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.

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

9. MOBILITY DATA INITIATIVES

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

13. 13
CONSUMPTION DATA CLASSIFICATION

14. 14
CONSUMPTION DATA CLASSIFICATION

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.

24. THANK YOU
QUESTIONS