtoolboxthatisopenfor
othersolutions.Ingeneral,wehaveseenfrompreviousresearchthatclosedIoTplatforms
tendnottomainstream,probablyduetotechnologicalandoperationallockins.There
fore,morefocusshouldbeputondistributedconcepts,suchasXRoadanddatamesh.
Forfutureempiricalresearch,morefocuscouldbeputonhowcrossbordercitiescan
offerjointservicesviaanUOP.ThecitiesofTallinnandHelsinkiareverydifferenteco
nomicallyand,therefore,ajointplatformforsmartcityservicescaneffectivelyserveasa
knowledgetransfermechanismfromamoreadvancedregion(Helsinki)toadeveloping
region(Tallinn).Astrongcommonelementofbothcitiesistheirstrongdigitalinfrastruc
tureandpotentialforinteroperabilityofservices.
Thekeypointtounderstandawinningsmartcityistounderstandthatthisisnota
onecitynoronecountrygame[8].Nomatterhowbigacity(Tokyo,SaoPaulo,etc.)is,
anylocalgovernmentistoosmalltocreatearealecosystemofcuttingedgeagileand
adaptivegovernancesolutions(predictiveanalytics,InternetofThingsandbigdatatech
nologies).Thefirstdeploymentshaveledtoinflexible“smartcitiesinabox”or“smart
countriesinabox”whichareageingfast,andfromwhichsolutionsdonotscaleelse
where.Thereisaneedtostartfromsimpleandwidespreadurbanservicesthroughacol
laborativejointcrossborder,handsoneffort.Standardisationisalsothekeytocrossbor
derurbanservices.Therealthreatisthatiflocalmunicipalitiesdonotmanagetoinnovate
fromthebottomupjointlywithneighbouringcities(bothnationalandinternational),then
Appl.Sci.2022,12,70013of14
allcrossbordersolutionwillbeenforcedtopdownoraggressivelylinkedtoglobalbusi
nessvendors.
AuthorContributions:Conceptualization,R.M.S.,T.R.,andH.P.methodology,R.M.S.andT.R.;
writing—originaldraftpreparation,R.M.S.,T.R,andH.P.;writing—reviewandediting,R.M.S.,
T.R.,andH.P.;visualization,T.R.Allauthorshavereadandagreedtothepublishedversionofthe
manuscript.
Funding:ThisresearchhasbeensupportedbytheEuropeanCommissionthroughtheH2020project
FinestTwins(grantNo.856602).
InstitutionalReviewBoardStatement:Notapplicable.
InformedConsentStatement:Notapplicable.
ConflictsofInterest:Theauthorsdeclarenoconflictofinterest.
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