perspektiv 25

TEMA: SMArT CiTy

TidsskrifT for GeoGrafisk informaTion december 2015

PErSPEkTiv25

2 • PersPektiv nr. 25 • 2015

Leder - smart City og geografisk information 3

Gode data er fundamentet for smart Cities Bente steffensen, tina svan Colding, Louise Albæk Jensen, Lasse Borum Lunding 5

kan busdata beregne trafik? erfaring fra Aalborg kommune med busdata stine sørensen 10

Making Digital elevation Models Acces sible, Compre hensible, and engaging through real-time visualizationthomas kim kjeldsen, Peter trier Mikkelsen, Jesper Mosegaard 14

BiM & Gis Connectivity paves the way for really smart CitiesUlf Månsson 19

Perspektiver og udfordringer ved at etablere sMArt CitY og sMArt COMMUnitY-løsningerthomas W. Møller, sine Dyreborg 25

smart Cities – 50 mia. ”ting” på internettet – og det skal styres!Jes Bruun Olsen 30

towards smart city democracyLasse steenbock vestergaard, João Fernandes, Mirko Alexander Presser 38

Open Data Dk skaber vækst og transparens Anna katrine Mathiassen, Michelle Bach Lindstrøm 44

ements of a successful Big Data Hackathon in a smart City Contextthorhildur Jetzek 51

smart Cities Around the WorldMaria skou, nicklas echsner rasmussen 61

inDHOLD

Geoforum Perspektiv ISSN 1601-8796

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Redaktionsmedlemmer:Martin Rudbeck Jepsen, KUPeder Klith Bøcher, AUPer Grau Møller, SDUThomas Theis Nielsen, RUCPer Knudsen, DTUThorhildur Jetzek, CBSJakob Fredslund, Alexandra

Geoforum Perspektiv er tidsskrift for Geoforum Danmarks medlemmer Henvendelse om medlemskab mv. kan ske til: Geoforum DanmarkKalvebod Brygge 31, 1560 Kbh VTlf. 3886 1075, [email protected]

www.geoforum.dk/ perspektiv

PErSPEkTiv


PersPektiv nr. 25 • 2015 • 3

En af de helt store nye trends inden for byudvikling er det såkaldte Smart

City-begreb. Med de eksplosivt voksende mængder af tilgængelige data om

snart sagt alle forhold vedrørende borgernes brug af deres by åbnes der i

disse år op for hidtil usete muligheder for at skabe effektiviseringer,

forbedringer, vækst, energibesparelser og bedre trivsel via nye digitale

services.

Rigtig mange af de nye data er georefererede. Og eftersom en stor del af

den potentielle værdi, som ligger gemt i alle disse data, forventes at blive

realiseret gennem sammenstillingen af forskellige datasæt, så vil der blive brug

for netop et samlende element på tværs af data; en fælles nøgle eller et fælles

sprog at tale i.

Dette fælles sprog vil meget ofte være geografien. Hvad enten det er i det

geografiske aspekt, at værdien i sig selv ligger, eller geografien bruges som

understøttende værktøj til fx visualisering, så vil der i de kommende år blive

større efterspørgsel på løsninger og kompetencer, som indeholder stavelsen

”geo-”!

I dette temanummer af Geoforum Perspektiv har vi derfor sat Smart

City-begrebet under lup. De forskellige artikler belyser begrebet fra

forskellige perspektiver, og vi synes i redaktionen, at vi er kommet godt

rundt om emnet.

En afgørende enabler for Smart Cities er data – tilgængelige data.

Danmark er et foregangsland, når det gælder om at åbne op for de offentlige

data, og derfor har vi bidrag fra de initiativer, der er søsat i Geodatastyrelsen

og Københavns Kommune (”Gode data er fundamentet for Smart Cities”),

Aarhus Kommune (”Open Data DK skaber vækst og transparens”) og Ålborg

Kommune (”Busdata kan beregne trafik”).

En gennemgående tanke, som ligger til grund for åbningen af det

offentliges data, er, at man via åbne data vil inddrage borgere og virksomhe-

der i værdiskabelsen. Borgerne som dem, der kan få mere direkte indflydelse

på beslutninger gennem en større bevidsthed om beslutningsgrundlaget, og

virksomheder som dem, der kan realisere øget vækst og beskæftigelse

gennem de gode nye idéer. Disse perspektiver belyses via cases i henholdsvis

”Towards smart city democracy” og ”From Hackathon to Big Data Startup -

Elements of a Successful Smart City Initiative”.

Jakob FredslundredaktørAlexandra [email protected]

leder

Smart city og geografiSk information

Line Hvingel Ansvarshavende redaktø[email protected]


Der skabes også i disse år mulighed for at

udstille realtidsdata. At kunne tilbyde borgere et

opdateret billede af tingenes tilstand kan helt

indlysende give en værdi. Læs om en konkret case

om trafikinformation i ”Perspektiver og udford-

ringer ved at etablere SMART CITY og SMART

COMMUNITY -løsninger”.

Én ting er visionen, en anden praksis. Skal

forhåbningerne indfries, skal teknikken også spille

med, og der skal være opmærksomhed både på

governance – hvordan forankres fortsat vedligehold af

og adgang til de nødvendige data i de relevante

organisationer – og på at sikre størst mulig integrati-

on mellem forskellige understøttende platforme og

standarder. Det sidste er emnet for ”BIM & GIS

Connectivity Paves the Way for Really Smart Cities”,

mens governance behandles i “Smart Cities – 50 mia.

ting på internettet – og det skal styres!”.

Når det gælder om at få de nye løsninger ud

til folket, så er smartphone apps det typiske svar.

Men udviklingen er også gået stærkt andre

steder, og i ”Making Digital Elevation Models

Accessible, Comprehensible, and Engaging

through Real-Time Visualization” demonstreres

det, hvordan det nu er muligt at lave visualise-

ringer af meget store, geografiske datasæt i en

almindelig webbrowser.

I andre lande er Smart Cities selvfølgelig også på

dagsordenen, men interessant nok går man til

værks på meget forskellige måder og lægger sit

fokus forskelligt. Temanummeret rundes derfor af

med et perspektiverende kig ud i verden i artiklen

”Smart Cities Around The World”.

God læselyst!

Jakob Fredslund, Alexandra Instituttet

Line Hvingel, COWI


GrunddataproGrammet Forbedrer den oFFentLiGe sektor oG skaber værdi i private virksomHederFormålet med grunddataprogrammet er at sikre frie, ajourførte data, som

er nemme at tilgå og som anvendes på tværs af sektorer og brancher.

Visionen er, at grunddataprogrammet bidrager til effektivisering, moder-

nisering og bedre forvaltning i den offentlige sektor. Derudover

understøtter de frie data af høj kvalitet innovation, vækst og nye arbejds-

pladser i den private sektor.

Grunddata er de grundlæggende oplysninger, som det offentlige

registrerer. Disse oplysninger er:

• Geografiske data

• Adressedata

• Ejendomsdata

• Virksomhedsdata

• Persondata

De offentlige grunddata er frit til rådighed for alle offentlige myndigheder,

private virksomheder og borgere (dog med undtagelse af personfølsomme

Grunddataprogrammet er sat i verden for at løfte kvaliteten af offentlige data og sikre en let til - gæn ge lig og stabil datadistribution. Det kommer private virksomheder, den offentlige sektor og borgerne til gavn i mange sammenhænge. et eksempel på dette er smart Cities, hvor data og teknologi kombineret med borgerinddragelse danner grundlag for intelligent byudvikling. Keywords: Grunddata, grunddataprogrammet, datafordeler, Københavns Kommune, Copenhagen Solutions Lab, byudvikling, Smart City, Minecraft

Lasse Borum Lunding styrelsen for Dataforsyningen og [email protected]

Bente Steffensen styrelsen for Dataforsyningen og [email protected]

Tina Svan Colding, styrelsen for Dataforsyningen og [email protected]

Louise Albæk Jensen styrelsen for Dataforsyningen og [email protected]

gode data er fundamentet for Smart citieS


oplysninger). Dermed er grunddata en fælles digital

ressource, som kan anvendes til kommerciel eller

ikke-kommerciel brug.

Grunddataprogrammet er organiseret i en

række projekter, der forbedrer kvaliteten af

grunddata, leverer en ny, fælles datamodel og en

fællesoffentlig datafordeler, der distribuerer data

hurtigt og pålideligt til brugere.

Projekterne forventes at være fuldt implemen-

teret i 2017.

dataFordeLeren er i LuFten med de Første dataDen 30. juni 2014 blev kontrakten med den tekniske

leverandør underskrevet, og dermed lød startskud-

det til at bygge den fællesoffentlige datafordeler.

I efteråret 2015 nåede projektet en vigtig milepæl.

Den 30. oktober kunne datafordeleren nemlig slå

dørene op for eksterne brugere, der fik adgang til fem

webservices med geodata. Alle interesserede fik

dermed for første gang mulighed for at afprøve den

tekniske integration og få indblik i datamodellerne.

De første data udstilles i følgende webservices:

• Tre webservices fra Danmarks Administrative

Geografiske Inddeling, DAGI. DAGI-datasættet

er et standardiseret referencedatasæt, som

beskriver og viser landets administrative

geografiske inddelinger.

• En webservice fra Danmarks Højdemodel.

Danmarks Højdemodel er en digital model af

landskabet i tre dimensioner.

• En webservice med Skærmkortet. Skærm

kortet er et digitalt topografisk kort over

Danmark velegnet til visning på skærm med

zoomfunktion, baseret på de topografiske

grunddata i GeoDanmark (tidligere FOT

Danmark).

Figur 1. Grunddataprogrammet: Data og anvendelse


de næste trin i dataFordeLerens udvikLinGI løbet af 2016 etableres de resterende grunddata

på datafordeleren, heriblandt adresse- og ejendoms-

data (delprogram 1 og 2 i grunddataprogrammet)

samt CPR og CVR.

Og når datafordeleren er i fuld drift i første

halvår 2017, vil der være adgang til alle grunddata

via online-opslag, hændelser/abonnement og

fildistribution. Brugere vil til den tid kunne hente

grunddata ét sted på en lettilgængelig, sikker og

stabil platform. Desuden vil der være adgang til

services, der sammen stiller data på tværs af datasæt.

Efterfølgende udfases de nuværende, eksisterende

distributionsløsninger.

Datafordeleren bygges i første omgang med

henblik på at distribuere grunddata. På længere

sigt forventes det, at datafordeleren kan anvendes

til distribution af andre typer data.

samspiLLet meLLem den diGitaLe oG Fysiske inFrastrukturGennem grunddataprogrammet får Danmark en

infrastrukturmodel, der definerer, hvordan

grund data, genbrug af data og sammenhængen

mellem data i den digitale forvaltning ser ud. Med

datafordeleren får vi en fælles distributionskanal,

der bl.a. muliggør anvendelse af data på tværs af

datasæt. Dette skaber nye muligheder for effektiv

dataudnyttelse.

København Kommunes Copenhagen Solutions

Lab udnytter dagligt data til at forbedre forvalt-

ningen. Med henblik på at skabe en mere

intelligent byudvikling bruger Copenhagen

Solutions Lab data som den infrastruktur, der dan-

ner rammen om udviklingen mod København som

en Smart City.

Mange af de data, der er brug for i forbindelse

med f.eks. trafikregulering, skybrudshåndtering og

affaldshåndtering, er realtidsdata, der viser, hvad

der sker i byen. Det er data, som kan bruges i

handlingsrettede sammenhænge, og som kan

bruges til at forudsige, hvad der sker i fremtiden.

Og det er data, der går på tværs af typer og

sektorer, som når data om luftkvalitet bruges til at

tilrettelægge trafikken rundt i byen, så der så vidt

muligt tages hensyn til byens luftkvalitet.

Det er en tilgang til byudvikling, der tænker den

samlede, sammenhængende datamængde som en

del af byens infrastruktur. Det kræver tilgængelige,

nøjagtige og ajourførte data, som er meningsfulde i

de forskelle sammenhænge, de anvendes i.

Grunddataprogrammet er sat i verden for at skabe

det grundlag af data, som udviklingen mod Smart

Cities kan bygge på.

udvikLinG med borGere, virks omHeder oG vidensinstitutionerEn Smart City består ikke kun af teknologi og data.

Et vigtigt parameter for byerne er at inddrage

borgerne, så man udvikler den by med de services

og løsninger, som efterspørges, og som er forståe-

lige og nemme at anvende. For at opnå det arbejder

Copenhagen Solutions Lab med at skabe såkaldte

Triple Helix-partnerskaber.

Triple Helix-partnerskaber er, når det private

erhvervsliv møder de behov, der er i den offentlige

sektor, sammen med fageksperter og universiteter-

ne, der har pulsen på, hvor forskellige teknologier

er på vej hen. På den måde skabes de bedste, mest

innovative løsninger.

Resultatet af partnerskaberne ser man bl.a. i

Copenhagen Solutions Labs Smart City Street

Lab, der tager de første spæde skridt mod en

Smart City. Smart City Street Lab er København

Kommunes testområde for intelligent byudvik-

ling, baseret på det prisvindende koncept

Copenhagen Connecting. Midt i Indre København

afprøver de den nyeste teknologi inden for

byudvikling. Det kan f.eks. være sensorer, der

måler luftkvaliteten eller detekterer ledige

parkeringspladser i byen.

Således kan virksomheder se deres løsninger i

funktion i byrummet og lave proof-of-concept,

inden teknologien skaleres til hele København eller

andre store byer. Og borgere, politikere og andre

kan få et konkret og fysisk billede af, hvad

intelligent byudvikling egentlig er.


trafikal regulering, der mindsker trængsel af biler,

cykler og mennesker. Det vil betyde øget trafiksik-

kerhed og mobilitet og mindre miljøbelastning.

Den type digitale løsninger kombinerer gode,

ajourførte og tilgængelige grunddata og data skabt

af kommuner, virksomheder, borgere mv. Samtidig

forudsætter det en infrastruktur, der samler,

beriger og behandler de store datamængder, som

eksempelvis grunddataprogrammet og datafor-

deleren gør det.

’Der er ingen tvivl om, at der er spændende perspekti-

ver i offentlige data, som kan bidrage til at løse en række

store samfundsudfordringer, som den offentlige sektor står

overfor. Dette gælder blandt andet inden for områderne

forsyning, energi, trafik og sundhed. Vi vurderer, at der

her er potentiale i at tilgængeliggøre og udnytte de data

den offentlige sektor allerede er i besiddelse af, men at det

også er vigtigt at have fokus på nye og hidtil uudnyttede

kilder til data’, siger Laura Poulsen, kontorchef i

GeoGraFisk dataanvendeLse i ForvaLtninGenGrunddataprogrammet og datafordeleren har fokus

på at anvende og genbruge grunddata på tværs af

forskellige offentlige myndigheder. Derved kobles

grunddata på tværs af fagområder og sektorer og

bliver det fundament, mange offentlige og private

digitale løsninger bygger på. De digitale løsninger

får deres specifikke udtryk, når andre typer data

kobles på: Realtidsdata, domænedata, ustrukture-

rede data og mange andre typer data er de bygge-

klodser, som de nyeste teknologiske løsninger inden

for intelligent byudvikling er bygget af.

Intelligent brug af data til udformning af nye

digitale løsninger vil i fremtiden bl.a. ske ved brug

af geografisk information. Dynamiske trafikinfor-

mationer, der kombinerer geografiske grunddata

og positionsdata fra trafikanters GPS eller mobil-

telefon, kan åbne for udviklingen mod smartere

Figur 2. 3D Urban Planning i Holland med Minecraft


og trafik med en storskærm og Minecraft. Det er en

løsning, der håndterer og formidler store og

komplekse datamængder og informationer på en

lettilgængelig og forståelig måde, så kommunen

kan gå i dialog med borgerne om de rigtige

løsninger.

Et mere hjemligt eksempel er Viborg

Kommune, der har fået lavet en interaktiv

3D-model af hele kommunen i computerspillet

Minecraft – altså deres eget Vibcraft. Hertil er der

blandt andet anvendt grunddata i form af data

fra Danmarks højdemodel og udvalgte

GeoDanmark- data. Vibcraft anvendes både til

undervisning i mate matik, geografi/geologi og

byplan lægning, samt til borgerinddragelse. Her

udnytter man 3D-data til at øge borgernes

rumlige forståelse af potentielle projekter, som

dermed bedre kan komme med input,

eksempelvis til byplan lægning.

Politik og Vækst, Styrelsen for Dataforsyning og

Effektivisering (SDFE), og tilføjer: ’Noget af det der er

afgørende for, at den data, der bliver produceret, skaber

værdi, er, at vi arbejder for at skabe de rette rammer både

for frembringelse og for anvendelse af data. Dette betyder

blandt andet, at vi skal have fokus på at samarbejde på

tværs af den offentlige sektor om at gøre data tilgængelige,

og at vi samtidig husker at realisere de mange nye

perspektiver for øget anvendelse af datadrevet forvaltning’.

Et eksempel på, hvordan frie grunddata med en

geografisk komponent kan tages i anvendelse, er

det danske Minecraft-projekt, hvor Danmark ligger

som en virtuel verden i størrelsesforholdet 1:1 i

selve Minecraft. I Holland har man ladet sig

inspirere og lavet en crowd sourcing-løsning, hvor

børn og unge kan bidrage til byens udvikling

gennem leg.

I Holland har de koblet en klassisk GIS-løsning

med geografiske informationer om bl.a. støj, lugt

Læs mere

På Digitaliseringsstyrelsens hjemmeside, digst.dk, kan du læse mere om visionerne og planerne for grunddataprogrammet.

På datafordeler.dk finder du mere info om de fem første webservices, der er i prøve-drift . Du kan følge den videre udvikling på twitter.com/datafordeler og gruppen Datafordeler på LinkedIn.

Figur 2. 3D Urban Planning i Holland med Minecraft


indLedninGVi skal tænke smart, når vi arbejder med data – vi behøver eksempelvis

ikke at indsamle ny data, for ofte kan det data, vi allerede har, benyttes til

at gøre vores byer smartere. I kommunerne har vi rigtigt meget data – og

meget af det data bliver i stigende grad stillet frit tilgængeligt via åbne

dataportaler, som tilfældet blandt andet er i Aalborg Kommune. Det

betyder, at enhver kan bruge data og til et hvilket som helst formål. Det

Dagligt transporteres tusindvis af passagerer fra busstop til busstop. Både busser og bilers hastig-hed afhænger af de samme trafikale forhold og ved at kombinere geografisk data, om blandt andet busstoppesteder, og data fra bussernes sensorer, kan man få nogle meget interessante resultater. Bussernes hastighed kan nemlig bereg nes ud fra disse oplysninger og benyttes som indikator for den generelle hastighed i trafik-ken. Derudover kan der let kobles mere data på, som gør beregningerne endnu mere nøjagtige. Dette er bare ét eksempel på, hvordan kom mu-nale data kan bruges til at gøre vores byer smar-tere og mere intelligente. vi har så meget data i de danske kommuner, og vi har endnu ikke set det fulde potentiale heraf. Keywords: Smart City, geografisk information, intelligente trafiksystemer

Stine SørensenAalborg kommune [email protected]

kan buSdata beregne trafik? erfaring fra aalborg kommune med buSdata


kan der være stor værdi i, både for erhvervslivet,

kommunen og for borgere. En undersøgelse fra

2011 viste, at der er et indtjeningspotentiale på

op imod 25 milliarder kroner på at udlevere data

fra det offentlige til erhvervslivet (Zangenberg &

Company, 2011).

En af fordelene ved at udgive data er, at andre

kan få adgang og bruge kommunale data til noget

helt nyt. Data er et af det vigtigste elementer i

Smart City, da data kan udnyttes til ny viden, nye

ideer, løsninger og services. Vigtigst af alt, så kan

kommunale åbne data kombineres med andre

datakilder, hvilket kan give nye og hidtil usete

muligheder.

En af de ting, der optager rigtigt mange

mennesker, er, hvornår der er kø på vejene. Når

folk kører hjemmefra, vil de gerne vide, om der er

kø – eller endnu bedre: vil de gerne kunne

forudsige, hvornår der er kø. Det interessante er, at

vi faktisk via eksisterende data kan beregne netop

dette. Vi skal bare huske at tænke smart.

busdata bereGninGerI Aalborg Kommune samler vi data om ankomst og

afgangstider på vores busser – det gør vi for hvert

enkelt busstoppested og for hver eneste buslinje.

Dataene holdes op mod køreplanen, hvorved vi kan

analysere om busserne er forsinkede. Ved at sammen-

sætte disse to datasæt kan det udregnes, om en bus

generelt er 2 minutter forsinket eller for tidlig i

forhold til køreplanen. Det er helt normalt, at data

bruges til netop det formål, således vi hele tiden kan

optimere den offentlige transport. Og det er også

baggrunden for at indsamle akkurat disse data.

Netop data om ankomst og afgangstider gav vi

til en studerende fra Aalborg Universitet. Vi

forventede, at han ville udarbejde en dybde-

gående analyse omkring vores ankomst- og

Figur 1. Distancen mellem stoppestederne Vesterbrogade og Jomfru Ane Gade


vil vi med garanti kunne spotte nogle generelle

tendenser. Ved at koble data om tidspunkt på

dagen, årstid og ferietid bliver udregningen

endnu mere interessant, da vi således kan se,

hvornår der er mest trafik på vejene. En

yderligere dimension er vejret – hvis det regner,

kører busserne så langsommere, fordi flere

vælger at tage bilen og antallet af køretøjer på

vejene derved øges?

En anden faktor, som er vigtig at tage forbe-

hold for, er vejens forløb. Eksempelvis er det

vigtigt at vide, om der er mange lyskryds på

strækningen, ligesom antallet af sving kan være

afgørende for bussernes hastighed. Kobles alle

disse nævnte data, kan vi efterhånden sige ret

meget om bussens hastighed. Ud fra disse

beregninger kan vi således vide, om der er meget

eller lidt trafik på vejene. De første resultater

viser, ikke overraskende, at der generelt er mest

trafik i morgen- og eftermiddags timerne.

Resultaterne er endnu ikke tilgængelig for

borgerne, men netop dette data, vil måske indgå i

trafikbrergninger fremadrettet.

afgangstider, og på den baggrund komme med

ændringsforslag. Den studerende brugte dog

vores data helt anderledes.

Via geokoordinater for to busstoppesteder

kunne den studerende beregne den distance,

som bussen kørte. Ud fra vores busdata vidste

han præcist, hvornår en bus var afgået fra et

busstoppested og hvornår denne bus var ankom-

met til næste stoppested. Med disse to tal kunne

bussens gennemsnitshastighed beregnes.

I dette tilfælde er der 950 meter imellem

stoppestedet på Vesterbrogade og Jomfru Ane

Gade. Ved Vesterbrogade afgår bussen kl 13.59.00.

Ved Jomfru Ane Gade stoppestedet ankommer

bussen kl 14.03.05. Det betyder, at gennemsnits-

hastigheden er 14.0 km/t. Sammenligner man

dette med f.eks. en bus, der afgår kl 08.42.44 fra

Vesterbrogade og ankommer ved Jomfru Ane

Gade kl 08.49.20, så kan vi se, at gennemsnits-

hastigheden er 8,6 km/t. To tilfælde er

selvfølgelig ikke nok til at kunne sige noget

fuldstændigt om den generelle trafik, men laves

disse beregninger ud fra alle buslinjer hele året,


ForudsiGeLser aF biLtraFik – ud Fra busdataSom udgangspunkt følger busserne trafikken – i

hvert fald i byerne. Bussernes hastighed er dog ofte

lidt langsommere end bilernes, men vi kan stadig,

via ovenstående beregninger, finde ud af, om der er

meget eller lidt trafik. Det er dog stadig kun et

historisk billede af trafikken. Det meste data

kender vi på forhånd, og det er nærmest kun data

om vejret, som kan variere. Ved at sætte det hele

sammen vil vi således kunne estimere trafikken fra

dag til dag. Det vil ikke kun være en fordel for dem,

der rejser med bus, det vil i høj grad også være en

fordel for øvrigt trafikanter. På sigt vil vi sand-

synligvis kunne modtage livedata fra busserne og

dermed få et realtime billede af trafikken.

Det er nemt at forestille sig, at der kan kobles

yderligere data på, hvilket blot vil gøre

trafikbilledet mere nuanceret. Eksempelvis vil vi

også kunne forudsige trafikken, hvis der skal være

en større kultur- eller idrætsbegivenhed – blot vi

ved det finder sted. Det kan også være, at vi ved, at

universitetet holder en større forelæsning, og ud

fra data om vores buspassagerer ved vi, at det

typisk er studerende, der tager bussen. Det er dog

åbenlyst, at der er begrænsninger for forudsigelser-

ne, f.eks. ved pludseligt opståede hændelser,

eksempelvis et trafikuheld. Men ikke desto mindre

så kan vores data om bustrafik være en meget

præcis indikator for trafikken.

konkLusion oG perspektiverinGDer er rigtig meget data, som kan bruges til

mange ting. Ved hjælp af forskellige datakilder

kan man blandt andet blive i stand til at

forudsige trafikken endnu bedre i Aalborg

Kommune. Det er dog ikke det, der er den

væsentligste pointe med denne artikel. Dette lille

eksempel rummer mange perspektiver, hvor

åbne data er et vigtigt element;

• Vi behøver ikke nødvendigvis at indsamle

nye data for at få smarte løsninger

• Eksisterende data kan kombineres på nye

måder og skabe nye løsninger

Generelt er der rigtig meget data, som vi endnu

ikke har taget i brug, men som kan hjælpe os med

at forstå trafikken. Og kobles det med noget af alt

det geografiske data, vi har, eksempelvis geokoordi-

nater på p-pladser for både cykler og biler, så syntes

mulighederne nærmest uendelige.

Når der forhåbentligt bliver åbnet op for data

fra rejsekortet, så vil vi med garanti se utallige

eksempler på, hvordan data kan benyttes til

løsninger, som vi slet ikke havde forestillet os.

Med rejsekortdata vil vi kunne koble bussens

data med data om vores passagerer, og dermed

vil det være muligt at udregne langt mere

præcise data om trafikken. En simpel ting som

rejsekortdata vil kunne sige noget om er, hvor

passagerer kommer fra, og hvor de skal hen. Det

vil sige, at vi ved hjælp af data kan finde ud af,

om vi har passagerer, der rejser igennem tæt

trafikerede strækninger, uden behovet måske er

der. Det vil ikke alene være banebrydende for

den kollektive trafik, men også få betydning for

al anden trafik – og så har vi ikke en gang set på

fordelene for miljøet.

Kilder:

• Zangenberg & Company, kvantificering af værdien af åben offentlig data, 2011.

Figur 2. Angiver afgangstid og ankomsttid for to stoppe steder samt distancen mellem stoppestederne


introductionIn recent years, a large amount of spatial has been made available as open data

(Regeringen and KL, 2012). The data is of ever-increasing quality and resoluti-

on, but the true value comes from usage. The authors are fascinated by the

idea of interactive visualization pushing the possibilities within current

hardware and software. We believe this can create new business opportunities

for companies offering new experiences and new knowledge from data.

In this paper, we give an introduction to some of our experiments with

the new height model of Denmark (DHM) (The Danish Geodata Agency,

2015), and the possibilities that arise with fully interactive 3D available in

modern web browsers and virtual reality hardware.

Data in itself is tedious to work with – and cannot do anything in itself.

The larger the data set, the more difficult it becomes for human beings to

make sense of anything at all. On top of that, many software packages

suffer extreme performance penalties when data does not fit into memory.

The software slowdown can partially be alleviated by constructing sophisti-

cated algorithms that scale better with regard to input/output (I/O)

in this paper, we present our initial experiments with the new high-quality digital elevation model, “Danmarks Højdemodel-2015” (DHM) exposed as an interactive 3D visualization on web and in virtual reality. We argue that such data has great opportunities to spawn new business and new insight for the individual citizen if it is accessible, comprehensible and engaging. Keywords: WebGL, Visualization, DHM

Thomas Kim Kjeldsen Alexandra [email protected]

making digital elevation modelS acceS Sible, compre henSible, and engaging through real-time viSualization

Peter Trier Mikkelsen Alexandra [email protected]

Jesper MosegaardAlexandra institute [email protected]


operations – one variant being the streaming

algorithms used in the present work. When the

questions that need to be answered through data

queries are known, the data can be crunched –

i.e., pre-processed in a way so that answers to the

given and known types of questions can be given

relatively quickly. However, there are many

situa tions in which the question is not clear or

known – and where the human observer needs to

inspect, observe and experience the data in

context. This is especially true in situations with

strong visual and emotional aspects, for instance

“How does that wind turbine affect my home?”

We argue that those personal perspectives and the

exploration of data needed can be achieved if data is

available as interactive 3D. We believe that those

visualizations should ideally be made easily accessible

through simple HTML5 web pages – and that further

immersion into full virtual reality allows users to

fully grasp scale and impact of (changes in) reality.

is dHm data For everyone?We firmly believe that data such as DHM has a

basic level of usage for anyone, ranging from “let’s

find our house” to “let’s find new business

opportunities”. Even though the data is available,

it is not readily accessible, engaging and compre-

hensible for the broad audience.

making data accessibleTo be fair, DHM is actually easily accessible for

someone with a bit of a technical background, but

can be almost impossible for a novice within IT.

Users need to be registered, data downloaded, new

hard disk drives bought, data downloaded again,

software found that can read data, software

installed, and finally looking at GIS related

functionality without knowing what to do.

There could be so many opportunities for the

individual citizen to understand or comment on

larger decisions of infrastructure within the

context of their own home, city and region.

Examples could be wind turbine projects, city

planning, highway construction, and geo-located

statistical data.

Most people are used to simply clicking on a

new link that someone sent through an e-mail, or

launch that smartphone app that others recom-

mend. That is why we decided that DHM should be

made easily accessible through a simple web page,

see Figure 1. Visualizing 3D within the browser as

part of a web page has been made possible recently

through the WebGL standard that enjoys wide-

spread support in all major browsers – even on

mobile devices such as Android and iOS. WebGL

allows an application programmer to access the

hardware accelerated graphics card through an API

Figure 1. Denmark’s Height Model in 3D on a webpage (http://Denmark3D.alexandra.dk)


is that the height map is only needed at full

resolution in a small region close to the camera

position, while the vast majority of the visible

terrain can be rendered with a much lower

resolution without affecting the final image

quality. When the camera moves through the

world, we continuously stream in new high-

reso lution data on demand. The height map data is

arranged in a standard Web Map Tile Service layout

which makes it easy to request a chunk of data as a

map tile at a certain level of detail. The data tiles

that have been streamed in are then stored in

graphics card memory in a large unordered pool as

shown in the top right corner of Figure 2. The main

task of the rendering algorithm is then to keep

track of where each tile is located in the pool and

to fetch height data from the correct tile,

depending on world position and level of detail

(Mittring, 2008).

making data comprehensibleVisualizing data is sometimes thought of as a

direct mapping of spatial data to 3D projections –

without any intermediate “manipulation”. Nothing

could be further from the truth. Artistic and

technical choices are at the heart of visualization

in javascript. And, it allows us to deliver an

experience close to that of a desktop program, with

the added benefit that no application has to be

installed or updated, and data can be loaded

on-the-fly without requiring huge datasets to be

downloaded manually.

Naturally, the large amount of data is still an

issue that needs to be addressed, and high

performance is still a challenge to reach. The main

problem is that the total amount of data is by far

too large to fit in both system memory and

graphics card memory. For example, a height map

of Denmark (approximately 45.000 km2) with a

pixel density of 2500*2500 km-2 stored in 4-byte

floating-point format requires around one terabyte

of memory. However, it is of course not necessary

to store the full resolution map of the whole

country in order to create highly detailed terrain

rendering locally.

Our solution exploits this fact to stream in

chunks of the height map in a level of detail

depending on what can be seen at the current

zoom level. Figure 2 shows a wireframe model of

the geometry used for terrain rendering. Notice

that the mesh resolution varies with the distance

from the observer. The advantage of this technique

Figure 2. Caching and Level of Detail in rendering. The upper right corner shows the height map tiles that are streamed into the graphics card memory.


and always include a level of interpretation and

presentation. One such set of choices concerns the

more or less realistic shading of surfaces arising

from reflections, materials and light. We argue

that this is one important aspect of giving the user

the illusion of seeing something real – which then

becomes comprehensible to him or her.

Ideally, we would like the users to be fully

immersed in the virtual environment to compre-

hend the environment and really be able to feel the

visual impact and size of large changes in buildings,

nature and infrastructure. An important upcoming

trend, driven by the computer game industry, is

virtual reality (VR) where users see a virtual

environment through head mounted glasses. The

first VR equipment was built by Ivan Sutherland in

the 60’s, but was never really successful due to

severe limitations in display technology. Since the

successful Kickstarter of Oculus VR in 2012 and the

later acquisition by Facebook in 2014, the field has

been re-booted with new promises of total immersi-

on in photorealistic virtual environments. As

computer graphics geeks we finally believe the hype;

the new generation of VR has the necessary low

latency, lightweight headset, and wide field of view

in a high resolution to realize a believable digital

world. Consequently, we also ported our DHM

visualization to the Oculus VR.

making data engagingTo engage users, they need to see, explore and

experience things that matter to them. One such

thing is the construction of wind turbines near

one’s home. We did a prototype utilizing the DHM

dataset to visualize the impact of a wind turbine

construction for the individual citizen, see Figure 3.

This is one case where VR has a great potential

impact beyond images, videos, and interactive

applications. No screen can give the impression of

being there, but VR can. VR allows the user to

judge true size and distance – and can present the

users with scenarios that can otherwise only be

imagined. Thus, we believe that digital modelling

of proposed constructions combined with the DHM

data and VR can be a useful platform for public

evaluation of environmental impact assessments. A

key challenge in the widespread use of VR is that

users are required to purchase head-mounted

displays. These are expected to be adopted widely

by gamers but probably not by the average

consumer. There are, however, several low cost

products available today, e.g. Google Cardboard

Figure 3. The image shows stereoscopic rendering for each eye. When viewed through the lenses of a VR helmet, sizes, distances and colors will appear as if they were real.


embracing truly interactive applications with

real-time feedback made possible through tech-

niques such as the those we have described here,

and not accept the performance of sluggish

desktop applications that try to import gigabytes of

data for presentation. Finally, we suggest that

Virtual Reality may hold unexplored opportunities

to present “larger-than-life” scenarios in training,

simulation and construction – and that visual

effects from computer games can be embraced as

very effective means of visual communication.

References

• The Danish Geodata Agency (2015). Danmarks Højdemodel, DHM/Terræn. Data version 2.0 – Januar 2015. Geodatastyrelsen.

• Mittring, M. (2008). Advanced virtual texture topics. In SIGGRAPH ’08: ACM SIGGRAPH 2008 classes, pp. 23–51. ACM.

• Regeringen and KL (2012). Gode grunddata til alle – en kilde til vækst og effektivisering. Rosendahls – Schultz Grafisk.

and Samsung Gear VR, that transform a regular

smartphone into a VR system. Thus, the target

audience with access to VR equipment can be

expanded significantly with such products.

concLusion & Future workOur current VR visualization of the DHM dataset is

a stand-alone application, not integrated with the

web-based WebGL visualization. A key issue is the

current lack of support for VR in browsers. A new

standard, WebVR, is available in nightly/

experimental builds of Firefox and Chrome and

suggests that we might have an easily accessible VR

platform in the very near future.

Our recommendations for working further with

the DHM data are to adopt web-based visualizations

as a means to make it easily accessible for people to

explore this impressive dataset – and further, to

empower both private citizens and businesses with

the ability to utilize the dataset as a canvas for

many other applications. We also recommend


connectivityWay back in time, when I started studying GIS and Remote Sensing, I

remember discussions like ”Are you vector or are you raster?”. The idea of

combining these features would have been considered revolutionary at the

time. Also, if you did choose a GIS-tool, you committed yourself to the vendor

of the chosen platform and the system´s proprietary file-storage format.

today, we see several good examples of smart City and Geodesign initiatives around the world. they often depend on BiM data (Building informa-tion modeling/Bygnings informations Model lering) and spatial data. However, interoperability is a challenge that must be adressed in a more effi-cient way. More generally, the question is what is required to take the leap from good examples to broad and mainstream application in urban and regional development? in this article, some key success factors for this development and described and the important challenges outlined. the v-Con innovation project addressing these challenges is described as a possible solution. Keywords: Geodesign, BIM (Building information modeling), GIS (Geographical Informa tion Systems), Internet of things, Semantic Web, Smart Cities

Ulf Månsson, Project Manager, sWeCO, [email protected].

bim & giS connectivity paveS the way for really Smart citieS


Exchanging data between platforms was hard - if

even possible at all.

Since the introduction of connectivity to standard

databases and the evolving of the Internet - the GIS

industry has come a long way. We have standards like

GML, WMS and WFS (Reichardt, Mark E. 2012).

Interoperability tools are considered a must in most

organizations. ”We do not want vendor lock in” is a

common phrase heard in many organizations.

The official reasons for the fear of ”vendor lock in”

may vary (Verstraete, C. 2015): It can be an economic

motive. If we invest heavily in a platform from vendor

A - the cost can skyrocket if the vendor changes the

license-model. Also you may be too dependent on a

certain expertise. … It can also be a decision about

Open Source or Proprietary. You may feel safer with

either side when thinking of the long time aspect.

Personally, I think the most important fact to

consider is none of the above. Focus should be on

connectivity. Data created, collected and stored by

an organization has greater value if it can be

connected and combined with other data - coming

from any place. Connectivity is a cornerstone in two

trending fields, Smart Cities and Geodesign.

smart citiesThere are many different definitions of Smart City

but the fundamentals are (Wikipedia 2015):

• Enhancing quality and performance of urban

services.

• Reducing costs and resource consumption

– thus achieving sustainability.

• More effective engagement with its citizens.

A typical future scenario in a Smart City is often

exemplified with emergency response (Enbysk, L.

2013). In a really Smart City, the ambulance

personnel not only gets notifications about the

fastest route to the correct building, considering all

current traffic-related data. They would also get

live instructions on which entrance to use and

finding a fire safe way to the correct floor as fast as

possible.

To achieve the above, all kinds of data must be

connected between many different sources and

systems leading to useful information and

knowledge. With regards to spatial areas, cities

have huge spaces and functionality inside buil-

dings. As an example, Dan Campbell at the City of

Figure 1. Achieving connectivity between GIS and BIM, Ulf Månsson


’A design and planning method which tightly couples

the creation of design proposals with impact simulations

informed by geographic contexts’ (Flaxman M. 2010)

Within the geodesign discipline, some of the

steps in planning and implementing a new

residential area could be:

• Gather information based on existing data

such as road-networks, traffic-information,

building information, geology etc.

• Perform analysis and simulations. (For

example; How will traffic be affected with

more residents?).

• Create proposals based on evaluation models

and communicate these for feedback among

stakeholders and citizens. (Steinitz C. 2012)

In these steps, we need current data, we also create

new data and when something eventually is built

we should evaluate on the accuracy of the simulati-

ons and predictions.

Vancouver, explains that just one BIM-model uses

¼ of the space of the 3D GIS-model of the entire

city (Safe Software 2015). This means that in many

Smart City scenarios, most data will have to come

from BIM Systems (Building Information Models)

and connect to GIS. Therefore, BIM databases will

have to evolve to the same state of openness as GIS

(Figure 1) to make this feasible.

Figure 1 explains how GIS and BIM have evolved

during time and how different areas have been

embraced. Today, the use of Open Spatial Databases

can be considered a de facto standard within GIS.

However, BIM focus today is very much on WEB-

enabling it and not yet on using Open BIM

Databases.

GeodesignOnce again, there are many definitions. The

following definitions is short and concise enough

for this context:

The Smart City as visualized by August Wiklund, Sweco


reLationsHip between GeodesiGn and smart citiesOne can see that a well-performed Geodesign-

process would benefit from existing Smart City

information for well-informed decisions. For

example, getting information about traffic-

statistics and all kinds of sensors and other Big

Data sources. On the other hand, one could also see

a well-performed Geodesign-process as funda-

mental to a Smart City. If the designs coming out

of the Geodesign process are not stored, updated

and kept accessible - they won’t help the vision of

the Smart Cities.

In regard to data, achieving connectivity in these

fields has many barriers, both technical and legal.

Fortunately, as more organizations open their

datasets, there are now less legal barriers. The

technical challenges still remain. Many of these are

well known to the GIS industry, and are linked to the

difficulties of combining data from different sources.

Examples of challenges:

• Reading and writing from different formats

and sources (including open standards and

proprietary).

• Combining different types of geometry types.

• Coordinate systems and precision.

• How data is layered or have attribute

schemas.

The more complex BIM-platforms have not come as

far as the GIS-platforms regarding connectivity.

This is quite understandable as these models are so

complex with their high level of detail and

3D-capabilities. In reality, most BIM-data live in

their proprietary systems, and exchanging

information is cumbersome.

tHe cHaLLenGes aHeadThe vision of smooth Geodesign processes and

blooming Smart Cities will benefit greatly if two

specific areas will be addressed.

accessibility of bim dataA lot of effort is being made in standards such as

IFC (Industry Foundation Classes) to be able to

exchange information in an efficient way (buil-

dingSMART 2015). However, it is still very rare that

you have storage in open databases where data

lives. In the GIS-industry, it can be considered best

practice to have a database that owns the informa-

tion, and different platforms can access this

database with modern tools such as version-con-

trol, integrity rules etc. Other, non-spatial systems

can directly connect to the databases as they use

the same technology. This can be exemplified by

Microsoft SQL Server and Oracle - databases that

are widely used and shared between many types of

systems – spatial or not.

The BIM-industry is far from this point. Software

tools exist - but they are rarely open for integration

(Isaac S et al 2013).

Using BIM-data together with GIS-data in reality

mostly means:

• You export a subset of your BIMmodel to your

GIS database.

• You import a subset of your GIS database into

your BIM-model.

You very rarely connect these sources on an object

level directly.

systems understanding systems When we traditionally think of GIS, it is often in

the context of seeing and relating to maps

produced for the human eye. That is, the data is

presented in a form that allows a human to make a

Figure 2. Graph model


object model where you define tables or classes and

relate them together according to predefined rule

sets or schemas – as most GIS solutions do.

However - a key element for the semantic web

is that you store and send information as graphs

(Figure 2). You have nodes, edges and properties.

Communicating in this triplet-way adds meaning

for machines interpreting these connections. As

a graph can be dynamic, it can evolve during

time and become more or less complicated. This

is something that works very well with BIM-

models, for instance the IFC-standard that in its

complete implementation is very extensive. In

most implementations, only subsets of the

IFC-standard are used. However, during a projects

life cycle, different subsets and parts are being

adopted. To support these dynamics in an

IFC-model with a relational database is almost

impossible but far more possible with a dynamic

graph database.

The idea of achieving better connectivity

between BIM and GIS systems with help of the

above technique is based on the assumptions that:

• It’s easier to model BIMdata as a graph than

in a relational model

• BIMmodels change over time – something

that is possible to handle with new links in

the graph.

• Connections between specific BIM and

GIS-objects can be maintained with links in

the model. (The actual geometries could be

stored in the model or it can be links to

external storage as physical files. Something

called “Hybrid Approach”).

Communicating with a Semantic Web enabled

system can be done with special query-languages

like SPARQL. These languages provide a way to

query graphs over the Web and can be utilized by

different systems.

vcon paves tHe way The author is currently participating in the

PCP-part of the V-Con project (The Virtual Construc-

well-informed decision. This also affects the way

data is stored.

BIM is often ”more” intelligent as one of the

major purposes is to keep track of details and of

how objects are interconnected describing the

topology of a building or complex infrastructu-

re-projects. But still - it is humans making most

decisions based on what is displayed.

The Smart City concept relies on complex

chains of systems communicating with each other.

In the ambulance example above, several systems

would need to interact. Traffic-information,

navigation, BIM with building layouts and elevator

systems would need to understand each other.

The traditional way of achieving this is through

standard protocols. That is, you ”hard wire”

intelligence into systems to understand what other

systems mean. A protocol can both describe the

physical means of communications and also the

standards describing the logic of data. So if two

systems understand the same protocol - they can

communicate. The drawback is that operating on

new types of data demands new protocols. So a

Smart City getting smarter by connecting new data

would demand a lot of new protocols.

An exciting alternative to using predefined

protocols is the ”Linked Data” approach. Linked

Data describes a method to communicate data so it

can be interlinked and become useful through

semantic queries. The approach uses standard Web

technologies but instead of serving web pages it

can be read and understood automatically by

computer systems.

tHe semantic webThe semantic web concept is complicated so it will

just be touched upon briefly. A cornerstone is the

use of Linked Data. ’The Semantic Web is not a separate

Web but an extension of the current one, in which

information is given well-defined meaning, better enabling

computers and people to work in cooperation’ (Tim

Berners-Lee, Hendler and Lassila, 2001).

The more traditional way of storing and commu-

nicating information is through the relational or


tion for Roads) that aims to improve the efficiency

and effectiveness of the National Road Authorities

in Europe. (Read more at http://www.rws.nl/english/

highways/v-con)

PCP is an approach for procuring R&D services

and consists of a funnel of three phases: challenge

solution design, challenge prototype and pre-pro-

duction testing.

This project is managed by the Dutch National

Road Authority at the Ministry of Infrastructure &

the Environment. Other participators are the

National Swedish Road & Rail Authority and research

institutes from France and the Netherlands.

The ground breaking idea in this project is to

keep using existing standards in GIS & BIM but also

keep the information linked. The foundation for

achieving this is envisioned to be via a linked data

approach through the semantic Web.

It is a very ambitious project and is very

technically challenging. V-Con aims at enabling

national road authorities to introduce software

tools for exchanging/sharing comprehensive road

information with commercial parties in the sector.

The author is responsible for designing

SWECO’s solution idea that was selected in

competition with 14 proposals and further

developed in phase 1 of the PCP-process. The

solution idea has now qualified for phase 2 of the

project - meaning that challenge prototyping will

begin January 2016. In short, the solution design

consists of designing modules adding Semantic

Web capabilities to a standard Spatial Data

Integration platform (FME by Safe Software). This

platform already supports reading and writing

most BIM and GIS standards but currently doesn’t

have Semantic Web functionality. Adding these

new Semantic Web capabilities to an already wide

spread integration platform will hopefully increase

the chances of the Linked Data approach to be

adopted throughout the industry.

If the prototype meets the challenges in phase 2

it might be a candidate for pre-production testing

towards the end of 2016. After this it can be

released as a solution for the market.

The V-Con project is one example that may pave

the way to broad application of Smart Cities and

Geodesign solutions. We need more such initiatives

in all affected sectors of our society in order to

make BIM and GIS databases better connected and

help the vision of really Smart Cities.

References

• buildingSMART (2015). IFC Overview summary, at http://www.buildingsmart-tech.org/specifications/ifc-overview

• Enbysk, Liz (2013). How smart transportation systems reduce emergency response times, saves lives. Smart-Citiescouncil, at http://smartcitiescouncil.com/article/how-smart-transportation-systems-reduce-emergen-cy-response-times-saves-lives

• Flaxman, Michael (2010), quote from Geodesign Summit, Redlands, California. Amended by Stephen Ervin (2012)

• Isaac S., Sadeghpour F., and R. Navon (2013), Analyzing building information using graph theory, Proceedings of the 30th ISARC, Montréal, Canada at http://www.iaarc.org/publications/proceedings_of_the_30th_isarc/analy-zing_building_information_using_graph_theory.html

• Reichardt, Mark E. (2012). Driving geospatial interoperability communities of interest, 2012 NGAC Meeting, at https: //www.fgdc.gov/ngac/meetings/april-2012/open-geospatial-consortium-activities-reichardt.pdf

• Safe Software (2015), How to Create BIM & GIS Interoperability, http://www.safe.com/webi

• Steinitz, Carl (2012). A Framework for Geodesign, Redlands, Esri Press

• Verstraete, Christian (2015). You don’t want vendor lockin...but aren’t you always lockedin?,ITPeerNetwork,at https ://communities.intel.com/community/itpeernet-work/blog/2015/03/11/you-dont-want-vendor-lock-in-but-arent-you-always-locked-in

• Wikipedia (2015). Smart city, at https://en.wikipedia.org/wiki/Smart_city


erfaringer fra vejdirektoratets projekt om realtids-trafikdata baseret på bilisters GPs-oplysninger.

Danmark har igennem mange år haft en føren de position inden for digitalisering, og de første sMArt CitY-initiativer er ved at blive realiseret. vejdirektoratet har sammen med Devoteam siden 2014 arbejdet for at etablere en sMArt CitY-trafikløsning med realtidsdata fra billister. Denne artikels ambition er at dele vores erfaring er fra projektet med andre, der står – eller kommer til at stå - med de samme udford ringer.

sMArt CitY eller sMArt COMMUnitY 1 (herefter: sMArt CitY) er nogle af de termer, der anvendes til at beskrive en trend i de store internationale by-samfund såsom rio, London, Barcelona, München, tokyo og københavn. trenden går ud på at gøre bysamfundene mere ”intelligente” ved at opsamle, analysere og anvende information om og fra by-rummene. et af fundamenterne i sMArt CitY er digitalisering. Keywords: Smart City, digitalisering, geografiske information, intelligente trafiksystemer

Thomas W. Møller Devoteam Consulting A/s [email protected]

perSpektiver og udfordringer ved at etablere Smart city og Smart community-løSninger

Sine Dyreborg vejdirektoratet [email protected]

1 sMArt COMMUnitY betegner anvendelse af smarte teknologier til at fremme vækst og udvikling i land-distrikter og mindre byer


smart city – deFinition aF beGrebet oG den aktueLLe udbredeLse aF smart city i danmarkBegrebet, SMART CITY, er et rummeligt begreb, der

indeholder alt fra smarte cykelparkeringer, skæve

skraldespande, bycykler, trafikstyring, effektiv

affaldshåndtering, parkeringssystemer, energiplan-

lægning mv. Ambitionen i SMART CITY er at skabe

et godt bysamfund med økonomisk vækst, der

anvender optimal ressourceudnyttelse, yder god

borgerservice og samtidig er bæredygtig samt

omstillingsparat i forhold til forandringer.

Mange teknologier såsom stedbestemte

realtidstrafikdata, tracking systemer og sensorer,

der indgår i SMART CITY-initiativer, er nu tilstræk-

keligt modne til at kunne omsættes kommercielt i

de løsninger, som markedet udvikler. Der er i

Danmark stort fokus på at skabe SMARTE byer og

landområder - i 2014 viste en analyse fra Ministeriet

for By, Bolig og Landudvikling , at hovedparten af

kommunerne i større eller mindre grad allerede

arbejder med SMART CITY-initiativer (Ministeriet

for By, Bolig og Landudvikling, 2014).

Mange private og offentlige aktører har i de

seneste år været med til at sætte SMART CITY på

dagsordenen. For eksempel har Realdania haft et

strategisk fokus på SMART CITY klimatilpasnings-

initiativer, hvilket har igangsat udvikling af mange

nye byrum i kommunerne. Tendensen ses også hos

private parkeringsudbydere, hvor f.eks. EasyPark

har skabt sammenhængende parkeringsløsninger

på tværs af næsten alle kommuner, der har

resulteret i landsdækkende standarder samt

datamodeller for parkering og afregning. Nu er der

også erfaringer fra arbejdet med bl.a. smarte

hospitaler og smart trafik, hvor Region Hoved-

staden og Vejdirektoratet har designet, gevinst-

estimeret, udbudt, indkøbt og implementeret store

mobility-, sporings- og positionsdatasystemer.

Projekterne har alle til formål at skrabe atraktive

bysamfund, med optimal ressoruceudbyttelse og

god bogerservice.

Erfaringerne fra både de offentlige og private

projekter viser, at det er teknologisk, økonomisk og

organisatorisk muligt at skabe smarte løsninger,

der giver gevinster. Det sker ved tilrettelæggelsen af

en strategi, der identificerer de forretningsmæssigt

”rigtige” udviklingsprojekter og dernæst etablerer

den grundlæggende datamodel og infrastruktur.

Et eksempel på et udviklingsprojekt, der ligger

indenfor ambitionen i SMART CITY, er realtidsdata-

projektet i Vejdirektoratet. Devoteam har hjulpet

Vejdirektoratet med at indkøbe data til pilotprojek-

tet. Pilotprojektet har til formål at optimere

trafikinformationen ved at opsamle realtidsdata

fra billister for at skabe et større overblik for både

trafikanterne og Vejdirektoratet.

anvendeLse aF biListers reaLtidsdataVejdirektoratet gennemførte, med hjælp fra

Devoteam, henover vinteren 2014/15 et EU-udbud

med formålet at indgå kontrakt med en leverandør

om realtidstrafikdata. På baggrund af en konkur-

rencepræget dialog med tre bydende blev der i juni

2015 indgået kontrakt med Inrix der kunne levere

det økonomisk mest fordelagtige tilbud. Inrix

leverer GPS-baserede realtidstrafikdata, statistiske

data for det strategiske vejnet og for de øvrige

statsveje. Aftalen indeholder en option hvor

kommunerne kan købe de samme data de næste to

år. Kontrakten kan forlænges i to gange et år.

Trafikdata har tidligere været baseret på bl.a.

statistisk information fra trafikanternes køretøjer

- indsamlet via vejsideudstyr eller spoler i vejen få

steder i Danmark (København, Århus og i Trekant-

området), se figur 1 på side 27. Data fra dette

vejudstyr har givet nogle meget præcise data om

antallet af biler samt hastigheden. Disse statiske

data har givet Vejdirektoratet mulighed for - på

disse få strækninger - at lave analyser af motorvej-

strafikken, undersøge trængselspletter osv., som

kan anvendes statistisk og i fremtidig planlægning

af vejstrækninger og vejarbejder.

Målet med at indkøbe og anvende realtidsdata er

at få en bredere dækning af trafikdata og hermed et

mere dækkende billede af, hvordan trafikken

forløber. Som det fremgår af højre side af figur 2 på

side 28 – skaber realtidsdata for det statslige vejnet


De udvidede muligheder med realtidsdata-

projektet er følgende:

• information om rejsetid

• rejsetidsprognoser

• trafiktilstande

• ekstraordinær kø

• hændelsesdetektering

Vejdirektoratet prioriterer højt, at trafik-

information om ekstraordinære kødannelser kan

komme hurtigt frem til trafikanterne, så de tidligst

muligt kan blive adviserede om kødannelser, der

normalt ikke kan forventes på det pågældende

tidspunkt. På denne måde vil trafikanterne få et ret

præcist billede af deres rejsetid og mulighed for at

søge alternative ruter.

Realtidsdataene om hastigheder vil kunne

bidrage til, at Vejdirektoratet kan yde en bedre

indsats ved f.eks. uheld på motorvejene.

Vejdirektoratet kan meget hurtigere end tidligere

sende beredskabet og genskabe fremkommelig-

heden på f.eks. et ulykkessted.

Planen er, at realtidstrafikdataene skal flyde ind

i Vejdirektoratets Trafikcenter primo november

2015, hvor der køres test på dataene. Her er målet,

at det stilles til rådighed for trafikanterne via

Vejdirektoratets trafikinformationstjenester inden

udgangen af året.

ny LærinG/udvikLinG i veJdirektoratet som FøLGe aF proJektet For at Vejdirektoratet kan modtage de nye realtids-

trafikdata, har direktoratet skullet udvikle nogle

nye webservices og systemer for at kunne modtage

og parametersætte disse data. Vejdirektoratet har

hele grundsystemet og servere på plads, da

Vejdirektoratet tidligere har modtaget statistiske og

live-data fra vejsideudstyr.

Vejdirektoratet har mange års erfaring i at

modtage og analysere statistiske data fra vejsideud-

styr, hvilket har givet et bredt vidensgrundlag i

forhold til hvilke krav, der skal sættes til dataenes

kvalitet. Vejdirektoratet har udviklet et omfattende

testsystem til datakvaliteten med mulighed for

bedre mulighed for Vejdirektoratet for hurtigt at

agere – alt sammen med henblik på at forbedre

fremkommeligheden. I tillæg til realtidstrafikdata

får Vejdirektoratet også flere data om trafikken til

statistiske anvendelser f.eks. til analyse af trængsel

og hvordan trafikken omkring større vejarbejder

bedst kan forløbe – generelt giver flere statistiske

data forbedret grundlag for analyser.

Realtidstrafikdata modtages fra en bred flåde af

køretøjer, som har indgået aftale med Inrix. Det kan

eksempelvis være data fra erhvervsdrivende med

større flåder af køretøjer, bilister med smartphones,

udbydere af GPS-baserede smartphonenavigations-

tjenester og leverandører af navigations udstyr til

køretøjer og bilfabrikanter. Vejdirektoratet har

sikret, at persondatalovgivningen overholdes ved at

lægge strenge krav ind i kontrakten om, at alle

kilder skal være anonymi serede.

Som det ses på figur 2 modtages data fra et

større geografisk område end tidligere, men nu

kun for en delmængde af køretøjerne på stræk-

ningen. Dermed adskiller data sig væsentligt fra

traditionel detektering via vejsideudstyr, hvor al

trafik måles fra ét punkt.

Dataene dækker det strategiske vejnets tre

niveauer 1, 2 og 3 samt øvrige statsveje i 2015 -

og fra 2016 udvalgte væsentlige kommuneveje.

Figur 1. Eksempel på nuværende dækning.


Fotogrammetriske geodata har i mange år været

indkøbt på markedet hos en leverandør som følge

af en veldefineret specifikation for data og

omfattende kvalitetssikring. Så erfaringerne herfra

dokumenterer, at det er muligt. Fotogrammetriske

data har dog en lang statisk horisont (flere år) og

kan i den sammenhæng ikke direkte sammenlig-

nes med realtidsdata.

Realtidsdata, der indkøbes via en leverandør,

som måske trækker på mange underleverandører,

minder på mange måder om en crowd-sour-

cing-model. Crowd-sourcing på dette område går i

grove træk ud på, at mange bidrager med indsam-

ling, ajourføring og vedligeholdelse af data. På

denne måde kan man indsamle og vedligeholde

massive mængder af data for meget små omkost-

ninger og på relativt kort tid.

De nye måder at anskaffe data stiller krav om

fast og sikker overvågning af datakvaliteten i

forhold til de aftalte standarder/dataspecifikatio-

ner. For at kunne opretholde autoritative myndig-

hedsdata, der gør en forskel i forhold til ikke-auto-

ritative data – bliver det afgørende at kunne

dokumentere kvaliteten.

Erfaringerne fra realtidsdataprojektet bliver

spændende at følge. Det er kun fantasien, som

bod, hvis Inrixs data ikke lever op til de stillede

krav.

Inrix og Vejdirektoratet har arbejdet intensivt på

at få alle tekniske systemer til at fungere og ser frem

til, at data flyder ind til gavn for de danske bilister.

De næste to år er et pilotprojekt, hvor der skal laves

grundlæggende analyser og evalueringer. Disse skal

vise, om dette er løsningen for en fremtidig kilde til

hændelsesdetektering og trafikinformation.

perspektiver For smart city, reaLtidsdata oG den oFFentLiGe sektor teknologiske perspektiver Både realtidsdata og SMART CITY-initiativer stiller

teknologiske krav til håndtering af data. Som

erfaringerne fra Vejdirektoratet viser, er der

løsninger til rådighed. Modenheden i de anvendte

systemer og hos leverandørerne er fuldt ud til stede

ift. Vejdirektoratets løsning.

datakilder og perspektiverne I forhold til SMART CITY-udviklingen kan man

forestille sig, det ikke kun er én leverandør men

potentielt mange leverandører, der leverer data til

en løsning. Ydermere kan data være realtidsdata

eller statiske data.

Figur 2. Eksempel på fremtidig dækning.


I traditionelle Business Case-modeller er

mindskede udgiftsbudgetter/besparelser en

forudsætning for at få en positiv business case, men

man kan også have en tilgang, hvor man ser den

samfundsmæssige nytte af at gennemføre et projekt.

Her vil det typisk kræve en business case-model, der

medregner gevinsterne for samfundet som helhed

– en Business Case hvor f.eks. sparet rejsetid hos

borgerne skaber et øget nytte for samfundet eller

hvor ny frie data om trafik og rejsemønstre giver

virksomheder mulighed for at forbedre logistikken

og dermed sikre en øget vækst i virksomhederne og

i samfundet som helhed.

konkLusion Som ovenstående case om realtidsdata viser, findes

der eksempler på SMART CITY-teknologier, hvor

organisationerne/ledelsen, datakilderne og økonomi-

en - og dermed den samlede løsning – er veltestede og

modne, og at der kan realiseres flere nye løsninger.

Mulighederne er mange og potentialerne store.

Der kan de kommende år være behov for en større

koordinering af indsatserne, således at den ”dybe

tallerken” ikke skal opfindes på ny hver gang af alle

myndigheder – i staten, i regionerne og i kommuner-

ne. Koordineringen kan være på mange niveauer og

på mange måder – det kan være som fælles løsninger,

som læringsnetværk, som fælles arkitektur eller som

fælles standarder og datamodeller.

Hvor SMART CITY initiativer tidligere har været

teknologisk drevet – er der nu en begyndende

trend mod en bredere tilgang. En tilgang hvor både

organisation, økonomi, data og teknologi sammen

skaber SMARTE løsninger - der giver gode bysam-

fund med økonomisk vækst, med optimal ressour-

ceudnyttelse, god borgerservice og samtidig er

bæredygtige og omstillingsparat.

Referencer

• BT, 2012 http://www.bt.dk/danmark/pris-for-denne-ba-enk-1-mio.-kroner

Ministeriet for By, Bolig og Landudvikling, 2014, SMART CITY I DE DANSKE KOMMUNER - STATUS OG INITIATIVER

sætter grænserne for, hvilke datakilder der kan

anvendes til SMART CITY-initiativer.

orGanisation oG LedeLsesperspektiver Nye datakilder og eksterne dataleverandører kan

potentielt stille krav til en ny organisatorisk

selvforståelse og rolle for den organisation, der

udstiller data. F.eks. at en organisation går fra at

være dataproducent til at være en organisation, der

distribuerer en ekstern leverandørs data. Dermed

foregår produktionen af data ikke længere inhouse,

hvor man kan følge, sikre og garantere kvaliteten i

form af nøjagtighed og aktualitet. Og at håndtere

det giver nye organisatoriske udfordringer.

Medarbejdere og brugere af data træffer på

daglig basis beslutninger på baggrund af de

offentlige data. Hvis der er en risiko for, at data kan

give f.eks. forlængede rejsetider, uforudsete

kødannelser og dermed øgede udgifter, så stiller det

krav til en ny kommunikation og formidling af de

forudsætninger, der ligger til grund for data. Det er i

den forbindelse centralt, at data får en større

dækning og kommer i realtid på tværs af hele landet

– og at der samtidig opnås en høj kvalitet af data.

økonomi og business case i smart cityprojekter SMART CITY-initiativer har været beskyldt for at være

politiske ”trofæprojekter”, hvor business casen nogle

gange har været mindre troværdig. Eksempelvis en

bænk i Københavns Kommune til 1 mio. kr. (BT, 2012)

Rationaliteten i realtidsprojektet i Vejdirektora-

tet er dog baseret på det faktum, at Vejdirektoratet

ønsker at udvide dækningen af realtidstrafikdata

inden for en overskuelig økonomisk ramme. Dette

var ikke muligt med de nuværende systemer, så

som vejsideudstyr og spoler, da dette er dyrt at

opstille og vedligeholde. Derfor var man nødsaget

til at undersøge nye muligheder for at få tilveje-

bragt data - og en ekstern leverandør endte med at

blive løsningen.

Fagligt er det vigtigt at understrege, at med de

rigtige værktøjer og modeller er det muligt at lave

business cases for alle projekter.


indLedninGSmart Cities er det nye sort i større byer og er sat på dagsordenen i et stort

antal kommuner på tværs af Danmark. Visionerne og målene er mange og

projekterne er mangfoldige. Som med alle andre hypede tiltag fører det en

masse ny teknologi med sig, nye platforme, nye gadgets, dingenoter,

sensorer, nye applikationer og et nærmest uendeligt behov for kapacitet. Vi

skubber datagenerering og dataopsamlingen ud i omgivelserne og i det

yderste af vores organisation. Men er vi klar til at håndtere denne udvikling i

de eksisterende organisationer med de nuværende roller?

Artiklen er blandt andet skrevet med udgangspunkt i mine erfaringer og

refleksioner om, hvordan vi fremover skal håndtere de udfordringer, vi står

smart Cities er det nye sort i større byer og er sat på dagsordenen i et stort antal kommuner på tværs af Danmark. visionerne og målene er man-ge, og projekterne er mangfoldige. som med alle andre hypede tiltag fører det en masse ny tekno-logi med sig, nye platforme, nye gadgets, dinge-noter, sensorer, nye applikationer og et nærmest uendeligt behov for kapacitet. vi skubber data-generering og dataopsamlingen ud i omgivel-serne og i det yderste af vores organisation. Men er vi, som organisationer, klar til at håndtere denne udvikling i de eksisterende organisationer med de nuværende roller? Keywords: Smart City, Geografisk information, IoT, governance

Jes Bruun OlsenAtkins A/[email protected]

Smart citieS – 50 mia. ”ting” på internettet – og det Skal StyreS!


overfor, med den accelererede udvikling som

Internet of Things repræsenterer. At problemstil-

lingen er reel, og at det er nødvendigt seriøst at

adressere den nye kommende kompleksitet, har jeg

fået bekræftet gennem arbejdet med kvalitets-

sikring af et projekt omkring etablering af en

intelligent parkeringsløsning i Norge. Resultatet af

mine refleksioner er desuden blevet præsenteret i

et oplæg på Kortdage 2015.

Som digitaliserings- og forretningsansvarlige

omgiver vi os med denne til stadighed mere

komplekse virkelighed. Dét sætter vores evne til at

styre og koordinere udviklingen under pres.

Samtidig skal det alt sammen give en betydelig

gevinst til vores organisation. Denne artikel gennem-

går nogle af de styrings– og koordineringsmæssige

udfordringer, kommunerne står overfor, og anviser

en model til en start på denne, for mange, påkræve-

de forandringsrejse: En ny governancestruktur, der

modner processer og organisation i forhold til

systematisk at arbejde med strategisk alignment,

værdigenerering og styring, sikkerhed og risici,

styring af ressourcer og performance.

Fremtiden – er nu!Der er en række teknologiske principper/mega

trends, der i øjeblikket er med til at definere og

danne grundlaget for udviklingen af nye services:

• Mobile platforme (Smartphones, tablets etc.),

hvor services for borgere og medarbejdere

udvikles og implementeres i en lind strøm

både som en supplerende adgang (udover

eksisterende pc-baserede løsninger) og som

serviceudvidelser. Teknisk betyder udvik-

lingen en markant stigning i antallet af

applikationer (apps), udvidelser i grænse-

flader og integrationer, nye platforme m.v.

• Big data, hvor sammenstilling og behandling

af store, tilgængelige mængder af data giver

mulighed for udvikling af nye services,

effektivisering af servicekanaler m.v. Frigivelse

af grunddata er et af eksemplerne på denne

trend.

• Internet of Things, hvor ting, redskaber,

sensorer, tøj og biler m.v. kobles til internettet

med henblik på at etablere grundlaget for nye

services, anvendelser m.v. Dette flytter

dataindsamling til et hidtil ikke set decentralt

niveau. Det forventes, at der er 50 mia. ting på

internettet i 2020 – altså lige om lidt.

På et lidt andet niveau er der fra den kommunale

organisations side fokus på at øge effektiviteten og

skabe nye værdifulde services, opgaveløsninger m.v.

gennem anvendelse af:

• Velfærdsteknologier, som fokuserer på at

understøtte opgaver, forpligtigelser og services

over for borgerne gennem anvendelse af nye

teknologier (blandt andet mobile platforme,

internettilsluttet udstyr og sensorer)

• Design, projektering, udførelse og drift og

vedligeholdelse af bygninger og anlæg

gennem anvendelse og integration af Cad, GIS

og Asset Management løsninger.

• Mobilitet. Udvikle og flytte borgernes egen

service og støtte til de mobile platforme

Generelt set øger disse trends kompleksiteten i

kommunernes IKT-anvendelse, da initiativ,

udvikling og anvendelse flyttes fra centrale

initiativer til et meget decentalt niveau – ud i den

skarpe ende af organisationen. Det er her effekti-

viseringsdagsordenen skal løses.

udFordrinGenI gennem de senere år har vi set fremkomsten af

nye teknologier, koncepter for teknologiudnyttel-

se m.v. som har medført et nødvendigt opgør

med den vante måde at håndtere og styre

IKT-anvendelsen på. Dels er initiativet flyttet fra

en central styring (de fælles administrative

kerne- og infrastrukturløsninger) til et mere

forretningsdrevet perspektiv, hvor forretnings-

enhederne selv tager initiativ til afprøvning,

udvikling og implementering af nye IKT-baserede

løsninger. Udviklingen inden for anvendelse af


IKT-afdelinger. Deres udbredelse kom især fra det

pædagogiske område, hvor de i starten var et

individuelt redskab, men hurtigt blev gjort til et

strategisk pædagogisk læringsværktøj. I mange

kommuner var Skole-it allerede en del af den

centrale IKT-afdeling, og her havde man så

pludseligt en ny udfordring med et nyt produkt, på

en selvstændig platform, som ikke passede ind i det

normale sikkerheds- og driftsmiljø. Det gjorde det

ikke nemmere, at der også bredte sig et ”behov” fra

byrådene om at kunne anvende disse tablets til

effektivt at understøtte byrådsarbejdet. Det betød

hurtigt, at de kommunale ledergrupper tog tablets

til sig for at kunne være med på den samme

platform som byrådene.

I løbet af relativ kort tid var man nødt til at

bruge ressourcer på at etablere en ny serviceplat-

form (og -arkitektur) for at kunne understøtte både

SmartPhones og tablets.

BOYD (Bring Your Own Device) I sidste halvdel af

00’erne og i starten af 10´erne tog anvendelse af

digitale medier fart i de danske skoler, og presset

på anvendelse af netværk m.v. blev hurtigt en

flaskehals mange steder, som følge af de mange

elever der skulle på ved starten af hver lektion. I

mange kommuner havde IKT-afdelingen overtaget

driften af skole-it fra de enkelte skoler, og havde i

effektivitetens navn og for at reducere investe-

ringerne i området koblet dem på kommunens

netværk. Resultatet var en sikkerhedsmodel, der

gjorde det umådeligt tungt med pålogningstider

på 5-10 min. Absolut uacceptabelt. Næste skridt,

som følge af nationale mål om at styrke anvendelse

af it i undervisningen og sikre hurtigt Internet, var,

at de fleste kommuner indførte den såkaldte

BOYD-model, hvor eleverne ikke nødvendigvis

skulle forsynes med it-udstyr men kunne med-

bringe og benytte deres eget. Det ændrede behov

udløste en massiv investering i trådløse netværk

med høj kapacitet, frigjort fra den kommunale

sikkerhedsmodel. Og igen startede initiativet

decentralt og blev en udfordring for IKT-afdelingen.

Fra få til mange – og komplekse anvendelse af sensorer

(og internetkoblet udstyr - Internet of Things) i

velfærdsteknologier er et godt eksempel herpå.

Man havde egentlig meget godt styr på infra-

strukturen. Man havde et fåtal af leverandører af

kommunale IKT-løsninger og alle udviklet til at

kunne understøtte den kommunale sikkerheds- og

driftsmodel. Dette kom under pres og i det efter-

følgende gives et par eksempler til at belyse dette.

PDA’er gjorde fremtiden håndholdt, og man så

hurtigt en måde at understøtte decentrale,

steduafhængige opgaver på med en IT-baseret

løsning. De udgjorde kun en begrænset udfordring

i IKT-mæssig forstand, da de ofte var ”født” som

frontend for en given systemløsning (eksempelvis

til opslag og registrering af informationer i

borgernes sundhedsjournaler m.v.) og dermed var

en del af sikkerhedsmodellen.

SmartPhones tog over og var i starten et anarki-

stisk redskab dels på grund af deres mangfoldighed

og deres tilgængelighed (udbredelse, grænseflade,

pris etc.). Udover at være mobile telefoner er de

født til at kunne benytte et utal af app’s, specialud-

viklede applikationer, informationssøgning,

internetopkobling, GPS og et utal af styresy-

stems-platforme. Man så dem hurtigt som en måde

at få de decentralt organiserede medarbejdere

(lærere, SOSU-personale etc.) understøttet i forhold

til deres administrative opgaver (tidsregistrering,

kørselsregnskab, mail, kalendere, informations

tjenester m.v.), og som en platform til ”smart” at

understøtte deres opgave løsning. En konsekvens

var, at IKT-afdelingen kom under pres, da disse

enheder blev anskaffet decentralt og ikke var født

som en naturlig del af kommunes sikkerheds- og

adgangsregler, ligesom opdatering, distribution og

vedligeholdelse af applikationsporteføljen ikke var

standardiseret og dermed krævede ekstra ressour-

cer. Det tog et par år og så var IKT-afdelingen klar

til at lukke dem inden for i den sikre verden, som

er et grundlæggende paradigme i den kommunale

IKT-anvendelse. Som en konsekvens fik man i

forretningsenhederne måske ikke realiseret den

forventede nytte af teknologien, så tidligt som man

havde forudset. Og det gav frustrationer.

Tablets kom på tilsvarende måde bag på de fleste


forhold til indsamling af data, styring af aktiviteter

m.v. eksploderer i disse år. Mobiltekno logien har

gjort anvendelse af sensorer billig og tilgængelig. Vi

anvender stort set alle sensorbaseret teknologi i dag

i større eller mindre grad på hjemmefronten, i vores

fritidsliv m.m.. Det har givet nogle udviklingsper-

spektiver (og et marked) som kan udnyttes og som

kan medvirke til at øge effektiviteten i vores

serviceudbud (opsamling af data i forbindelse med

sundheds- og omsorgsydelser, driftsovervågning af

anlæg, bygninger, arealer m.v., anvendelse af

faciliteter, opsamling af miljødata). Værdien vil

komme fra anvendelsen af mange forskelige typer af

sensorer installeret fysisk i natur, beklædning,

apparater, bygninger, køretøjer m.v. Men data skal

være tilgængelige, behandles, analyseres, og

anvendes. Og deri ligger også en række udfordringer.

Endelig har monopolbruddet, hvor kommunerne

under KOMBIT-paraplyen i de kommende år udskifter

store dele af deres kerne-løsninger fra én leverandør

(KMD) med løsninger fra nye leveran dører medført et

øget behov for at kommunerne opruster i forhold til

styring af kontrakter, integrationer mellem kerneløs-

ningerne og lokale specialapplikationer m.v. Selv med

nye veldefinerede arkitekturer vil det blive en opgave

af holde styr på alignment mellem løsninger og

integrationer, kontrakter m.v. Dette arbejde bliver

ikke mindre i fremtiden i forbindelse med den øgede

kompleksitet.

Alt i alt eksempler på hvordan IKT-afdelingens

politikker, strategier og handlingsplaner, samt

økonomiske finansieringsmodeller, er blevet (og

stadig bliver) overhalet af en udvikling, skabt i

forhold til at løse problemstillinger andre steder i

organisationen, eller hvor en forretningsenhed ser

en værdimæssig (effektivisering) fordel i at tage nye

teknologier etc. i brug.

Fra forretningsenhedernes side er der ikke altid

den store fokus på helheden. Ofte er fokus primært

på at optimere i forhold til egne mål. På tilsvarende

vis er erfaringerne med forretnings områdernes

pilotprojekter, at de er gode til at starte dem, men

knap så gode til at bringe dem i mål og få dem

modnet til drift. Så alt i alt må der være et fælles

behov for at ændre på tingenes tilstand.

I forbindelse med kvalitetsikring af et SmartCity


• Den fremtidige service og supportmodel

herunder, hvem der har ansvar og hvilke

roller der skal varetages. Også mere specifikt;

hvordan skal support- og servicemodellen

indrettes for de teknologikomponenter, der

ikke naturligt i dag er en del af IKT-afdelingen

• Sikkerhedsaspekter (kobling til kommunens

netværk, uønsket adgang m.v.)

• Integrationer og snitflader til andre relevante

løsninger (eks. Vejområdet, private p-operatø-

rer, administrative løsninger)

• Udvikling af apps (valueadded service fra

marke det etc.)

• Realisering af nytte/benefit m.v., herunder

hvem tager investeringen, og hvem og hvor

realiseres nytten/gevinsten

• Kompetencer i forhold til de fremtidige opgaver.

• Overensstemmelse og sammenhæng med

kommunes øvrige digitaliseringsstrategier og

initiativer.

Det er forhold, som rækker ud i den resterende

del af organisationen og eksternt, herunder også

projekt, der drejer sig om etablering af en ny samlet

løsning omkring styring af trafik og parkering i en

stor norsk by, kan man konstatere disse udfordrin-

ger i højeste grad. Pilotprojektet gennemføres af en

projektgruppe i en faglig enhed (By og Miljø).

Projektet er teknisk i front og adresserer – isoleret

set, alle de relevante emner, for at kunne gennemfø-

re pilotprojektet og sikre, at der ligger en realiserbar

løsning, eksempelvis:

• Kortlægning og digitalisering af parkerings-

muligheder

• Klassifikation af parkeringspladser, steder m.v.

• Anvendelse af nye teknologier: sensorer,

intelligent skiltning m.v.

• Udvikling af relevant forretnings og itarki tek

tur, for egne mål

• Indsamling og bearbejdning af data – realtid

m.v.

• Udvikling af parkeringspolitikker og strategi-

er i en større miljøpolitisk kontekst

• Udvikling af en Business CaseHvad projektet

ikke umiddelbart adresserer er:


ForandrinG i roLLer oG ansvar starten på den nye reJseDet er givet, at forandringen må ske ved, at alle par-

terne i denne udvikling erkender deres nye roller

og ansvar. Det gælder både forretningsenhederne

og IKT-afdelingen, men i højeste grad også

beslutningstagerne (ledelsen og politikerne).

Strategisk set sker der et paradigmeskifte i fokus

fra i dag, hvor man leverer services (provider), til

man fremover i højere grad også skal tænke på at

muliggøre services (enabler). Dette gælder i

relationen mellem IKT-afdelingen og forretnings-

enhederne men også i relationen mellem forret-

ningsenhederne og eksterne parter (borger,

virksomheder, serviceleverandører m.v.). Trenden

ses blandt andet udmøntet i åbning af adgang til

grunddata, hvor der i dag er mange serviceud by-

dere (ikke offentlige virksomheder), der bygger

løsninger oven på de tilgængelige data og

udstillede services (eks. DinGeo).

For forretningsenhederne handler det

specifikt om at få sat fokus på nedenstående

områder for at blive i stand til at udnytte de nye

muligheder og sikre fleksibilitet i forhold til det

fremtidige samarbejde om effektiviseringsdags-

ordenen:

• Infrastruktur: arkitektur, båndbredde,

standarder

• Integration og grænseflader til interne og

eksterne services

• Sikkerhed (adgang)

• Kontraktstyring

• Service og supportstruktur og tilgængelighed

• Driftsstabilitet og sikkerhed

• Kompetencer

For IKT-afdelingen er behovet at konsolidere og

koordinere forretningsenhedernes og eget behov

på følgende områder, hvis det skal være i stand til

at understøtte udviklingen:

• En opdateret arkitekturmodel for at sikre

support af fremtidige forretningsbehov

• Øget fleksibilitet i netværksstruktur og

segmentering (forskellige netværk, sikkerheds-

niveauer, stabilitet, tilgængelighed m.v.)

IKT-afdelingen, som det nødvendigt at have styr på,

hvis projektet skal realisere sine mål og blive klar

til drift.

Man må forudsætte, at udviklingen vil

accele rere og tage betydelig fart efterhånden, som

implementering af de nævnte megatrends

modnes. Det vil øge kompleksiteten og behovet for

en fleksibilitet, der kan understøtte denne

udvikling.

Vi kan opsummere de områder, hvor IKT-afde-

lingen vil være udfordret i fremtiden:

• Overblik over initiativer og drivere af

digitali seringen, der udspringer fra

forretningsen hederne (eksempelvis Miljø,

Veje, Sundhed og Omsorg, Park og Anlæg,

Transport)

• Antallet af leverandører (af data, services,

”ting”, applikationer etc.)

• Integration fra og til andre løsninger, inhouse

og eksterne, udstilling af services

• Vedligeholdelse og opdatering m.v. der er

alignet

• Sikkerhed – formål, segmentering af nettet,

sikkerhedsmodeller, nye netprotokoller

• Kompetencer – forretning, teknologi,

anvendelse m.v.

• Realisering af benefits – hvor og hvem skal

realiserer gevinsten, og hvordan sikres

IKT-afdelingens økonomi

• Investeringer – i platform/infrastruktur og

udstyr

• Kontraktstyring (mere udstyr, flere typer, apps

etc. og flere leverandører)

• Strategier og arkitektur, som understøtter

lokale formål, men som skal hænge sammen

med de overordne strategier.

• Modningsprocesser fra ide, pilot til drift

• Kultur (Hvor træffes beslutningerne centralt

eller decentralt, koordineret eller ikke)

Alt i alt vil kompleksiteten stige betragteligt,

og hvis ikke IKT-afdelingen skal være en hindring

for forretningsenhedernes realisering af nye

effektive tiltag, eller at der opbygges parallelle

(IKT-)organisationer, skal der ske noget.


forskelligartede behov. Samlet set er der behov for:

• Forbindelse mellem forretningsområdernes

ønsker og behov og IKT-afdelingens mulighe-

der - alignment

• En fælles proces for behandling af IKTudvik-

ling og aktiviteter og forretningsudvikling,

herunder realisering og fordeling af gevinster,

investeringsmodeller etc.

• Balance mellem anvendelse af IKT og

ressourcer, kompetencer m.v.

• Veldefinerede og klare ledelses og styringsmål

og strukturer

• En ansvarlig og effektiv udnyttelse af IKTres-

sourcer

• Håndtering af risk og sikkerhed i et forret-

ningsmæssigt perspektiv

Ovenstående figur er et eksempel på en model,

der beskriver de nødvendige styringsområder.

Strategisk aligment: Sikre at der er ovensstem-

melse mellem organisationens strategi, ikt-strategi-

en og forretningsenhedernes strategier, koordinere-

de handlingsplaner, at roller og ansvar er forankret

og implemeteret.

• Styring af leverandører, kontraktstyring m.v.

• Håndtering af øget kompleksitet i forhold til

drift, service m.v.

• Kompetencer

ForretninGsdrevet iktGovernanceEn umiddelbar løsning på problemstillingerne er

at udvikle og etablere en (ny) governancestruktur,

der modner processer og organisation i forhold til

samlet og systematisk at arbejde med de problem-

stillinger, der er nævnt ovenfor. Dette skal ske i en

mere struktureret og tematiseret form eksempelvis

ved at adressere strategisk udvikling og alignment,

værdigenerering (business cases, gevinstrealisering

etc.), sikkerhed og risici, styring af ressourcer

(investeringer og menneskelige), samt opfølgning

og evaluering af resultater.

Mange kommuner har allerede Governance-mo-

deller på plads, men de er fokuseret på, at det er på

IKT-afdelingens præmisser, hvor det ofte handler

om at styre udviklingen i takt med IKT-afdelingens

ressourcer og behov, og i mindre grad om at være i

stand til at håndtere forretningsområderne meget

Figur 1. Governance Model


governanceproces, så man sikrer et modent

fundament for at kunne møde de nye tendenser.

Det er ikke nødvendigvis afgørende hvordan

man organisatorisk indretter sig, men derimod er

det væsentligt at man fastlægger et forløb (årshjul),

der sikre at der er en systematisk forberedelse og

behandling af de relevante teamer, og at der er

seriøs og konsekvent deltagelse af de tre parter i

governancestrukturen: Ledelsen, IKT-afdelingen og

Forretningsenhederne.

Erkendelsen af behovet for at skabe de rammer,

der skal til i form af politikker, samarbejdsfora,

understøttende processer for koordination og

opfølgning, vil hjælpe den enkelte organisation med

at øge paratheden til den fremtidige nye orden:

forandringsparatheden, nye roller og ansvar, agilitet

i forhold til nye teknologier, en fælles rammearki-

tektur, håndtering af kompleksitet.

Og så er 50 mia. ting på nettet ikke længere en

helt så stor trussel, - men en mulighed!

Gevinstrealisering: Behandling af Business

Ideas, Business cases, styring og koordinering af

gevinstrealisering, fokus på en effektiv udnyttelse

af den samlede IKT i organisationen.

Sikkerhed og risikostyring: Behandling af risici

og sikkerhedsproblematikker med udgangspunkt i

organisationens behov, vedtagelse af sikkerhedspo-

litikker, drift og vedligholdelsesplaner m.v.

Ressourcer: Fokus på organisering og processer,

forretnings- og ikt-arkitektur, behandling af

investeringsportefølje(r), kompetencer, styring af

leverandører og kontrakter (koordninering m.v.)

Performance: Opfølgning på resultater og

fremdrift af IKT-projekter, gevinstrealisering,

forbedringstiltag m.v.

Realisering af modellen sker ved at styringsom-

råderne (de fem temaer) omsættes til politikker,

metoder og standarder, som alle forretningsenhe-

derne arbejder udfra, også IKT-afdelingen. En sådan

model vil kunne anvendes som skabelon for en

Figur 2. Tilpasset governance model


introductionThe Smart City concept has been around for some years now, aiming at

establishing a digital layer alongside the urban infrastructure to make data

about the city available to citizens, city authorities and industry. This digital

layer allows the different city stakeholders to improve and create new

innovative city services that ultimately aim at improving the experience and

the way citizens live in the city context. The core digital layer is important as

it gives the basis for building and improving these city services. The process

in this article, we discuss the current state of smart cities from a technological perspective. We argue that smart city developments are in a state of transition going from being technology-focused to now putting emphasis on the humans living in the cities. the transition is still latent in the smart city deployments, and we argue that quite a few existing as well as new smart city deployments are still relying on the old technology-focused approach to smart cities. We elaborate our own experiences in this particular field, and provide two concrete cases on how we are approaching citizen-empowering smart city technologies. Finally, we discuss how smart city technologies should respond to citizen needs. Keywords: IoT, Smart city, empowering citizens, empowerment

towardS Smart city democracy

Lasse Steenbock Vestergaard Alexandra instituttet A/[email protected]

João Fernandes Alexandra instituttet A/[email protected]

Mirko Alexander PresserAlexandra instituttet A/smirko.presser@ alexandra.dk


of creating these services must be as “democratic”

as possible, i.e. with the close involvement of the

city stakeholders including its citizens. This way,

the impact of the envisioned services is optimised

as we are addressing the real needs of the end-users

of such digital services.

Humans emerGe in smart citiesIn recent years, the term smart city has emerged

and is now widely (world-wide) used as a branding

and marketing concept. The Smart City Expo in

Barcelona is the latest example of this trend (Expo

2015). Up until now, the concept of smart city has

primarily been evolving around technology, where

deployment of sensors and building of IT infra-

structures has been in focus. This approach can be

seen in cities like Barcelona in Spain, Chicago in

US, and Songdo in South Korea. However, this

technology-driven approach has proven not to

reach its expected impact, as it lacks a bottom-up

approach where the city stakeholders have a much

more close involvement in this process. Cities

should not just be instrumented with sensors or

smart technological infrastructures, if there is no

assessment of the citizens’ needs/barriers and

therefore no certain impact on their quality of life.

Lately, this technology-focused approach has

been shifting its focus into including the citizens


emptied. Intelligent street lighting is all about

reducing municipal costs, by replacing light bulbs

with LEDs, and sensing people roaming the streets.

The latter is another cost reduction feature, that

makes lampposts only use electricity when it is

mostly needed, i.e. when a human is near.

One could argue that the existing smart city

infrastructures act mostly as cyber physical systems

(a network of interacting technological devises

reacting to in- and output from each other), where

the only innovative part is that technology has

succeeded in reducing humans to objects that can

be measured, and used as inputs for the system to

react according to a predefined behaviour. A

natural consequence of this is that citizens actually

become disempowered. Before intelligent street

lighting was deployed, citizens could rely on

lighting; if the street was lit, then it would stay

that way, and if it was dark it would stay like that.

As a human, it was possible to make a decision

based on the visual information, and one could

decide whether one would take the risk of walking

in the dark – or one would maybe even prefer

walking in the dark (for some this might feel more

secure – ’if I cannot see them, then they cannot see

me either’). This type of decision-making is no

longer possible. The street can be pitch dark when

looking at it from a distance, but it will light up

when a human approaches – the city becomes

completely unreliable, as the system reacts in a

default way without taking into account the

preferences of each of the citizens. And, what

about the person who wanted to walk in the dark?

He would be “caught” by the light. Being placed at

the epicentre of a light source can actually make

you more vulnerable, because it becomes harder to

see what is going on in the dark while people in

the dark easily can locate you.

This is of course an extreme view of the smart

city deployments, but most of the current deploy-

ments primarly consider humans as binary inputs

to the system - not necessarily adding direct value

to the citizens’ everyday life. Our critique is not a

novel discovery, and Rob Van Kranenburg already

as a key element causing a change in the way we

understand and approach smart cities. In essence,

we have begun to initiate smart city activities by

approaching citizens, and take this point of

departure in a citizen participation paradigm. This

particular approach is already on the European

agenda, and several EU projects are now getting

funding for doing research into this neo smart city

approach. The Horizon2020 project OrganiCity

(OrganiCity 2015) is a relevant example.

In the early days of smart city development, a

large number of sensors have been deployed for the

typical Smart X application, e.g. smart parking,

smart irrigation or smart transportation (eg.

around 20.000 sensors in the city of Santander in

Spain), and numerous IT infrastructures have been

built. Some people have marked this “first wave” of

smart cities as “smart city classic”, and it actually

seems that quite a few cities now have a valuable

Internet of Things (IoT) infrastructure. Recognising

that a lot of effort has been put into deployment,

we can now move into the domain of how to actual-

ly exploit the smart cities for the common good. As

a consequence, we have chosen to focus on the the

human-centered approach to smart cities in this

article. We argue that we are currently in a

transition phase, where the smart city classic

approach is still prevalent in most of the existing

and new smart city initiatives. In the following we

elaborate this argument further, and discuss

pitfalls and opportunities.

Humans in cyber pHysicaL smart citiesIn the neo smart city paradigm, one of the main

points is citizen empowerment – how do we make

cities better for citizens on their terms. Looking at

existing smart city technologies that have found its

way into the built environment, like intelligent

street lighting and trash bins, it becomes clear that

the smart city classic approach has been the way to

go. A trash bin do not take humans into account, it

only focuses on whether it is full or not, and sends

a notification to the utility when it should be


in 2008 referred to the tale of two cities: The story

elaborates two possible outcomes of instrumenting

the city with technology. One is how technology

can be used to create a city of surveillance – the

all-seeing eye – which monitors and autonomously

adjusts the society. The other is about how

technology is used as a support and help for the

citizens themselves – e.g. they can access street

cameras directly and scout for missing kids or

check if someone is hiding around the corner

(Kranenburg 2008).

Researchers and companies have started

working on solutions that fit better the human -

centric smart city approach. Concrete examples are

the open source Geiger counter from Safecast

(Safecast 2015), which empowers citizens to

measure and make background radiation from e.g.

Fukushima publicly available, and the recent

emergence of open data platforms (Ckan 2015).

Despite the fact that the human-centric approach

of smart cities is emerging and becoming stronger,

we still see quite a few technology deployments

that adhere to the smart city classic approach. In

the following section, we will discuss how to move

into the realm of humans, and provide two

examples of our approach.

power to tHe peopLeAs already discussed in the previous sections,

citizen empowerment has come into focus, but

technology developers are still caught up in the

smart city classic paradigm. We therefore have a

gap between smart city deployments, and citizen

empowerment. From our experiences we have

learned that user empowerment emerges through

transparency, flexibility, and adaptation to

individuals’ needs. This means, that a user should

be able to understand what is going on, the

technology should be capable of taking into

account the heterogeneity of the environment, and

it should be possible for the user to adjust a

specific technological deployment. The latter is not

just about enabling users to change color on a

screen or subscribe to a newsletter - it is way more

profound. Users should be able to make the

technology support their explicit needs here and

now. This means that a user should be able to turn

on or off the street lighting, right now at this


this particular case, users can participate by sharing

and being notified of events happening in the city

(Pulse of the City), as an example sharing informati-

on about a cultural event in a particular location in

the city, a traffic jam or even a problem that needs

to be fixed. Also connected to this event-based

platform are the Municipality of Santander and a

local newspaper, which in the first case are

connected to the platform in order to collect

information about complaints/problems happening

in the city and react upon it by sending someone to

investigate and fix it. For the second case, the

newspaper uses the platform both to publish the

local news, as well as to retrieve the information of

relevant events published by others as sources of

information that can lead to new news articles. This

application, called ”Pace of the City” (SmartSantan-

der 2015a), is available for both Android and iOS

platforms and has been used actively by many

citizens of Santander. What is most interesting and

unique about this approach is the involvement of

the citizens by giving them a voice to participate in

the city’s maintenance and development. They are

essential in the smart city context and have the

empowerment and the responsibility of participa-

ting in a democratic way in their cities.

vote a lamppostThe concept Vote a lamppost (vlp) evolves around

citizen empowerment, and our preliminary

prototype is evolving around a voting system. A

user can connect to the Vlp system, and provide a

suggestion for changing the state of a lamppost. All

other users can then vote the suggestion up or

down. If more than 50% votes up, the lamp will

change state. By empowering citizens through

providing a democratic ability to control street

lighting, the aim of vlp is to foster a different way

of thinking about and acting in the city. It

transforms the existing street lighting infrastruc-

ture from something that just exists in the

back ground to an active platform that shifts the

current municipality-citizen relationship, and in

this manner moves away from the service provider-

specific location. He should be able to get the route

home following the path of least pollution (not

predicted pollution, the actual real-time pollution

measurements). And it should be possible for him

to seamlessly tap into the abundance of infrastruc-

tures and services right at hand (ex. using car

sharing or couch-surfing).

We need to go to the next level of smart city

technologies and now focus on citizens as being a

rich reflective resource, and we need to co-create

future solutions with them, not for them. It is the

citizens who constitute the cities, and they should

also have the key to unlock and manage it. At the

Alexandra Institute, we are focusing on how to

empower users through technology, and we are

actively engaged in creating applications that

foster real power to the people. In the following

sections, we will elaborate further on two examples

of projects and applications that demonstrate the

work that has been carried out in the scope of our

smart city activities.

smartsantanderAs mentioned above, SmartSantander is an FP7 EU

project (SmartSantander 2015b) proposing a

city-scale experimental research facility that also

supports applications and services in a smart city

context. The project envisioned the deployment of

20.000 sensors among different cities such as

Belgrade (Serbia), Guildford (UK), Lübeck (Germany)

and Santander in Spain. Different services and

applications have been developed during the

project. The different covered use cases (Santander

2012) include for instance smart parking, environ-

mental monitoring and augmented reality

scenarios.

One of its most relevant services that has had a

large impact has been the ”Participatory Sensing

Service” (Gutiérrez et al. 2013). In this service,

mobile phones of citizens are considered as

resources that can both provide sensory data, such

as accelerometer, noise, temperature and location,

but also the users can feed the system with their

input/knowledge, all in a fully anonymised way. In


in the asphalt of a bike lane, the municipality need

to act reasonably fast and fix the problem. This trust

and credibility relationship needs to be built (this is

especially the case in southern Europe) and is

paramount for the future developments of smart

cities.

As an addition to the citizen-municipality

relationship, smart city technologies can be seen as

support for the citizen engagement. By adapting to

individual needs, and by providing direct control

to the citizens, ownership and responsibility will

emerge. A consequence is a shift in the municipa-

lity-citizen relationship, which results in levera-

ging the, yet unexploited, resource of reflective

and acting citizens.

References

• Brynskov, Martin, Juan Carlos Carvajal Bermúdez, Manu Fernández, Henrik Korsgaard, Ingrid Mulder, Katarzyna Piskorek, Lea Rekow, and Martijn de Waal. 2014. Urban Interaction Design - Towards City Making. Urban IxD Booksprint.

• Ckan. 2015. “Ckan - The Open Source Data Portal Soft-ware.” Accessed November 25. http://ckan.org/.

• Expo, Smart City. 2015. “Smart City Expo World Congress | Home.” Accessed November 24. http://www.smartcity-expo.com/en/.

• Foucault, Michel. 1977. Discipline and Punish: The Birth of the Prison. Vintage Books.

• Gutiérrez, Verónica, JoseA. Galache, Luis Sánchez, Luis Muñoz, JoseM. Hernández-Muñoz, Joao Fernandes, and Mirko Presser. 2013. “SmartSantander: Internet of Things Research and Innovation through Citizen Par-ticipation.” In The Future Internet SE - 15, edited by Alex Galis and Anastasius Gavras, 7858:173–86. Lecture No-tes in Computer Science. Springer Berlin Heidelberg. doi:10.1007/978-3-642-38082-2_15.

• Kranenburg, Rob Van. 2008. The Internet Og Things. Amsterdam: Network Notebooks.

• OrganiCity. 2015. “OrganiCity.” Accessed November 24. http://organicity.eu/.

• Safecast. 2015. “Safecast.” Accessed November 25. http://blog.safecast.org/.

• Santander, Smart. 2012. “D4.2 SmartSantander – WP4 Working Document D4 . 2 Description of Implemented IoT Services.”

• SmartSantander. 2015a. “Participatory Sensing Applica-tion.” Accessed November 24. http://www.smartsantan-der.eu/index.php/blog/item/181-participatory-sensing -application.

• 2015b. “SmartSantander.” Accessed November 24. http://smartsantander.eu/.

consumer relation to making it more equal

(Brynskov et al. 2014), which again fosters hyper-

local social engagements. When people get power

they also get responsibilities, which forces them to

reflect and act intelligently (Foucault 1977). Since

vlp is democratic there has to be an agreement on

the state of a unique lamppost. One neighbor

might want the light turned off (he is going to bed)

while another wants it turned on because her

daughter is coming home late. Decision-making is

not only a question about optimization (reducing

power consumption or making the streets safer),

but also about human convenience.

Vote a lamppost is yet another intelligent street

lighting application. The difference is that we have

chosen to move the intelligence away from the

lamppost, and instead put it into the hands of the

citizens. We argue that street lighting should

respond to immediate needs of citizens, and not

just an intelligently thought out algorithm. Now

that street lighting is becoming truly intelligent we

can hand over the power to citizens – they can

decide when they want their hyper local lamppost

to be on, off or just dimmed.

towards tecHnoLoGicaL democracy in smart citiesThe two above-mentioned applications are examples

of developments that focus on the citizens as being

reflective individuals who act and live in the city.

What has become clear to us during our work is that

there might be a gab between how decision-makers

and citizens perceive the city. From the municipal

perspective, it seems that focus is on efficiency

– how to reduce costs. From the citizens’ perspecti-

ve, it seems to be more about convenience and

liveability. Through different smart city projects, we

have seen that citizens actually care about their city,

and they like participating in the making of the city

if it creates an actual impact. By giving citizens a

voice in the city, they become more engaged. This

also puts quite a lot of responsibility back on the

municipa lity, since citizens need to feel that they

are making a difference. If a citizen reports a crack


open dataOpen Knowledge Foundation (www.okfn.org) er en non-profit organisation

for personer, der arbejder med eller er interesserede i Open Data. De

definerer begrebet åben således:

’...the data must be available as a whole and at no more than a reasonable

vores digitale verden består af nuller og et-taller og i takt med den øgede digitalisering, bliver mængden af data større og større. Derfor er et af de nyeste buzzwords Open Data, som åbner for et helt nyt forretningsområde, hvor kernen er tilgængelig data. Men hvad er Open Data, hvad kan det bruges til og af hvem? Det offentlige har enorme mængde data, og det kan være en god ide at dele dem. i juni 2015 blev Open Data Dk samarbejdet lanceret. Det har til formål at sætte Open Data på den nationale dagsorden, under-støtte datadreven vækst og fremme transparen-sen i det danske samfund. Denne artikel vil beskrive Open Data området og tydeliggøre fordelene ved arbejdet gennem ek-sempler. Derudover beskriver vi, hvordan der bliver arbejdet med Open Data i Danmark. Keywords: Open data, geografisk information, smart city, digital forvaltning

Anna Katrine Mathiassen Aarhus [email protected]

Michelle Bach Lindstrøm Aarhus [email protected]

open data dk Skaber vækSt og tranSparenS


reproduction cost, preferably by downloading over the

internet. The data must also be available in a convenient

and modifiable form.’

De uddyber deres føromtalte definition med, at

dataejere ikke må lave restriktioner på, i hvilke

sammenhænge dataen må bruges, eksempelvis at

det ikke må bruge i reklamesammenhæng eller

kun må bruges til undervisning.

Danmark er et af de lande i verden, hvor der er

mest gennemsigtighed i den offentlige sektor i

forhold til informationer - for eksempelvis fra

byrådsmøder, møder i Folketinget, national statistik

og offentliggørelse af økonomi - og dette har i

mange år været en tradition i den offentlige sektor.

Alle interesserede har mulighed for at overvære

møder hos beslutningstagerne eller hente oplysnin-

ger om indholdet af deres møder. Dette er tidligere

foregået manuelt på arkiver, men i takt med

digitaliseringen er al information blevet tilgænge-

ligt i andre formater. Det er den tradition, Open

Data DK er med til at bygge ovenpå ved at skabe over-

blik over al tilgængelig åben data på én platform.

Eksempler på Open Data kan være kommunale

datasæt om trafikinformation, oplysninger om

begivenheder i byerne, oversigter over kommunale

bygninger og tilbud, tilbud i naturen, oplysninger

om sundhedsverdenen, kommunernes arealer, virk-

somheder i kommunen mv.

Open Data kan anvendes til at få indsigt i,

kopiere/ distribuere, mixe/ genbruge data i andre

sammenhænge eller helt modificere dem til at

eksempelvis indgå i et produkt.

open data som en del af big data bølgenOpen Data er ikke nødvendigvis det samme som

Big Data, men mange ideer/tanker samt erfaringer

overlapper, og således influerer begge begreber

hinanden. I denne artikel defineres Big Data som et

begreb, der udspringer af den eksplosive vækst i

data, der følger af digitaliseringen af data. Big Data

beskrives som oftest som forholdsvis store datasæt

eller med udgangspunkt i de tre V’er: Volume

(mængde), Velocity (hastighed) og Variety (mangfol-

dighed).

Når virksomheder kombinerer egne Big Data

med Open Data, understøtter Open Data Big Datas

indflydelse i samfundsøkonomien. Det sker, fordi

Open Data skaber gennemsigtighed, udstiller

variationsmuligheder kombinationsmuligheder og

gør det muligt for virksomheder og andre aktører

at eksperimentere med data forholdsvis omkost-

ningsfrit.

open data som en del af delekulturenInternationale succeser som boligleje- og boligbytte-

ordninger er eksempler på fremvæksten af en ny


delekultur, der ændrer den måde, vi som samfund

forbruger, arbejder, rejser og lever på. Specielt i

byerne vækster delekulturen, og deletendensen ses

som værende den nyeste trend i byerne, hvor det at

udnytte ejendele og information på den bedst

mulige og mest effektive måde er blevet gjort muligt

på baggrund af den øgede digitalisering, den

teknologiske udvikling samt fokus på nye forret-

ningsmodeller.

Et eksempel herpå er organisationen Creative

Commons, der tilbyder en række simple værktøjer,

der giver kunstnere, forskere og andre mulighed for

– helt eller delvis – at dele deres værk med andre.

Creative Commons har lavet en licens, hvor afsende-

ren kan skræddersy en ophavsret efter behov. Dermed

deler afsenderen sit værk/arbejde med brugerene.

Dette stemmer overens med definitionen af

Open Data, da tankegangen om deling er den

samme (jf. definitionen fra www.okfn.org.).

Modtageren skal således have fri mulighed for at

arbejde med data, og på den måde kan Open Data

siges at arbejde for delekulturen.

Open Data som genstandsfelt placerer sig

således i mellemrummet mellem Big Data og

delekulturen, og erfaringer med disse to felter kan

anvendes i arbejdet med Open Data.

potentiaLe ved open dataDer er mange forskellige måder, hvorpå data kan

bruges, samt forskelligartede former for vækst det

afstedkommer. Nedenstående er en række

eksempler på dette.

Open Data afføder social og økonomisk vækstOpen Data har indvirkning på den økonomiske

vækst, hvor eksempelvis transportsektoren kan

nyde godt af at tilbyde nye services om transport-

planlægning, parkeringspladser, vejfinding m.m.

– services som også har en positiv social betydning

i samfundet, idet det giver bedre fremkommelig-

hed for borgere og bilister.

En ny type firmaer, der tilbyder databehandling

og konsulentarbejde ser også dagens lys, og firmaer

af alle størrelser begynder at kombinere åbne data

med egne data til at forbedre deres produkter og

udviklingsarbejde.

Dette ses fx hos firmaet Geoboxers (http://www.

geoboxers.com/), som bruger en frittilgængelig 3D

model af Aarhus i computerspillet MineCraft, og

spillerne kan således gå rundt i et virtuelt Aarhus.

GeoBoxers har hentet oplysningerne til den

virtuelle by på Aarhus Kommunes Open Data

platform www.odaa.dk.


Flere rapporter viser, at der er enorme poten-

tialer i Open Data:

• Europakommissionen beregnede i 2012 et

årligt økonomisk potentiale på 140 mia. € i de

27 EU-lande i form af vækst for erhvervslivet

og effektivisering 1

• I Danmark forventes det danske grundda-

ta-initiativ at have en samfundsmæssig

gevinst på 800 mio. kr. om året fra 2020, når

initiativet er fuldt indfaset 2

• En finsk undersøgelse viser, at ITvirksom

heder i lande med en vedtaget Open Data-

politik har en omsætning, der er 13% større

end i lande, der ikke har 3

Erfaringer og analyser fra udlandet viser

således, at jo mere Open Data er forankret, desto

mere værdi kan der skabes.

Data er interessante for erhvervslivet, fordi de

kan bruges som råstof i udviklingen af eksempelvis

applikationer, tjenester og ydelser. Data er således

en ressource, der kan anvendes både til at skabe

nye services eller en mere effektiv forretning med

vækst og arbejdspladser til følge.

Qua de sidste års digitalisering af den offentlige

sektor samt samfundets brug af sociale og digitale

medier er den samlede mængde af data steget. For

erhvervslivet kan man se data som et råstof, vi har,

og som vi skal bruge til at udvikle nye services

baseret på bl.a. vores digitale vaner.

Open Data muliggør nye offentlige servicesOpen Data kan også skabe nye og mere effektive

services inden for det offentlige. Det offentlige kan

eksempelvis udnytte åbne data til effektivisering af

interne processer myndighederne imellem, lave

oversigt over kommunale legepladser eller

trafikken i byen 4... Sidstnævnte er udarbejdet af

Aarhus Stiftstidende baseret på data fra www.odaa.

dk, og viser trafikken i Aarhus.

Et andet eksempel er EU-projektet RADICAL5,

som sætter fokus på affald i hele Aarhus

Kommune. Dette projekt er også baseret på

affaldsdata, som er tilgængelige på Open Data

Aarhus 6. Her kan alle finde oplysninger om affald

efter postnummer, ligesom der er forskellige

oplysninger om renovation i byen med en

forhåbning om, at bedre viden om miljø på sigt

skaber bedre adfærd.

På Miljøportalen.dk finder vi endnu et eksempel

på, at Open Data forbedrer resultatet af et arbejde.

Digitalisering og udstilling af data om spildevand og

vandprøver har betydet, at udarbejdede vandplaner

er blevet bedre, hvilket igen betyder et bedre miljø,

idet medarbejderne har et bedre udgangspunkt. Læs

mere om projektet her 7.

Ovenstående viser, at Open Data skaber nye

tiltag, innovation, nytænkning og udvikling rundt

om i byerne, hvor borgerne har mulighed for at

tage initiativ til udvikling af services baseret på

deres behov. Derved påvirker Open Data borger-

inddragelse i en positiv retning.

open data styrker demokratietOpen Data giver borgerne mulighed for at følge

med i, hvad det offentlige bruger dets ressourcer

på og skaber mere transparens. Ligeledes kan de få

informationer om, hvordan Folketinget og

regeringen er struktureret, læse lovforslag eller

følge folketingsmedlemmernes stemmehistorik.

Virksomheden Buhl & Rasmussen har udviklet en

hjemmeside baseret på åbne data fra Folketingets

egen hjemmeside (www.hvemstemmerhvad.dk ),

hvor man kan se afstemninger og stemmefordeling

inddelt på parti, alder, køn eller storkreds. Niels

Erik Kaaber Rasmussen fra Buhl & Rasmussen

udtaler om projektet:

’Arbejdet med folketingets data er et forsøg på at skabe

øget politisk transparens og lette adgangen til vigtige

politiske data’.

1 (european Commission, 2012)2 (regeringen, 2012)3 (http://www.etla.fi/wpcontent/uploads/2012/09/dp1260.pdf)4 (http://www.opendata.dk/viden-om/use-cases/saadan-ser-trafikken-

ud-lige-nu)

5 http://genbrug.smartaarhus.dk/recycling.html6 http://www.odaa.dk/dataset/affald-fra-genbrugsstationer7 (http://www.opendata.dk/blog/aabne-data-bekaemper-miljoesvineri)


IKT, i Innovation og Forskning fra Region Midtjyl-

land og medlem af Open Data DK siger følgende:

’Det offentlige sidder på en lang række data, som

potentielt kan medvirke til at øge væksten hos virksom-

heder, skabe mere transparens og bedre services for

borgerne samt bedre løsninger til/af myndighedsopgaver’.

Han placerer dermed Open Data som en ny

måde at tænke data, hinanden og byens ressourcer

på. Open Data DK tror på, at åbenhed og gennem-

sigtighed i den offentlige sektor skaber mulighe-

der, så borgere og virksomheder kan blive mere

aktive medspillere i lokaldemokratiet.

De førnævnte kommuner er alle i gang med

Open Data arbejdet, og samtidig arbejdes der på

statsligt niveau med bl.a. at fritstille grunddata jf.

kommunernes fælles digitaliseringsstrategi, som

bliver udgivet i 2016.

Open Data DK er baseret på Open Source

software-platformen CKAN, som er et datamanage-

mentsystem, der muliggør deling og søgning,

ligesom platformen kan kommunikere med andre

sider, som bruger CKAN. Således kan kommuner og

andre organisationer, der har egne CKAN-installati-

oner, integreres på én fælles platform og dermed

skabe et overblik for brugerne. Systemet er

internationalt anerkendt og anvendes af et flertal

af andre internationale Open Data initiativer som

eksempelvis data.gov.uk, Englands nationale Open

Data indsats.

Open Data DK er en ny form for netværk for

videndeling og samarbejde på tværs af kommunale

grænser og sektorer. Open Data er således et helt

nyt mindset både i forhold til brug af data og

tværkommunalt arbejde. Bo Fristed fortæller:

’Samarbejdet er begyndt som uformelle møder mellem en

række Open Data-entusiaster og er et billede på, at der kan

opnås væsentlige resultater ved at arbejde nedefra og op’.

Samarbejdet er således udsprunget af en fælles

interesse for Open Data, hvorfor deltagerne

arbejder mod et fælles mål. Det er ikke kun til gavn

for de respektive byer, men ligeledes for hele

landet. Arbejdet med at gøre data frit tilgængelige

Arbejdet med data kan bruges aktivt i forhold til

folketingsvalg, og efter valget om patentdomstolen

i maj 2014 afholdt interesseorganisationen Open

Knowledge Denmark en workshop med stemmere-

sultaterne. Til deres overraskelse fandt de frem til,

at der på Taarbæk Skole var byttet rundt på ja og

nej svarene, da den endelige indberetning blev

sendt af sted. Fejlen blev rettet, men det ville måske

ikke være blevet opdaget, hvis ikke workshoppen

havde fundet sted 3.

Overstående eksempler viser, at arbejdet med

Open Data eksempelvis kan bruges til at give nem

adgang til det offentlige arbejde samt kontrollere

selvsamme, hvilket i sidste ende styrker demokratier.

open data dk – en by er ikke et markedI foråret 2015 startede portalen www.opendata.dk

som er et tværkommunalt samarbejde mellem

Aarhus, København, Vejle, Aalborg og Odense

Kommune samt Region Midtjylland med et formål

om at sætte Open Data på den nationale dagsorden

samt at skabe en landsdækkende portal, hvor data

fra offentlige instanser og private virksomheder

samles. Bo Fristed, Formand for Open Data DK og

IT-chef i Aarhus Kommune udtaler følgende om

samarbejdet:

’Open Data DK er et stort og vigtigt skridt for arbejdet

med Open Data i Danmark og er med til at sikre en

sammenhængskraft kommunerne imellem. Det er

skelsættende, at Danmark nu får en samlet portal for Open

Data - og helt uden sidestykke internationalt’.

Tanken bag Open Data DK er at skabe overblik

over tilgængelig data i landet på én national

platform, hvor interesserede borgere eller virksom-

heder kan hente data til fri afbenyttelse, som kan

danne rammen om nye applikationer, tjenester,

services eller være afsæt i analyser mv. På denne

måde bliver der dannet nye, uforpligtende

partnerskaber med iværksættere/ virksomheder/

borgere og landets kommuner.

Jesper Algren, Projektleder for Digitalisering og

3 http://www.version2.dk/artikel/aabne-data-afsloerer-valgfejl-ja-og-nej-stemmer-blev-byttet-om-58873


er i høj grad både på den internationale og den

nationale dagsorden. Open Data DK er således med

i Open & Agile Smart Cities (OASC) et netværk af

nationale by-samarbejder. Formand Martin

Brynskov siger følgende:

’Visionen er at skabe et globalt Smart City marked

bygget på behov, styrke konkurrenceevnen og skabe

løsninger med respekt for lokale faktorer og jobskabelse’.

Hermed er målet et internationalt netværk af

Smart City byer, som alle arbejder med individuelle

samt skalerbare løsninger, der passer til deres egen

by. OASC fordrer således videndeling og sparring

byerne imellem.

Alt arbejde i Open Data DK er drevet af initiati-

ver både i kommunerne og blandt de virksomhe-

der, som er med. Således bæres arbejdet frem af

lysten til arbejde med Open Data, dog er der

enkelte barrierer som kan hæmme virksomheder-

nes og kommunernes motivation til at arbejde med

data. De beskrives i det følgende.

Manglende tilgængelighed og overblikDatadreven forretningsudvikling er tæt forbundet

med adgang til data. Erhvervsstyrelsen beskriver, at

der er mulighed for yderligere vækst i det danske

erhvervsliv, såfremt tilgængeligheden af åbne

offentlige data øges. Offentlige data kan supplere

virksomhedernes egne data - eksempelvis kan data

om personer og geografi bruges til at segmentere

og analysere virksomhedernes kunder. Ved at have

én portal, der giver overblik over Open Data i

Danmark, understøtter Open Data DK data som

vækstfaktor i det danske erhvervsliv.

manglende viden om dataDanmark er et digitalt foregangsland, og der findes

en række data- frontløbervirksomheder, men på

trods af det, er der stadig en stor usikkerhed om de

potentielle gevinster ved datadreven forretningsud-

vikling. Flere virksomheder har et behov for at

databegrebet afmystificeres. Open Data DK

afholder løbende workshops og arrangementer,

ligesom der deles alle de gode og relevante use

cases, der gør brug af Open Data. Derudover

afholder vi gerne, i samarbejde med andre

partnere, såkaldte hackathons, hvor data bringes i

spil. Alt sammen for at udbrede viden om data og

brugen heraf.

manglende information om sikkerhed/privacyFor at kunne udvikle services, applikationer og

kunne skabe forretning baseret på Open Data

kræves der fra virksomhedernes side en ensartet

rådgivning om brug af data samt en gennemsigtig

og klar licens. Open Data DK tilstræber qua

samarbejdet med OASC at ensarte brugen af

licenser, og som udgangspunkt opfordres de

deltagende dataejere til at benytte dokumentet

”Vilkår for brug af danske offentlige data” lavet af

Digitaliseringsstyrelsen. Vilkårene er i overensstem-

melse med PSI-loven (Lov om videreanvendelse af

den offentlige sektor informationer). Open Data DK

vil vejlede virksomheder og organisationer om den

bedste brug af data.

Når der arbejdes med Open Data, er det vigtigt

at have styr på de nødvendige love og regler, der

gør sig gældende ved offentliggørelsen af data.

Flere kommuner udtrykker en usikkerhed, når de

skal fritstille data, fordi de nærer frygt for at frigive

personfølsom information. Data på Open Data DK


frigives inden for Persondatalovens rammer,

ligesom vi løbende undersøger nye muligheder for

at sikre og anonymisere data - eksempelvis har vi

udviklet en CPR-scanner der sikrer, at CPR-numre

ikke kommer ud. Vi har yderligere udarbejdet en

rapport, hvor dataejere kan læse om de lovmæssige

aspekter, der er relevante at have for øje; juridisk

dokumentation om persondataloven, licenser,

personhenførbare oplysninger og ophavsret.

opsummerinGDer er flere potentielle gevinster for kommuner og

virksomheder i at arbejde med Open Data.

• Overblik over egne data på tværs af organisati-

onen: Ved at få indblik i, hvilke ressourcer

kommunen bruger hvor, kan de effektivisere

og optimere brugen af disse.

• Optimering ved at kombinere egne og

eksterne data: Kommunernes egne data om fx

trafik kan kombineres med trafikforskning,

hvilket kan bruges i byens fremtidige

trafikplaner og -udvikling.

• Datadreven innovation: På baggrund af

kommunernes egne data kan borgere udvikle

services baseret på borgernes egne behov,

hvilket kan resultere i innovative løsninger,

som dataejerne ikke selv ville have udviklet.

• Øget vækst og forretningspotentiale blandt

virksomheder: Før beskrevne eksempler om

GeoBoxers og Buhl & Rasmussens brug af

Open Data viser, at private kan skabe ydelser

og produktioner af tilgængelige data, som i

sidste ende kan afføde vækst.

Open Data som borgere og virksomheder i hele

Danmark nemt og gratis kan tilgå, vil altså kunne

bruges som råstof i udviklingen af applikationer,

tjenester og services eller være afsæt for analyser,

tendensvurderinger, forskning osv. Samtidigt vil

Open Data kunne understøtte gennemsigtigheden i

den offentlige forvaltning, så borgere og virksom-

heder kan blive endnu mere aktive medspillere i

vores lokaldemokrati. Sammenholdt med rappor-

terne fra EU og Erhvervsstyrelsen er det således

tydeligt, at Open Data er en del af fremtiden inden

for nytænkning af data og jobskabelse, og arbejdet

er godt på vej.

I skrivende stund er der over 340 datasæt på

Open Data DK-portalen fra hele Danmark omhand-

lende alt fra natur til trafik, begivenheder m.m.,

som alle er klar til at blive anvendt til applikatio-

ner og services. I øjeblikket arbejder Open Data DK

på at frigive så mange sammenlignelige datasæt fra

medlemmerne af Open Data DK som muligt. Det

gøres ved at inddrage virksomheder, uddannelses-

institutioner m.fl., så der i fællesskab kan findes de

data, som giver bedst mening at stille til rådighed

for offentligheden.

Kunne du tænke dig at høre mere om Open Data

DK eller være med?

Så følg med på www.opendata.dk

og på twitter @OpenDataDK

Referencer

• European Commission (2012), Digital Agenda• Regeringen/KL (2012), Gode Grunddata til alle• www.hvemstemmerhvad.dk• www.version2.dk/artikel/aabne-data-afsloerer-valgfejl-

ja-og-nej-stemmer-blev-byttet-om-58873• www.erhvervsstyrelsen.dk/sites/default/files/big-da-

ta-som-vaekstfaktor.pdf• www.opendatanow.com/2013/11/new-big-data-vs-open-

data-mapping-it-out/#.VhznNyuVAaI• www.mckinsey.com/insights/business_technology/open_

data_unlocking_innovation_and_performance_with_liquid_information

• http://www.opendata.dk/viden-om/use-cases/saadan-ser-trafikken-ud-lige-nu

• http://genbrug.smartaarhus.dk/recycling.html• http://www.opendata.dk/blog/aabne-data-bekaem-

per-miljoesvineri• www.okfn.org• www.geoboxers.dk Yderligere• www.opendata.dk• www.odaa.dk


this paper presents a case study of a smart City initiative in Lyngby-taarbæk municipality, which has successfully applied the triple helix model to create an informal collaboration between academia, govern-ment and private industry. the study recounts how a group of university students, participating in a big data hackathon, managed to create a smart City solution prototype based on open data in only 48 hours. the solution offers to make the municipality more cost efficient and improve citizen services, while simultaneously contributing to reduced CO2 emis-sions, thus addressing a difficult societal challenge. A special attention is paid to how the smart City vision, based on the triple helix model, is used to align inte-rests and enable an informal collaboration between heterogeneous stake holders. this collaboration represents an underlying value network, where value generation is moving beyond the simple profit-driven mechanisms of the markets. the paper identifies three main roles in the triple helix based value net-work: the influencer, the Facilitator and the imple-menter.

Keywords: Smart city, big data hackathon, innovation contest, energy efficiency, spatial data

elementS of a SucceSSful big data hackathon in a Smart city context

Thorhildur JetzekDepartment of it Management, Copenhagen Business [email protected]

reviewed


introductionFor the past two decades, information and

communication technologies (ICTs) have been

exerting a growing influence on the nature,

structure and enactment of urban infrastructure,

management, economic activity and everyday life

(Kitchin, 2014). This has led to a growing interest in

the concept of Smart City. The Smart City concept

can be viewed as an overarching concept that

describes a city’s ability to use data and technology

for improving the livability and wellbeing of its

citizens1. Concurrently, there has been an increa-

sing focus on societal challenges that are reflected

in our societies’ inability to sufficiently address

complex problems, such as the refugee crisis and

climate change (OECD, 2011). I propose that Smart

City initiatives based on informal collaboration

between stakeholders in different sectors offer a

new model for solving these grand challenges. The

key to success is a Smart City project’s ability to

encourage and activate more members of society to

collectively address societal challenges. History

tells us that silo structures, which oftentimes

characterize governmental organization, are poorly

suited to tackling complex problems across sectors.

Moreover, the market by itself lacks the incentive

structure and appropriate business models needed

to solve societal challenges. And stakeholders with

interest and drive, such as civil society or universi-

ties, might lack the capital, skills and resources to

take promising ideas to scale (Murray et al., 2010).

In order to successfully address societal

challenges, it is necessary for all of these stakehol-

ders to leverage their individual strengths and

capabilities. However, in order to incentivize a

diverse group of people to collaborate on finding

and implementing solutions, it must be acknowled-

ged that their motivations and goals may vary

widely. In this paper, I study a case where a loosely

organized collaboration between different

stakeholders and sectors has succeeded in enabling

individual participants to create and capture value,

while simultaneously addressing a societal

challenge, namely climate change. The case data is

based on 5 interviews with participants from

different sectors, including follow-up; as well as

analysis of online content and documents provided

by the interviewees. A list over organizations

interviewed is provided in Appendix A. The case

context is that of a Smart City, however the case

includes many other new and interesting concepts

such as big data, innovation contests and open

government data. The case offers insight into how

different motivations can be aligned through the

triple helix model, i.e. how to motivate and enable

heterogeneous stakeholders to collectively

contribute to a common goal. Moreover, I discuss

how value can be created in a value network,

moving beyond the simple profit-driven mechanis-

ms of the markets towards a complex network of

aligned interests.

urbanization and tHe smart cityUrbanization, the demographic transition from rural

to urban, is associated with shifts from an agricultu-

re-based economy to mass industry and more

recently, technology and service. If these trends

continue as projected, the percentage of people living

in urban areas will increase to 70% before 20502. The

trajectory of the rapid urban population growth is

not just an interesting fact but also requires a

demanding imperative for sustain able development

and better livability (Nam and Pardo, 2011). As an

example, although cities currently occupy less than

two percent of the landmass of the earth, urban

residents consume over 75% of the world’s natural

resources and are primarily responsible for gre-

en-house gas emissions (Marceau, 2008). Urbanization

is also changing how we need to approach problems.

Multiple diverse stakeholders are now sharing a

physical space, which results in high levels of

interdependence, competing values, and social and

political complexity (Dawes et al., 2009; Weber and

Khademian, 2008).

1 http://tti.tamu.edu/group/transit-mobility/files/2013/05/3-Definitions-of-livability-handout.pdf2 http://www.who.int/gho/urban_health/situation_trends/urban_population_growth_text/en/


Making a city smart is a novel way to approach

such challenges (Nam and Pardo, 2011). But what is

a Smart City? Bolici and Mora (2015) define Smart

Cities as urban areas in which information and

communication technologies (ICTs) are used to

solve their specific problems and support their

sustainable development in social, economic and/

or environmental terms. The Lyngby-Taarbæk City

of Knowledge initiative defines Smart Cities as

digital and inclusive cities that seek to optimize

how the city functions by creating synergies

between the physical and the social in the digital

space. According to their definition, a Smart City

should support relationships between authorities,

businesses, organizations and citizens, mainly

through sharing of data and information across

organizational boundaries. Wikipedia3 offers this

definition: A Smart City uses digital technologies

or information and communication technologies

(ICT) to enhance quality and performance of urban

services, to reduce costs and resource consumption,

and to engage more effectively and actively with its

citizens. It is safe to say that a Smart City is an

emerging phenomenon and as such has no precise

definition. However, what all of these definitions

have in common is a focus on the digital space and

how new technologies and new means of collabora-

tion can facilitate and accelerate how we address

many of the societal challenges that result from

increased urbanization.

tHe city oF knowLedGe: LynGby taarbæk‘s smart city visionThere are a number of Smart City initiatives in

Denmark. Perhaps the most prominent one is

Copenhagen Smart City Initiative which has won

awards like the World Smart Cities Award in 2014.

Additionally, various smaller municipalities have

started their own Smart City initiatives, although

some of them might not explicitly use the Smart

City concept. One of them is Lyngby-Taarbæk

municipality. Lyngby-Taarbæk is a host to many

technology and information driven companies as

well as one of the most respected technical

universities in Europe, The Technical University of

Denmark, DTU 4. The municipality has identified

Lyngby-Taarbæk as a City of Knowledge & Urban

Development. Their City of Knowledge vision

includes attracting and retaining knowledge-based

businesses, developing Lyngby-Taarbæk into a

university town, creating urban life, forming

networks, furthering social innovation and

internationalization, inspiring entrepreneurship,

and broadening municipal services to the busines-

ses and citizens in Lyngby-Taarbæk 5.

The City of Knowledge initiative is designed as a

triple helix model (Etzkowitz, 1993; Etzkowitz and

Leydesdorff, 1995; Ranga and Etzkowitz, 2013). The

Triple Helix thesis is that the potential for

innovation and economic development in a

Knowledge Society lies in the hybridisation of

elements from academia, industry and government

to accelerate production, transfer and application

of knowledge. The City of Knowledge & Urban

Development includes stakeholders from all three

sectors and is governed by an independent

organization that is jointly funded by all of the

sectors. The participating stakeholders all agree on

the common vision for the City of Knowledge &

Urban Development, and presumably expect to

benefit from this collaboration. However, their

motivations for collaborating vary considerably.

The key to success in the triple helix model is to

create a win-win-win situation where each of the

partners can focus on their own benefits while

their individual contributions will add value to the

larger ecosystem in which they operate. Figure 1

shows an example of a triple helix model.

Academia mainly contributes through knowledge

creation which is disseminated through teaching

and research. Government contributes to a healthy

environment for innovative collaboration, creating

3 https://en.wikipedia.org/wiki/smart_city4 DtU is listed number 43 in thomson reuter’s list of the World’s most innovative Universities, and counts number 7 of all the european Universities on the list. see: http://www.reuters.com/article/2015/09/15/idUsL1n11k16Q20150915

5 http://www.vidensby.dk/english.aspx


policy and supplying necessary services, e.g.

through funding organizations or open data

platforms. Industry contributes through wealth

generation, and provides the capital and work

processes, necessary for scaling up promising ideas

and introducing them to markets.

the big data HackathonThe independent City of Knowledge & Urban

Development organization governs and facilitates

different networks where members develop ideas

and common projects. One of these networks has a

focus on climate and green technology. Network

members showed an interest in gaining improved

access to Lyngby-Taarbæk’s data for supporting the

development of data-driven smart city solutions,

such as Intelligent Energy Systems. The idea to

support an innovation contest, or big data

hackathon, was originally raised by DTU Compute

department but the City of Knowledge agreed to

partner in the organization of the event, together

with representatives from Lyngby-Taarbæk

municipality and IBM, which provided IT tools to

the participants. Lyngby-Taarbæk municipality

agreed to give the hackathon participants access to

some of their data, as well as providing a descrip-

tion of some of the problems or challenges the

municipality was faced with, in a hope for a

potential (partial) solution. The hackathon was

hosted by DTU Compute in the new DTU Skylab

building on the18th and 19th of November 2014.

Simultaneously, DTU hosted a big data conference

where the prizes were to be awarded. The first

three winning solutions were to get prizes of a

total of DKK 55.000, which were sponsored by

Danske Bank, a private company in the munici-

pality. Moreover, the EU climate innovation

initiative, Climate-KIC, contributed a special prize

of DKK 10.000 for the idea providing the most

climate friendly solution.

Invitations were extended to university students

in various Danish universities, mainly through

Facebook sites and student organizations. In short,

the hackathon was a success with 65 participants

and provided many interesting solutions. Intere-

stingly, an emerging literature on innovation

contests in the open data literature has shown that

such contests are in many cases poorly attended

and do not produce sustainable solutions

(Hjalmarsson et al., 2014). However, for this

hackathon, the results were considered as a huge

success by all participating stakeholders. Thus, I

have attempted to extract the potential success

factors of this hackathon from the interview data:

• There was an introductory meeting where

students could show up and form teams. A

positive result of this event was that the

meeting gave the students a chance to meet

others with complementary qualifications

and the resulting teams offered more diversity

of knowledge and skill.

• The municipality not only contributed data

but also formalized some questions or

problems they were facing. An overarching

theme was to create a solution which would

make the lives of the citizens in Lyngby-Taar-

bæk easier and contribute to a more sustai-

nable environment (special prize). This gave

the participating students, who had little or

no prior knowledge of the societal challenges

faced by municipalities, a starting point from

where to develop their solutions.

Figure 1. The Triple helix model. Loosely adapted from Farinho and Ferreira, 2013.


• The technical and business related requests

for the solutions also helped the students

think more broadly in terms of future

applications. The solutions were required to

make use of big data, have a novelty value, be

user-friendly, scalable and have commercial

potential.

• The students were somewhat motivated by the

cash prize but even more motivated by the

fact that prominent members of industry

were a part of the panel of judges. Other

industry stakeholders were supporting the

hackathon with IT solutions and prizes. As

many of the participating students were just

about to finish their studies, they needed

industry contacts.

From Hackathon to a startup companyThe winning team consisted of 6 individuals, 2

with computer science skills, 3 with mathemati-

cal modelling and machine learning skills (all

five from DTU) and one student from CBS with a

business administration background. They had

an opportunity to meet once before the hackat-

hon to brainstorm, but all of the real work

happened in the 48 hours of the hackathon

itself. In the following, the solution itself is

described.

Lyngby-Taarbæk provided a number of data

sources from different departments in the

municipality. The choice of data was more or less

ad hoc, based on which data could easily be

provided. The winning team arrived to the contest

with a semi-structured idea in mind from the

brainstorming meeting. They started by looking at

data on buildings owned by the municipality and

thermographic images of houses in Lyngby-Taar-

bæk. Next, they created a program that could link

the addresses of buildings owned by the municipa-

lity (provided in an excel spreadsheet) to a geo lo-

cation. From this geolocation they could link the

addresses to the map of thermographic images and

see which houses were losing most heat. They

could also use the geolocation to connect these

data to the Danish elevation model, which is

provided as open data by the Geodata Agency

(Geodatastyrelsen). The geolocation thus has a very

important function as a key identifier, making

diverse sets of data interoperable.

Having access to the property data gave them

information about the age of the building and

from that they extrapolated the type of insulation

in different houses. From the thermal images they

could draw conclusions on the relationship

between the insulation and how well the house

retained heat. Based on (openly available) data

from several providers of insulation material they

could calculate the potential cost of insulating an

old house to a modern standard. They looked at

(provided but closed) data on heating sources and

expenses for the properties owned by Lyngby-

Taarbæk, and from combining all these data, they

could deduce how cost-efficient it would be to

insulate different houses and the magnitude of

possible environmental effects (reduced CO2). The

interesting thing about how these students

approached this task is that they did not only

utilize a single dataset provided by the municipali-

ty as has been shown to be the case in many open

data applications, but rather combined the

datasets provided with openly available data from

other sources.

Afterwards, the winning team calculated for

each property whether or not it would be

cost-efficient to implement solar panels. For this

they used the elevation model to find the angle

and orientation of the roof, information about

yield based on angle and orientation (from

various sources), open data on yearly solar

radiation from Danish Meteorological Institution

(DMI) and available information from different

solar panel vendors (prices pr. m2, efficiency pr.

m2, efficiency guarantees etc.). From their

knowledge about roof sizes (provided open data),

energy costs (open data) and composition of

energy sources (provided closed data), they could

also calculate the eco footprint for individual

houses. As the group had access to data on


current energy sources for the municipality´s

own buildings, they could present a solution that

could make the municipality more cost- and

energy efficient. While they did not have such

detailed data for all the privately owned property

in the municipality, they could calculate the

energy efficiency of solar panels based on the roof

size and direction and then calculate estimated

energy savings. Hence, the solution delivers

openly available content, which can help the

citizens of Lyngby-Taarbæk municipality make

informed decisions about how to influence their

own energy costs and eco-footprint. The solution

was simultaneously addressing the need for more

cost efficient municipality, the need for improved

citizen services and the ability to improve energy

efficiency and reduce CO2 emissions.

One of the sponsors of this contest was

Climate-KIC, EU’s main climate innovation

initiative. Climate-KIC has an acceleration

program for entrepreneurs in Denmark and their

representative encouraged the winning team to

apply for funding so they could develop their

ideas further. This is a very important element for

further development of data-driven products. The

open data literature shows that many of the

solutions that have been developed in open data

innovation contests are not sustained, in the sense

that they fail when it comes to scaling up and

developing the solution for the market. A

suggested reason for this is that the public sector

participants that often plan and execute such

contests do not have the capabilities or the funds

required to function as innovation incubators

and/or accelerators. While Lyngby-Taarbæk

municipality has committed some funding to

further the development of the product for use in

the municipality, the winning team‘s dream was

to develop the solution further and make it ready

for general marketing. However, such develop-

ment requires funding and support. The winning

team founded a company, Picodat, and continue

to develop their solution. They are currently

working on a more general solution which can be

marketed for other municipalities in Denmark

and hopefully later in Europe as well.

discussion and FindinGsIn this section, I discuss some of the main findings

that emerged from the case data analysis.

Figure 2. The winning team (Source: www.DTU.dk)


Different roles of stakeholders in the triple helix modelThe idea that the university, industry and govern-

ment are relatively equal interdependent and

interacting institutional spheres is the basis of a

triple helix society (Etzkowitz et al., 2007). However,

these spheres are not only autonomous but

overlapping, not entirely distinct but not completely

merged either (ibid). Thus, I conceptualize three

stakeholder roles, moving away from the instituti-

ons themselves and their roles in society, and

towards the individual stakeholders that represent

these organizations within a triple helix collaborati-

ve initiative. Doing so, I propose, will provide an

extra layer to the triple helix model, representing a

value network of aligned interests, where roles can

be switched or spheres can provide more than one

role, which can explain how they overlap.

AcademiaThe academic partner in this particular triple helix

model was the stakeholder that originally came up

with the idea of a big data hackathon. The Universi-

ty’s organizational role is to do research and to disse-

minate knowledge to society. Accordingly, they like

to test some of their new ideas and methods with

real data and applications. DTU acted as the thought

leader or the driver behind the hackathon, mostly to

raise awareness of how data and data science could

contribute to society. While the other partners (from

the municipality and industry) did not previously

have any structured data-related initiatives, they

were happy to go along with ideas and initiatives

leading in this direction. Thus, in this triple-helix

constellation, the academic stakeholder has the role

of Influencer.

GovernmentLyngby-Taarbæk does not yet have an open data

strategy or a specific open data initiative, so they did

not function as influencers in this particular triple

helix setup. However, the municipality was willing

to experiment and provided access to data in the

hackathon and information on problems in need of

solving. Moreover, the role of Lyngby- Taarbæk’s City

of Knowledge organization as a coordinator between

the different stakeholders was very important for

keeping all the partners aligned. For this case, I

Figure 3. A screenshot of the winning solution. (Source: Picodat)


propose that government acted as the Facilitator as

their contribution was important for creating the

right environment, including aligning the incenti-

ves of different participants.

IndustryThe presence of industry in the panel of judges in the

hackathon itself, as well as industry’s contribution to

winning prizes, clearly created an incentive for the

students to participate. However, industry played a

larger role in the development of the final product.

The panel of judges contributed important knowled-

ge regarding commercial potential and scalability of

the solutions presented. Moreover, Climate-KIC

ultimately provided the funding necessary to take the

idea to the next level, contributing to a sustainable so-

lution6. I propose that industry played the role of

Implementer. Hjalmarsson et al. (2014) argue that only

a limited number of results from contests successfully

reach the end user market. Having implementers on

board increases the chance of promising ideas being

implemented in practice, thus, this role might have

been missing in some earlier open data hackathons

that did not provide sustainable solutions. Moreover,

after a company is founded (in this case Picodat), the

participants in the hack a thon become Implementers

themselves.

value networkThrough this case study I want to contribute to

knowledge on how a constellation of heterogene-

ous partners in a Smart City context can collecti-

vely generate new value from existing data. One of

the findings is that different stakeholders in a

triple-helix constellation not only have different

roles, they are also differently motivated. The

academic stakeholders were interested in

stimulating interest in big data, in order to

further research, develop new methods and

contribute to knowledge. Moreover, they were

interested in getting access to more open govern-

ment data, and perceived the hackathon as a

potential venue to raise awareness to this issue.

The stakeholders from the municipality were

interested in seeing a practical example that

could demonstrate how their own (siloed) data

could be used more effectively, for increased

efficiency and improved services. The stakeholder

from Climate-KIC was primarily motivated by the

prospect of supporting solutions that could

contribute to reducing CO2. Other industry

sponsors were motivated by having access to

future talent or present their products and/or

services. The participants in the hackathon were

mainly university students. While cash prizes and

just having fun were most likely strong motivatio-

nal factors, some of them were motivated by the

prospect of getting industry contacts and others

by their wish to start their own company. The

members of the City of Knowledge & Urban

Development were motivated by the potential of a

successful outcome, which could also promote

Lyngby-Taarbæk as a Smart City.

Interestingly, while different stakeholders

exhibited different motivations and drivers, they

collectively addressed a societal challenge through

the hackathon, i.e. climate change. As this wasn’t

the primary goal of any of the stakeholders besides

Climate-KIC, this finding is presented as evidence

of the usefulness of such a triple helix setup for

creating an environment where complex societal

challenges can addressed through synergies that

arise when strengths of individual sectors are

combined. The City of Knowledge and Urban

Development has created an environment where

the interests of different stakeholders with

different motivations are successfully aligned,

ultimately creating a win-win-win situation, which

made the resulting outcome possible. Ultimately,

all of the interviewed stakeholders shared the

notion that the success of the winning team,

Picodat, equaled their own success.

6 it might be controversial to include Climate-kiC in the industry category as they are a PPP which include industry partners, academic partners and public/not-for-profit organizations, thus representing a triple helix setup on their own. However, as they are 50% business, 30% academic and 20% public and not-for-profit, they are included with industry. http://www.climate-kic.org/about/how-we-are-organised/


they utilized calculations that require some

in-depth knowledge of concepts such as energy

efficiency. Moreover, they used a variety of

available information to draw conclusions

(increase their knowledge) about the cost-efficien-

cy of different approaches. The team needed to

pitch their solution to the committee of judges

and explain why it had potential to generate value

for the municipality. Besides technical skills, they

also needed, and made use of, business perspecti-

ves. It is encouraging to see how the students

managed to capitalize on the diversity of their

group and utilize this diversity in their efforts to

generate a solution that is both easy to under-

stand but at the same time quite sophisticated.

Hopefully their solution will not only help reduce

CO2 emissions in Lyngby-Taarbæk, but all around

Europe in the future. I personally hope that this

will be one of many initiatives that will drive

more open access to an increasing number of data

sources, which can later be used to address

societal challenges through improved information

dissemination and scientific knowledge, as well as

commercial products and services.

concLusionThe case of Picodat is a case of a successful

hackathon that resulted in a new big data startup

company and a solution that offers a potential for

Lyngby-Taarbæk to increase their own energy

efficiency and improve citizen service. Moreover,

the solution contributes to the important goal of

addressing climate change by reducing CO2

emissions. The City of Knowledge and Urban

Development managed to align the interests of

different stakeholders through use of the triple-

helix model, despite quite different motivations

and goals. In this case I have identified three

stakeholder roles for the triple helix model: The

Influencer, the Facilitator and the Implementer.

For future research, it could be interesting to

analyze and compare successful and unsuccessful

big data hackathons and search for existence of

these different roles.

Other findings related to use of open/big dataResearch has pointed out that there are five

main dimensions that contribute to the state of

openness of individual datasets (Jetzek, 2015).

These are: strategic dimension (availability),

economic dimension (affordability), legal

dimension (reusability), conceptual dimension

(interoperability) and technical dimension (usabi-

lity, accessibility and discoverability). In the case

of Picodat, the availability dimensions is quite

important as the team could find a number of

available datasets online that were not provided

by the Hackathon. The same goes for affordabili-

ty, it would have been a barrier if they had been

forced to pay for access to these data. As for the

other dimensions, Picodat did not comment on

open licenses or lack thereof. However, their

dependence on open licenses might increase

when they start to commercialize their solution.

Interoperability between heterogeneous datasets

did not seem to be a barrier in this case either, as

all the different datasets were linked through

the geolocation, which functioned as a common

identifier. The technical dimension did not seem

to be very important for this prototype work,

although some of the data that were used were

discovered through web searches and therefore

depended on the discoverability of the respective

data sources. Some of the data weren’t provided

or available in very user friendly formats,

however this did not discourage Picodat from

using them. Admittedly, this sentiment might

change when they try to scale up their solution

and make it more re-usable across different

municipalities. Moreover, it should be noted that

Picodat had direct access to the custodians of

most of the data, which might not be the case

when they develop the solution for other

countries.

Picodat made good use of all the talent in their

team and their ability to use complex mathe ma-

tical modelling is considered as an important

factor in the success of their solution. Moving

beyond the mashing-up of different sets of data,


REFERENCES

• Bolici, R. & Mora, L. (2015). Urban regeneration in the digital era: how to develop smart city strategies in large European cities. TECHNE: Journal of Technology for Archi-tecture and Environment, 5(2) [in press]

• Dawes, S. S., Creswell, A. M., & Pardo, T. A. (2009). From “need to know” to “need to share”: Tangled problems, infor mation boundaries, and the building of public sector knowledge networks. Public Administration Review, 69(3), 392-402.

• Etzkowitz, H. (1993). The Triple Helix: A North American Inno vation Environment. Available: http://taisurpjoe.tri-pod.com/NIS-PDF/America3.html

• Etzkowitz, H., & Leydesdorff, L. (1995). The Triple HelixUniversityindustrygovernment relations: A laboratory for knowledge based economic development. Easst Review, 14(1), 14-19.

• Etzkowitz, H., Dzisah, J., Ranga, M., & Zhou, C. (2007). The triple helix model of innovation: University-indu-stry-government interaction. Asia Pacific Tech Monitor, 24(1), 14-23.

• Jetzek, T. (2015). Managing Complexity across Multiple Dimensions of Liquid Open Data: The Case of the Danish Basic Data Program. Government Information Quarterly, in Press: doi:10.1016/j.giq.2015.11.003

• Kitchin, R. (2014). The realtime city? Big data and smart urbanism. GeoJournal, 79(1), 1-14.

• Marceau, J. (2008). Introduction: Innovation in the city and innovative cities. Innovation: Management, Policy & Practice, 10(2-3), 136-145.

• Nam, T., & Pardo, T. A. (2011). Conceptualizing smart city with dimensions of technology, people, and institutions. In Proceedings of the 12th Annual International Digital Government Research Conference: Digital Government Innovation in Challenging Times (pp. 282-291). ACM.

• Murray, R., Caulier-Grice, J. & Mulgan, G. (2010). The Open Book of Social Innovation. Available: http://www.nesta.org.uk/publications/open-book-socialinnovation

• OECD: Fostering Innovation to Address Social Challenges. Workshop Proceedings (2011), http://www.oecd.org/sti/inno/47861327.pdf

• Ranga, M., & Etzkowitz, H. (2013). Triple Helix systems: an analytical framework for innovation policy and practice in the Knowledge Society. Industry and Higher Education, 27(4), 237-262.

• Weber, E. P., & Khademian, A. M. (2008). Wicked problems, knowledge challenges, and collaborative capacity builders in network settings. Public Administration Review, 68(2), 334-349.

Conducted interviews• Interview 1: CEO, Picodat • Interview 2: Project Manager, Lyngby-Taarbæk City of • Knowledge and Urban Development• Interview 3: Entrepreneurship Lead, Climate KIC• Interview 4: CIO, Lyngby-Taarbæk Municipality• Interview 5: Associate Professor, DTU (Follow-up also

included a professor at DTU)


smart Cities are much more than fast internet connection, big data, and interlinked applications. the key is to set the human – both as a user and a citizen – at the core of the smart solutions, and keep the local context firmly in mind in order to gain most from the technology.in order to unleash the potential of smart Cities in Denmark, it is obvious to learn from experien-ces from abroad in relation to what it means to be a smart and digital city, and where the synergi-es with Danish strongholds are to be found. the innovation Centre Denmark is located in six of the biggest and most technology-oriented mega hubs in the world: silicon valley, shanghai, Munich, sao Paolo, new Delhi and seoul. We have spent some time investigating how smart cities develop, which policies are implemented and who the major stakeholders are. this article outlines some trends and policies taking a point of depar-ture in north American, south korean and German projects and decisions. Keywords: Smart City, Spatial Data, Innovation, ICT, Infrastructure, Energy Efficiency, Government, Policies, U-city

Maria Skouinnovation Centre Denmark in seoulMinistry of Foreign [email protected]

Nicklas Echsner-Rasmusseninnovation Centre Denmark in seoul, University of Copenhagen, [email protected].

Smart citieS around the world


introductionJust like cities are not made up by the bricks but by

its inhabitants, Smart Cities are much more than

fast internet connection, big data, and interlinked

applications. The key is to set the human – both as

a user and citizen – at the core of the smart

solutions, and keep the local context firmly in

mind in order to gain most from the technology.

Smart Cities has been a buzzword for a number

of years, and it is stated to contain endless

opportunities for growth and welfare. Although

full-scale Smart Cities and real market opportuniti-

es are only emerging slowly, it is an area that not

only Denmark seeks to exploit and benefit from; it

is also an area within which Denmark has better

conditions for excelling than most other countries.

In order to unleash the Danish potential,

develop, and capitalize from smart city technolo-

gies it is paramount that we understand how the

rest of the world positions itself in relation to what

it means to be a smart and digital city, and where

the synergies with Danish strongholds are to be

found.

The Innovation Centre Denmark is located in six

of the biggest and most technology-oriented mega

hubs in the world: Silicon Valley, Shanghai,

Munich, Sao Paolo, New Delhi and Seoul. We have

spent some time investigating how smart cities

develop, which policies are implemented and who

the major stakeholders are. This article will outline

some trends and policies taking a point of

departure in American, South Korean and German

projects and decisions.

case 1: usaIn many ways the US is the absolute leader within

the field of smart cities technologies. One of the

most prominent trends is using Internet of Things

(IoT) as the next level in smart cities development.

According to IoT 1Analytics seven of the top-10

Internet of Things (IoT) cities in the world are

located in the US, with San Francisco as no. 1

hosting 325 headquarters of IoT companies,

smaller start-ups as well as enormous tech

companies such as Cisco, Google, Apple and Intel.

Forecasts predict that no less than 75 billion IoT

units will be connected in 2020, pushing the

development of city 2integration . The decreasing

price of sensors as well as improved wireless and

cloud-based solutions has let the technologies

diffuse into people’s everyday lives.

In terms of innovation capability and technolo-

gical research, the U.S. is clearly the nation

spearheading global R&D and innovation. The

development is driven primarily by the private

sector, which underlines the key characteristic

behind the American leading position: Innovation

has been achieved on the background of beneficial

legislation enabling conducive public-private

partnerships and a thriving entrepreneurial

community. Nowhere is this more evident than in

Silicon Valley.

At the same time, however, the greater San

Francisco area is also the best example of the

paradox that the US presents us with. New

technologies, smart solutions, and innovative

business models are abundant, but Smart City

infrastructures are conspicuously few. In terms of

the ICT infrastructure, only 7,7 % of the population

in the US has optical fiber internet (the fastest and

highest quality available), and San Francisco ranks

a low number 208 out of 408 cities in terms of city

3connectivity .

The potential has been recognized by the

Obama administration in the latest Smart Cities

Initiative, released in September 2015, wherein

“the opportunity to be a global leader” is acknow-

ledged. In terms of federal spending, $ 45 million is

allocated to new grants and proposed investments

to build a research infrastructure for Smart Cities

by the National Science Foundation and National

Institute of Standards and Technology, as well as an

additional total of $ 115 million to find new

solutions to public policy challenges. Also,

1 http://iot-analytics.com/top-15-internet-of-things-cities/2 http://www.slideshare.net/GridPoint 3 http://onesanfrancisco.org/wp-content/uploads/Agenda-item-4-Dt-Connectivity-Presentation-revised.pdf


initiatives and policies including investment grants

dedicated to Smart Grid projects totaling $ 3.4

billion have been launched by the current admini-

stration. The grants follow an industry matching

model, meaning that every private investment

made will be matched by federal grants. This is an

unparalleled investment scheme and one that

underlines the fact that the current government

wishes to maintain and develop the American

leading position within smart cities. As the

U.S.-model represents the most market driven

approach to smart cities, it will be of huge interest

to see what solutions and business models will be

developed in the coming years, both in large

corporations as well as in small and medium sized

companies. This will have a global impact on the

perception and development of smart cities.

case 2: soutH koreaSince 2003, South Korea has retained its top spot in

the United Nations E-Government Development

Index, which among other things is due to its

impeccable ICT infrastructure. Ultra-fast LTE

network (4G) is accessible in most of South Korea,

making it the most connected country in the

world. There is a 100 % LTE penetration rate in

Seoul with 831 free wi-fi zones provided by the

local government, and one of the major banks in

South Korea has funded mobile phone chargers at

these Wi-Fi spots, so everyone can access the

internet and get their phones charged at designa-

ted spots in the city. In January 2014, the South

Korean government announced that it will

upgrade the country’s wireless network to 5G by

2020 making downloads about 1,000 times faster

than with the current LTE (4G) network. Moreover,

in September 2014, the European Union and South

Korea agreed to cooperate on developing ultra-fast

fifth-generation wireless communications

networks, i.e. 5G. The agreement covers govern-

ment, research and educational institutes and

private companies, and aims to forge a consensus

on key functionalities for the new standard by the

end of 2015. The big telecommunications compa-

Figure 1. The World’s Leading IoT hubs


nies and the South Korean government agreed on a

roll-out plan for 5G network starting from 2017.

Thus, South Korea will maintain its technological

front runner status and prepare for future ICT

functionalities, also in the smart cities’ area.

Unlike the smart city concept, which originated

in Western countries, the South Korean U-city

(Ubiquitous City) is driven by establishment of

ubiquitous ICT systems in new towns mostly

through government/local government top-down

measures; Smart city is a concept centered around

physical, intellectual and social capital in existing

cities (see table below). This implies that the South

Korean central government and local governments

are the main drivers to U-cities development in

South Korea.

The South Korean Government established a

first phase of the U-city plan from 2009 to 2013,

and a second phase plan is running from 2014 to 5 2018. The first plan focused on setting up the

basic infra-structure for U-city, the second plan is

trying to combine U-city with various national

agendas such as urban regeneration, balanced

national development and national safety measu-

res. Additionally, the second plan seeks to support

private companies in developing U-city technologi-

es and promoting overseas business through

international cooperation. Target countries are

among others Mongolia and Malaysia.

The most prominent U-city example is the

creation of the U-city Project in the Incheon Free

Economic Zone (“IFEZ”), also called New Songdo

City. The gross area is total 209 km2 including

Songdo, Yeongjong and Cheongra, which are all

areas reclaimed from the shallow waters of the

Yellow Sea. Each area has a different development

concept, such as international business and

high-tech industry for Songdo, logistics, tourism

and leisure for Yeongjong, and international

finance and sport leisure for Cheongra. IFEZ is the

leading U-city project and runs from 2006- 2020

with a budget of approximately $ 490 million. The

New Songdo City is built to be smart from the

beginning. A key element is the Operations Centre

which manages a large number of wireless CCTV’s

to monitor and overview the city in terms of for

4 http://cityprotocol.org/5 korean Ministry of Land, infrastructure and transportation

U-City Smart City

Purpose solutions to urban problems, improve-ment of quality of life, job creation, use of data, system efficiency

solutions to urban problems, impro-vement of quality of life, job creation, low-cost and high efficient space

Concept Physical capitaliCt centricDigital city

Physical + social capitalDigital + knowledge cityintelligent city

Target new townssystem integration basisservice system

Old & new townssolution basissmart grid

Agent Central and local governments Private firms (Cisco, iBM, etc.), instituti-ons and universities

Means Government drivenU-city world forumU-city road show

Global city alliancesGovernments, academia, nGO, 4City protocol society

Tabel 1. The different U-city and Smart City concepts Source: Korean Planning Association


U-City Smart City

Purpose solutions to urban problems, improve-ment of quality of life, job creation, use of data, system efficiency

solutions to urban problems, impro-vement of quality of life, job creation, low-cost and high efficient space

Concept Physical capitaliCt centricDigital city

Physical + social capitalDigital + knowledge cityintelligent city

Target new townssystem integration basisservice system

Old & new townssolution basissmart grid

Agent Central and local governments Private firms (Cisco, iBM, etc.), instituti-ons and universities

Means Government drivenU-city world forumU-city road show

Global city alliancesGovernments, academia, nGO, 4City protocol society

instance safety and security (disaster, fire and

crime), traffic and transportation information.

Many other U-city projects in Korea are heavily

focused on the traffic sector. Bus information

service applications are common and are created

via using open data. A well-known example is the

Daum Kakao’s taxi app Kakao Taxi, which has

proven to become the ‘Korean Uber’. Kakao Taxi

finds the fastest available cab based on the

distance, traffic, and ETA. After identification, it

sends the driver’s name, photo, phone number and

car information to the passenger. The passenger

can also send notification messages to friends

telling the ride information. As the ride is finished,

both the passenger and the driver can rank their

service and experience. In the near future, Daum

Kakao is planning on adding its payment service

Kakao Pay or Bank-Wallet Kakao to Kakao Taxi.

The challenge with the Korean U-city concept is

that it is mainly driven by the government. Several

Korean ministries are involved in the national

U-city scheme and they sometimes fail to coordina-

te their planning of policies and budgets. Moreover,

U-city projects are highly up to political decisi-

on-making, thus a possible change of government

results in uncertainty of on-going projects.

The viability of the Korean U-city concept will be

tested in the coming years with the emerging IoT

technologies, the focus on healthy living and

citizens, as well as the efforts to export to countries

where lack of ICT infrastructure is a key factor.

Most importantly, however, is Korea’s ability to

keep being the main developer of future ICT

infrastructure, which is widely considered to be

the main competitive advantage of the Korean

U-city concept.

case 3: GermanyIn Germany, the main element of smart cities is

sustainable growth and transportation, and how

smart solutions can improve energy management

and achieve energy-efficiency. The Federal govern-

ment launched the 2010-plan to phase out nuclear

power, which puts heavy emphasis on developing

renewable energy technologies as well as energy-ef-

ficient solutions. Grounded in historical reasons,

Germany has a huge interest in privacy and data

protection – perhaps to the furthest extent in the

world. Hence, this is a prerequisite for the develop-

ment.

Figure 2. Infrastructure in Seoul, Korea


Thus, ”Efficient Energy Use” plays a crucial role

in Germany’s smart cities’ conceptualization. Many

municipalities and regions in Germany have set

the goal of Renewable Energy Self-sufficiency

(RESS). Main drivers are Munich, Berlin, Hamburg,

and Mannheim. The Federal Ministry of Economics

and Energy therefore promotes research on energy

efficient cities and energy efficient heating and

cooling networks. In addition to the energetic

optimization of individual buildings, the aim of

raising energy efficiency depends crucially on a

comprehensive approach to urban areas as well as

to local and district heating networks. This

potential is improved significantly via intelligent

use and networking of innovative technologies

with research and pilot projects.

Germany launched a project called “100 %

Erneuerbare-Energie-Regionen”. This project

identifies and monitors regions, municipalities

and cities that want to convert their future energy

supply entirely to renewable energy. At present,

there are already more than one hundred and forty

counties, municipalities, regional associations and

cities in Germany that are following this goal. The

project supports committed actors in the regions

through communication, transfer and networking

services. In addition, the contest ”Energy-Efficient

City” of the Federal Ministry of Education and

Research aims at increasing the target energy

efficiency in cities and municipalities geared

towards the climate protection targets of the

Federal Government and the relevant municipal

structures and functions.

“Elektromobilität” (e-cars) is another major

focus area for the German government. It is

expected that Germany will have one million

e-vehicles by 2020 and 6 million in 2030, meaning

that Germany will be a leading provider and a

leading market for electric mobility by 2020.

Germany had 24,000 electric vehicles on its roads

in 2014. The Federal Ministry of Transport,

Building and Urban Affairs has implemented a

program named “Electro-mobility model regions”

in Germany. The electric mobility scheme is

Figure 3. Map of Smart cities and energy efficient regions

6 https://us.drive-now.com/#


financially supported in eight German metropoli-

tan regions and the funding comes from funds

from an economic stimulus package. Another

aspect of smart transportation and ‘Elektromobi-

lität’ is the DriveNow software 6program . The

connected car integration enhances the consumer

experience by connecting the DriveNow users’ daily

needs across content categories as well as providing

access to real-time information and a personalized

view of their surroundings. This interactive

solution dovetails with BMW’s overarching goal to

become the leading provider of electric mobility.

The program received recognition from media

outlets including Wired.

On the R&D side, the research foundation

Fraunhofer has launched the Fraunhofer Morgen-

stadt, which is a large-scale project addressing the

various challenges and opportunities of Smart Cities.

The Morgenstadt program explores how district-level,

municipal and regional demonstration and innovati-

on projects, which integrate clean technologies with

business models, can result in Cities of the Future

with net-zero emissions, minimal waste and

maximum quality of life for its 7citizens .

In Munich, the “Smart Cities and Communities

solutions integrating energy, transport, ICT sectors

through lighthouse (large scale demonstration

– first of the kind) projects” started in 2014-2015.

The total budget for the projects is approximately €

200 million. The plan stems from the Munich City

Council decision “Climate Protection Program

2013”, which includes more than 60 individual

measures in eight actions fields. The scope is to

identify, develop and deploy replicable, balanced

and integrated solutions in the energy, transportati-

on sectors, and ICT actions through partnerships

between municipalities and industries. The projects

will be lighthouse projects as identified by the Com-

munication on Smart Cities and 8Communities .

concLusionThis brief presentation of policies and trends has

only vaguely opened the black box that the concept

of Smart Cities constitutes. However, we see some

distinct characteristics of the continents embodied

by the three countries.

While the U.S. is heavily favoring the involve-

ment of the private sector in development of smart

cities, the South Korean U-city approach is much

more top-down and government controlled.

Expanding the view to include a wider range of

Asian countries one would find that South Korea is

actually very liberal compared to China or Japan.

Germany also has a strong government

involvement in Smart City initiatives but with a

specific aim to reduce energy consumption and

generate a shift from fossil fuels to renewables. A

bold strategy backed by the industry and research

institutions paving the way for many comprehensi-

ve solutions with a potential global impact. The

article has furthermore highlighted the difference

between an infrastructure and application focus.

Again, this is a distinction that would stand out

even more if we include for instance India or

Brazil, where basic infrastructure still is a major

challenge. In a country such as the U.S. the ICT

backbone is still not aligned between urban and

remote rural areas, whereas South Korea has an

impeccable infrastructure and a strong focus on

functionality and technical systems, and now needs

to shift their priorities and put the user at the core.

This is where the Danish focus on user-friendliness

and human utility comes into the picture. Danish

smart city solutions are unique and the leading

principle seems to be that the more inclusive we can

make our solutions the better they will fare.

This is something valuable that Danish busines-

ses, municipalities and researchers can bring to the

table, if they want to collaborate internationally.

Likewise, the private initiative, the strong strategic

aims and the focus on ICT systems from the three

countries described are strongholds that also Danish

partners could learn from. The combination and

innovation of smart cities has only just begun.

7 http://www.morgenstadt.de/en.html8 http://www.muenchen.de/rathaus/stadtverwaltung/referat-fuer-Gesundheit-und-Umwelt/klimaschutz_und_energie/klimaschutzstrategie/iHkM.html

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