How to build Open data Ecosystems for Smart Cities: European experience Alberto Abella
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1 How to build Open data Ecosystems for Smart Cities: European experience Alberto Abella
2 Examples Trends 1 Smart City Ecosystem 1 Success factors Smart cities 2 An Strategic open data plan 2 Ogov passive vs active 3 EU Smart city Ecosystems 3 Citizen Experience 4 Apps4EU 4 Data reuse: MELODA
3 Smart city Ecosystem Source: Abella, Ortiz-de-Urbina and De Pablos (2015)
4 A strategic open data plan Agenda - 4 items Dataset Dataset inventory inventory Owners, Owners, legal legal conditions, conditions, updating, updating, responsibilities responsibilities Best Best practices practices Lessons Lessons learnt learnt all all over over EU EU Sustainability Sustainability Savings Savings and and incomes incomes (direct (direct and and indirect) indirect) Promotion Promotion Nurturing Nurturing and and Supporting Supporting the the ecosystem ecosystem Existing Existing and and potential potential businesses businesses Check Check what what datasets datasets could could be be useful useful for for business. business. Ask Ask ecosystem. ecosystem.
5 EU Smart cities ecosystems Ecosystem's Ecosystem's populations populations City StartersStarters- Mature Mature -- Advance Advance Different Different ecosystems' ecosystems' size size Different Different stages stages Helsinki London Bologne Zaragoza Zurich Berlin Amsterdam Liverpool Milano Marseille Malaga Strasbourg #Apps Source: Abella, Ortiz-de-Urbina and De Pablos (2015)
6 EU Smart cities ecosystems Agenda - 4 items Timeliness Timeliness Apps Apps % % Apps Apps were were real-time real-time Geolocated Geolocated Apps Apps % % Apps Apps provide provide geolocated geolocated information information Creators Creators % % Apps Apps City. City. 26% 26% Developers Developers 14% 14% SME SME 14% 14% unidentified unidentified Hot Hot topics topics Transport Transport % % Other Other (Tourism) (Tourism) 26% 26% Source: Abella, Ortiz-de-Urbina and De Pablos (2015)
7 Smart city Ecosystem Madrid: Madrid: fines fines published published Amount, Amount, type, type, location, location, etc etc
8 Smart city Ecosystem Barcelona: Barcelona: to to downloads downloads Based Based on on data data released released by by Barcelona Barcelona Smart Smart city city Successful Successful competitor competitor (single (single developer) developer)
9 Apps4EU Force Field Analysis 1 Incubators not investors 2 Data standardization 3* Business Lounge Ecosystem populated Lessons learnt ( ) Online competitions 1 Support & promotion 2 Update data sources 3*
10 The open circle Open Open circles circles Release info Roads Roads (2194 (2194 ) ) High High Speed Speed train train (3561 (3561 M ) M ) Wikipedia Wikipedia M M Profit from release No return No No impact impact model, model, just just political political impulse impulse
11 Change in data licensing terms CHANGE IN LICENSING TERMS IN SPAIN IN OPEN DATASETS 100% 88% 90% 84% 80% 70% 60% % 40% 30% 20% 12% 16% 10% 0% Copyright and restrictive licensing Commercial & only attribution Source: Abella (2013)
12 Success factors in Smart cities Internal External Social capital Human capital Civic Engagement Governance SMART CITY Economy (competitiveness) Infrastructure and ICT Environmental Sustainability Source : Kogan 2014
13 Success factors in Smart cities Source : Kogan
14 Open government passive vs active Breaking Set (Adding new ideas) 1 OGOV Active Passive 2 Goals Service s improvement Having lots of people in well designed sites 3 Participants Representative citizens sample Those willing to participate 4 Info. Release Actual demand and use Authorities interests and availability 5 Timeliness ASAP Once reviewed 6 Applications Ecosystem of developers Own development 7 Participation Commitment to answer Just open 8 Training In place No (just principles) Source: Abella, Ortiz-de-Urbina and De Pablos (2015)
15 New Standards Smart Smart Cities Cities Open Open data. data. AENOR AENOR : : Dimensions POLITICAL DOMAIN TECHNICAL DOMAIN Strategy and political dimension Availability dimension LEGAL DOMAIN Access dimension Legal Domain Data quality dimension ORGANISATIONAL DOMAIN Updating dimension Organisational dimension SOCIAL AND ECONOMIC DOMAIN Assessment dimension Reuse dimension Participation and collaboration dimension
16 Citizen Experience Analysis Analysis 1/5 1/5 1 2 Benchmark: Best practices 4 Qualitative Focus group and interviews 3 Quantitative Sampling Detect statistically sound user needs in order to define features of the service
17 Citizen Experience Design Design experience experience 2/5 2/5 Involving Involving agents agents and and stakeholders stakeholders in in services services Redesign Redesign Co-design Co-design
18 Citizen Experience Modelling Modelling experience experience 3/5 3/5 Statistical Statistical approach approach Driver For every attribute of experience Attribute TOUCHPOINTS Innovation LIFECYCLE PHASE Office Call Center Driver 1 (x %) Driver 3 (z %) ATM Stage impact on attribute Discover Brand SERVICE experience Save Time Use of services Driver 2 (y %) Driver 4 (t %) Discover Brand. Trust Finishing Driver 5 (a %) Driver 6 (b %) Channel impact on attribute
19 Citizen Experience Implementation Implementation 4/5 4/5 Phases Phases Gantt Gantt
20 Citizen Experience Governance Governance 5/5 5/5 Stable Stable centre: centre: User User Test Test Centre Centre Automatic report Automatic report KPI database Input forms Repository of indicators Scorecard Design of the input forms about operative data on the KPI of Citizen Experience Design of the data model. Use of ETL and visualization tools Periodic routines of exportation Visualization about current situation and KPI of Citizen experience evolution
21 Data reusabilty : MELODA Metric Metric releasing releasing Open Open DAta DAta Quantifies Quantifies reusability reusability of of data data sources sources Related Related with with reuse reuse Related Related with with value value creation creation MELODA MELODA
22 Questions & Answers
23 Thanks Alberto Abella Consultancy: Academia:
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