Lecture week 5 -

Open Data-Driven Innovation

and Smart Cities

Fatemeh Ahmadi-Zeleti

Insight Centre for Data Analytics

National University of Ireland, Galway (NUIG)

[email protected]

@fatemehahmadi_

Open DataData 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

http://www.worldbank.org/content/dam/Worldbank/Feature Story/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


https://www.youtube.com/watch?v=PzWpcVzuwV0


Open Data-Driven

InnovationData 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

PlanningData 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 ServicesData 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

MarketingBusinesses can radically improve

cost efficiencies and market

agility through the data they

capture about their processes

and products.

e.g. Amazon

Open Data-Driven

OperationsData 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.



Open Data Innovation Ecosystem:

World Bank

https://www.youtube.com/watch?v=07LFJYB2o3I


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/

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

https://www.youtube.com/watch?v=HgPx_TuF-Js

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)

[email protected]

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 streamshttp://dl.acm.org/citation.cfm?id=2612745


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

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

https://www.youtube.com/watch?v=QoAOzMTLP5s


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-labelhttp://dl.acm.org/citation.cfm?id=2612745


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

@[email protected]

Lecture week 5 -

Documents

open data cont

development data

kind of data

open data innovation

world banks open data

open datadata

kind of innovation

rates of innovation