Lecture week 5 -

Open Data-Driven Innovation
and Smart Cities
Fatemeh Ahmadi-Zeleti
Insight Centre for Data Analytics
National University of Ireland, Galway (NUIG)
fatemeh.ahmadizeleti@insight-centre.org
@fatemehahmadi_

Open Data
Data that are freely available to everyone to use and republish as they wish without
restrictions from copyright, patents or other form of control mechanisms
Share public data for transparency, participation, and stimulate new services based on
the data
e.g. Public Sector Information (PSI)
Open Science Data
Open Data gained popularity with launch of Open Data Initiatives such as Data.gov and
Data.gov.uk
http://dl.acm.org/citation.cfm?id=2612745

Open Data Cont.
[Open Data is] going to help launch more businesses…
It’s going to help more entrepreneurs come up with
products and services that we haven’t even imagine
yet.
http://www.worldbank.org/content/dam/Worldbank/Feature%20Story/ICT_India_OpenDatainDevelopment.pdf

Open Data Cont.
The World Bank’s Open Data Initiative, which was launched in April 2010,
provides free, open, and easy access to development data, and challenges the
global community to use the data to create new solutions to eradicate poverty.
Today, the World Bank’s Open Data Catalog includes over 8,000 development
indicators, of which 1,400 for 252 countries and 36 aggregate groupings, going
back over 50 years, in 50 languages, and is continuously expanding
https://www.youtube.com/watch?v=PzWpcVzuwV0

Open Data-Driven
Innovation
Data can enable any kind of
innovation.
Data-driven innovation can be a
sustainable source of economic
growth but capturing its full
potential will require a
concentrated effort from
governments, businesses and
individuals
Open Data-Driven
Planning
Data can be used to make robust
decisions on the basis of
facts, trends and patterns
rather than the more variable
tools of management
expertise or ‘gut feel’.
e.g. Queensland Health
Data-Driven Goods
and Services
Data can be used to help
businesses create new
products and services that
respond to customer needs
faster than ever before
e.g. SocietyOne
Open Data-Driven
Marketing
Businesses can radically improve
cost efficiencies and market
agility through the data they
capture about their processes
and products.
e.g. Amazon
Open Data-Driven
Operations
Data can be used by
businesses to identify new
customers, or increase
satisfaction and spend.
e.g. Tip Top Bakeries
http://www.pwc.com.au/consulting/assets/publications/Data-drive-innovation-Sep14.pdf

Open Data-Driven Innovation
Data driven innovation... is the value from using any kind of
data to innovate
Data itself is not inherently valuable. Value is created by
working more intelligently with it to innovate, invent,
change business processes, and enhance decision-making
Data-driven innovation can differ from industry to industry
in terms of the rates of innovation and types of
innovation. Some industries are characterised by step-
change innovations and others by smaller, incremental
improvements.
http://www.pwc.com.au/consulting/assets/publications/Data-drive-innovation-Sep14.pdf

Open Data Innovation Ecosystem:
World Bank
https://www.youtube.com/watch?v=07LFJYB2o3I

Innovation in City
• Improve the way citizens live in a city
• Cities are the most important innovation platform
• Innovation, most of all, is driven by collaboration. So it
takes more than just smart people, but diversity as well
• Design + Technology = eco city, green city, sustainable
city and etc.
http://www.forbes.com/sites/gregsatell/2013/11/09/why-cities-are-our-most-important-innovation-platform/

Innovation Dimension in Cities

Waves of Open Data Innovation
Approach in Cities
Networks
of Civic
Innovation
Offices
Need-
driven
Programs
Hack
Events
“Direct” engagement of residents, city managers, other stakeholders
Freedom for bottom up innovation, techno-centric with “token”-level
participation of city management and residents
+t
http://conferences.computer.org/hicss/2015/papers/7367c326.pdf

Wave 1 Exemplar – Dutch Open
Hackathon
Available datasets including airport shuttle bus events, job
data, flight data, supermarket, order etc.
http://www.dutchopen
hackathon.com

Wave 2 Exemplar –
Summer of Smart in San Francisco
Engage mayoral candidates in
San Francisco (2011) on
solutions by Hack Teams to
pressing problems in areas
including 1) Community
Development, 2) Buildings.
Transportation and
Sustainability, 3) Public
Health, Food and Nutrition
Focus is on real needs and
involvement of major
stakeholders in solutions
Source: http://www.summerofsmart.org/home/

Wave 3 Example :
New Urban Mechanics
Boston
UtahPhilly
A Network of civic innovation offices in
Boston, Philadelphia and Utah.
Each of the innovation offices serve as
the in-house research and development
group for the respective mayors.
They build partnerships between
internal agencies and outside
entrepreneurs to pilot projects that
address the needs of residents
https://www.youtube.com/watch?v=Hg
Px_TuF-Js
http://newurbanmechanics.org

Smart Cities Initiative Development
Framework (SCID)
SCID developed
from the studies
of smart city
programs in 10
countries.
Links Smart City
initiatives to
concrete city
domains and
associated
stakeholdersA. Ojo, E. Curry, T. Janowski, Designing Next Generation Smart City
initiatives, ECIS 2014, Isreal

City Cases
Chicago, Helsinki, Amsterdam, Barcelona and Manchester

Chicago
Economy: Data Science Chicago, Chicago Shool of Data
Governance: Data Science Chicago, Chicago Shool of Data
Health & wellbeing: Chicago Shool of Data
Environment: Chicago Shool of Data
Transportation & mobility: Chicago Shool of Data
Education: Chicago Early Learning Portal, Chicago Shool of
Data
Tourism: Chicago Shool of Data

Helsinki
Economy: Smart Kalasatama, Helsinki Region Infoshare,
Apps4Finland, Helsinki Loves Developers
Governance: CitySDK
Health & wellbeing: CitySDK
Environment: CitySDK
Transportation & mobility: CitySDK
Education: CitySDK
Tourism: CitySDK
http://conferences.computer.org/hicss/2015/p
apers/7367c326.pdf

Amsterdam
Economy: Code4Europe
Governance: Apps for Amsterdam
Health & wellbeing: Apps for Amsterdam
Environment: Apps for Amsterdam
Transportation & mobility: Apps for Amsterdam
Education: Apps for Amsterdam
Tourism: Apps for Amsterdam

Manchester
Economy: Greater Manchester Data Synchronization
Program (GMDSP), Greater Manchester Datastore,
Transport for Greater Manchester
Governance: GMDSP, Greater Manchester Datastore
Environment: Transport for Greater Manchester
Transportation & mobility: Transport for Greater
Manchester

Impact Domains
Governance and Economic Domains standout …

Impact Domains
Domain Impact Patterns
Economy Creation of marketplace for society
relevant applications;
Availability of data products and
services based on city operational
data and;
Scaling up the adoption of open
data innovations across city
functions through tools provision.
Education Availability of innovative digital
services for the education domain.
Energy Availability of innovative digital
services for the education domain.
Environment Greener environment.
Governance Better information sharing; open
innovation for co-created services;
open engagement in policy and
decision making; and interoperation
within city-network.
Tourism Co-created services based on
available open data.
Transportation Better City Park Management; and
Shorter transit time for commuters.

Governance Mechanisms
Five governance mechanisms:
1) Collaboration – enabling collaboration between city and stakeholders
2) Participation – enabling participation of residents and developers
3) Communication – enable better policy outcomes through publication of
relevant data
4) Data exchange – Enabling data sharing among city authorities and
network of cities
5) Service and application integration – to provide software development
tools (e.g. CitySDK) to build OD-based applications

Data Ecosystem
Specific datasets that are associated with major SCs
domains – number of datasets include in the ff sectors:
1) Transport and Mobility – OpenStreetMapdata,
CurrentCarParks…
2) Health and wellbeing – UKFoodHygiene,
DrugTreatmentStatistics…
3) Environment and safety – FloodMap, EnergyUsage…
4) Education – CookCOunty, AdultEducation…
5) Tourism – Cultural and Leisure…
More focus on Transport and mobility as well as Environment and safety
datasets, which are both characterised as innovation cluster data.

Stakeholders
“Open Data Ecosystems in these cities have the active
participation of residents, different city authorities,
software developers, and SMEs in providing, curating and
consuming the datasets … ”
Participation of non-technical stakeholders are minimal –
“token”

Major Issues
Two significant issues:
1) Cities-> “Open Innovation Economies”
Emerging 2nd generation open data based smart city
initiatives are redefining the respective cities as “Open
Innovation Economies”. This is significantly different from
the emphasis of first generation initiatives which are
strongly linked to physical environment and infrastructure.
1) Need-driven open data initiatives in smart cities such as
those described earlier are exceptions

Conclusion
1) There are still huge potentials and gaps on how open data
can impact smart cities aspects. In particular, need driven,
stakeholder-led data driven innovation programs are still
relatively few.
2) There are currently no rigourous model to fully analyse
this opportunity gap. We are currently investigating such
models.
3) Interviews and discussions with City Managers and Open
data program officers in cities may explain and identifies
barriers to need-driven approaches in open data projects in
smart cities.

Emerging Open Data Business
Model
Fatemeh Ahmadi-Zeleti
Insight Centre for Data Analytics
National University of Ireland, Galway (NUIG)
fatemeh.ahmadizeleti@insight-centre.org

Business Model
A business model describes how value is created and
captured by an organization through the decisions
made and the resulting consequences
A business model is a conceptual tool that contains a
set of inter-related elements that allows a company
to generate money
It comprises a description of the value a company offers
to one or several segments of customers, the
architecture of the firm, and its network of partners
for creating and delivering this value in order to
generate profitable and sustainable revenue streams

Business Model Cont.
Shafer, Smith and Linder Business
Model

Hamel Business Model

Kamoun Business Model
Basic building blocks of a business model and the external
forces that have an affect on these blocks
http://cdn.intechopen.com/pdfs-wm/18084.pdf

Osterwalder and Pigneur Business
Model
https://www.youtube.com/watch?v=QoAOzMTLP5s http://dl.acm.org/citation.cfm?id=2612745

Open Data Business Model (ODBM)
• The demand for Open Data is increasing the idea
for businesses to use Open Data to generate
value and revenue
• Utilizing Open Data can help companies improve
the productivity of current business processes
and can lead to new products, services
• ODBM should be designed and developed
accordingly so that businesses can generate
value and revenue from utilizing Open Data

15 ODBMs
Freemium: Offering is given for free
Premium: Offering is high end products and services and customer willing to use the
offer has to pay
Dual Licensing: [open source + proprietary licenses] Offering is provided as open
license for certain purposes and under a closed license for others
Support and Services: Offer is provided in a full package with complete support and
service of the business. E.g. Availability, bug fixing, etc.
Charging for Changes: Charges applied for changes in the offer
Increasing Quality through Participation: Increasing integration and participation of
the customer is a new organizational choice aimed at generating higher margins
Supporting Primary Business: Releasing an offer naturally supports the primary goal
of a business or organization
Demand-Oriented Platform: Charging for demand side of the offer [charging developers
the added value such as advanced services and refined datasets or data flows
provided upon the original raw open data] http://dl.acm.org/citation.cfm?id=2612745

15 ODBMs cont.
Supply-Oriented Platform: Charging for the supply side of the offer [presence of an
intermediary business actor having an infrastructural role]
Open Source: The offer if provided in a complete open format [all source codes are open]
Sponsorship: Offer is provided for free to customers and obtaining revenue from some
sponsors
Infrastructural Razor & Blades: Selling a product for a low price in order to generate
revenues from the complementary products
Cost avoidance: Reducing the cost of production [reduces the cost of data publishing by
having a sustainable publishing solution. same data to be published a number of times
and in different formats]
Free, as Branded Advertising: Generate revenue from strong brand advertising [Business
delivers commercial messages through visualized data which is also called “display
advertising”]
White-Label Development: Offer is developed by one business and is sold to other business
with white-label

ODBM Conceptual Model

ODBM Main Components
Value Proposition
Offer
Channel
Value
Knowledge
Management
Value Adding
Process
Strategic Operational
Value in Return
Volume of Sale
Income
Future
Opportunity
Value Network
Actors
Support
Infrastructure
Value Management
GovernanceAdministrationStructure Discipline
Value Capture
Profit Model Market Size

ODBM Components

ODBM Patterns [15 to 5]
• Freemium
“Freemium”, “DualLicensing”, “Charging for Changes”,
“Open Source”, and “Free as Branded Advertising”
models
[offer limited data free of charge and apply fees for
additional request]
• Premium
“Sponsorship”, “Support and Services”, “Demand-
Oriented Platform”, “Supply-Oriented Platform”, “White-
Label Development” and “Premium” models
[data is not offered free of charge]

ODBM Patterns [15 to 5] cont.
• Cost Saving
“Increase Quality through Participation” and “Cost
Avoidance” models
[Models reduce cost of opening and releasing data]
• Indirect Benefit
“Supply Primary Business” model
[Offer naturally supports the primary goal of the business]
• Razor-Blade
“Infrastructural Razor and Blades” model
[Incomplete offer at a discount and complementary offer at
a higher price]

Open Data Business Value Disciplines
• Usefulness: tailors value proposition of the business to
meet usefulness of the business offer
• Process Improvement: tailors value proposition to
match to the needs of the customer for improving
processes
• Performance: tailors value proposition for a better
performance
• Customer Loyalty: tailors value proposition to target
customer loyalty

ODBM Patters and Value Disciplines

Conclusion
• All businesses MUST employ particular Business Model
• Open Data businesses MUST design, develop and sustain
particular (combination of) ODBM/s
• Before identifying Business Model, value discipline MUST be
identified
• ODBM patterns and value disciplines SIGNIFICANTLY AID
business to effectively deliver value to the stakeholders and
generate revenue

Thank You
@fatemehahmadi_
fatemeh.ahmadizeleti@insight-cenre.org

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