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The role of open data in driving sustainable mobility in nine smart cities

The work was presented in European Conference on Information Systems (ECIS 2017) , at Guimaraes Portugal. The work presents a comprehensive survey results on open data focused in mobility domain in nine smart cities like Barcelona, Dublin, NewYork etc.

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The Role of Open Data in Driving Sustainable Mobility in
Nine Smart Cities
Piyush Yadav, Souleiman Hasan, Adegboyega Ojo, Edward Curry
OUTLINE
1 Introduction
2 Objective
3 Sustainable Mobility Indicators
4 Mobility Open Dataset Statistics and Initiatives
5 Production, Consumption and Nature of Mobility Data
6 Mobility Open Data Applications and its Impact
7 Conclusion
INTRODUCTION
3
Sustainable Mobility
Goal 11: Make cities inclusive, safe, resilient and sustainable
Provide access to safe,
affordable, accessible
and sustainable
transport systems
Improving road
safety, notably by
expanding public
transport
Special attention to
the needs of those in
vulnerable (women,
disabilities)
INTRODUCTION
4
Open Data in Smart City
European Commission ➔ EU eGovernment action plan 2011-2015 ➔ Publishing
public information on its portal to harness its capabilities through its reuse
UNE 1783 ➔ Standard➔ specific guidelines in terms of requirements, indicators,
and policies to make open data more mature so that it can be used in the smart city
perspective.
Aligning open data to smart city context
OBJECTIVE
5
Analysis of mobility open data initiatives in nine smart cities
Mobility Open Data in 9 Smart Cities
• Amsterdam
• Barcelona
• Chicago
• Dublin
• Helsinki
• London
• Manchester
• New York
• San Francisco
SELECTION CRITERIA
6
Selection
Criteria for
Smart Cities
Mission
Statement
• Well-established mission and plan
Open Data
Advocacy
• Have a strong open data initiative and policies
and best open data practices
Open Data
Production
• Significant amounts of data should be
available in public domain for use

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The role of open data in driving sustainable mobility in nine smart cities

  • 1. The Role of Open Data in Driving Sustainable Mobility in Nine Smart Cities Piyush Yadav, Souleiman Hasan, Adegboyega Ojo, Edward Curry
  • 2. OUTLINE 1 Introduction 2 Objective 3 Sustainable Mobility Indicators 4 Mobility Open Dataset Statistics and Initiatives 5 Production, Consumption and Nature of Mobility Data 6 Mobility Open Data Applications and its Impact 7 Conclusion
  • 3. INTRODUCTION 3 Sustainable Mobility Goal 11: Make cities inclusive, safe, resilient and sustainable Provide access to safe, affordable, accessible and sustainable transport systems Improving road safety, notably by expanding public transport Special attention to the needs of those in vulnerable (women, disabilities)
  • 4. INTRODUCTION 4 Open Data in Smart City European Commission ➔ EU eGovernment action plan 2011-2015 ➔ Publishing public information on its portal to harness its capabilities through its reuse UNE 1783 ➔ Standard➔ specific guidelines in terms of requirements, indicators, and policies to make open data more mature so that it can be used in the smart city perspective. Aligning open data to smart city context
  • 5. OBJECTIVE 5 Analysis of mobility open data initiatives in nine smart cities Mobility Open Data in 9 Smart Cities • Amsterdam • Barcelona • Chicago • Dublin • Helsinki • London • Manchester • New York • San Francisco
  • 6. SELECTION CRITERIA 6 Selection Criteria for Smart Cities Mission Statement • Well-established mission and plan Open Data Advocacy • Have a strong open data initiative and policies and best open data practices Open Data Production • Significant amounts of data should be available in public domain for use
  • 7. 7 SUSTAINABLE MOBILITY INDICATORS Target Dimensions Global Environment Economic Success Mobility System Performance Quality of Life Energy Efficiency Mitigation and Adaptation Liveability Condition Access Affordability Travel time Risk and Safety Public Area and Space Usage Governance Public Finance R&D Pricing Reforms Taxes and Subsidies Facility Costs Security Congestion and Delays Intermodal Connectivity and Integration Active Mobility Intelligent System management
  • 8. MOBILITY OPEN DATASET REVIEWED Smart Cities/ Characteristics Dataset Review Application Review API Review Open Data Platforms (Search) CKAN SOCRATA Amsterdam 15 11 4 3 0 Barcelona 23 16 0 10 0 Chicago 14 16 3 0 151 Dublin 14 16 4 2 0 Helsinki 10 22 2 1 0 London 20 4 18 10 0 Manchester 8 3 1 0 0 New York 22 7 4 1 744 San Francisco 22 10 3 0 133 Total 148 105 39 27 1028
  • 10. 10 MOBILITY OPEN DATA EVALUATION • Types of open mobility data • Characteristics (Format , Batch, Real-time) • Applications available • API available • Open Data Portal Technology • Taxonomy for Mobility Domain • Classify Datasets • Classify end user usage • Classify API • Identify Portal Platform Production Consumption
  • 11. PRODUCTION DATA CLASSIFICATION 0 10 20 30 40 Bus Car Cycles Rail Flight Ferry 0 5 10 15 Casualties Penalties Safety 0 5 10 15 20 Counts Signals Traffic Information Modes Of Transport Accident Traffic 0 10 20 30 40 50 Road Work Requests Signs Timetables Permits Meter Car Sharing Services
  • 12. PRODUCTION DATA CLASSIFICATION 0 10 20 30 40 Environment Health Energy Consumption 0 5 10 15 20 25 30 Events Culture Travel Visitors 0 20 40 60 80 Parking Stations Entry Routes Sustainability Tourism Infrastructure
  • 15. CHARACTERISTICS : NATURE OF MOBILITY DATA 0 2 4 6 8 10 0 1 2 3 Static Realtime Static • Changes very rarely • Bus/tram stop locations, gas stations, routes information, parking facilities etc. • Update frequency-half yearly, yearly or more. Dynamic • Updated frequently like daily, weekly, monthly, quarterly . • Realtime data- updated constantly from minutes to seconds like the locations of buses or trains, and their arrivals.
  • 16. CHARACTERISTICS : NATURE OF MOBILITY DATA 0 3 6 Daily 0 1 2 3 4 Weekly 0 2 4 Monthly 0 1 2 Quarterly
  • 17. CHARACTERISTICS : DATA INTERACTIVITY Documents • Provide general information • Least developer friendly • Cost of effort to visualize and use is significant. • Zip/Tar,Pdf/Txt/Doc/ppt, Image, Bin Machine Readable Data • Somewhat developer friendly. • Effort is required to deploy and visualize • Tabular(xlsx),Csv/Tsv, Json, Html,Xml Developer Friendly Format • Highly developer friendly • Minimum or no effort is required. • Geojson, Api’s/Odata, Wms/Wfs,Kml/Kmz, Rdf,Shape/Sbn/Sbx
  • 18. No. of dataset formats in nine smart cities Comparison of dataset formats in terms of developer interactivity CHARACTERISTICS : DATA INTERACTIVITY
  • 19. 19 IMPACT OF OPEN DATA ON MOBILITY • Real-time information of current parking spaces • Current pricing and tariffs, • Information regarding disabled friendly parking’s • Better management of space usage • Peak management Better Parking Management • Improved safety- providing advisories, potential collision areas, • Improved productivity- reducing congestion and suggesting alternative routes, • Better planning - interactive visualizations showing live camera pictures, schedules, etc. Intelligent Traffic Management • Transit easier and faster • Choose options with the most effective, fastest or cheapest route • Travel more accessible and convenient Improved Transit
  • 20. 20 IMPACT OF OPEN DATA ON MOBILITY • Various applications on Air polluting emissions, Noise Hindrance, Water effluents, GHG . • People aware of their surroundings and inspired to use cleaner fuels , electric vehicles and avoid habitat destruction. Increased Environmental Awareness • Improving people awareness of soft modes options like walking and cycling. • Pedestrian-friendliness of streets, bike trails Active Mobility • Made the travel convenient, economical, and accessible to a larger mass by bring potential travelers together. Increased Trend in Ride Sharing
  • 21. 21 IMPACT OF OPEN DATA ON MOBILITY • Data from Smart Cities opened immense opportunities to develop new innovative solutions and services to resolve mobility challenges Fostering Innovation and R&D • Mobility distribution model where the transportation needs of individuals are satisfied by a service provider over a single interface. • Ride-sharing, trip planning, digital payments, on-demand services Mobility as a service (MaaS)
  • 22. OPEN DATA PORTAL PLATFORMS Open Data Platforms Amsterdam Barcelona Chicago Dublin Helsinki London Manchester New York San Francisco CKAN 3 10 0 2 1 10 1 0 0 Socrata 0 0 151 0 0 0 0 744 133 CKAN Query Barcelona http://ckan.opendata.nets.upf.edu/dataset?q=barcelona London https://datahub.io/api/3/action/package_search?q=london%20%transport%20isopen:true Socrata Query New York https://www.opendatanetwork.com/search?q=new%20york&categories=transportation • CKAN • Socrata • DKAN • Junar • OpenDataSoft
  • 23. 23 CONCLUSION • Study helps us to better understand open mobility data in the context of smart cities and understand its impact in nine smart cities. • Diverse mobility datasets and applications are available. • Various open data publishing platforms and mobile stores have made the availability of these API’s and applications easily accessible to end-users and developers . • Moving towards more citizen-centric and participatory mobility model leveraging ICT and open data as its backbone. • Impacts of open data in creating sustainable mobility.