06877 Topic Implicit Association TestNumber of Pages 1 (Doub.docx

06877 Topic: Implicit Association Test
Number of Pages: 1 (Double Spaced)
Number of sources: 4
Writing Style: APA
Type of document: Research Paper
Academic Level:Master
Category: Psychology
Language Style: English (U.S.)
Order Instructions: Instructions Attached
Take one (gender, age, race, sexuality, disability, or weight) of
the Implicit Association Tests (IAT) at the Harvard University
website.
Examine how attitude is formed.
Discuss how personal implicit biases can form understandings at
a local, national or global level.
Analyze the strengths and weaknesses of the IAT as a research

tool.
Reflect on your personal results from the IAT.
Use three to five scholarly sources to support your thinking,
your textbook can be used as one of the resources.
Prepare this assignment according to the guidelines found in the
APA Style Guide, located in the Student Success Center. An
abstract is not required.
This assignment uses a rubric. Please review the rubric prior to
beginning the assignment to become familiar with the
expectations for successful completion.
84 September/October 2012 Published by the IEEE Computer
Society 0272-1716/12/$31.00 © 2012 IEEE
Graphically Speaking Editor: Miguel Encarnação
Toward Visualization in Policy Modeling
Jörn Kohlhammer, Kawa Nazemi, Tobias Ruppert, and Dirk
Burkhardt
Fraunhofer IGD
Information visualization and visual analytics (VA) have
become widely recognized research fields applied to a variety of
domains and
data-related challenges. This development’s main
driver has been the rapidly increasing amount of
data that must be dealt with daily. Virtually every
industry or business, or any political or personal
activity, generates vast amounts of data. At the
same time, citizens, shareholders, and customers

expect highly efficient, informed decision-making
based on increasingly complex, dynamic, and in-
terdependent data and information.
All this applies in many ways to public-policy
modeling. As the recent financial crisis has shown,
policy making and regulation are highly challeng-
ing tasks. The outcomes of policy choices and in-
dividual behavior aren’t easily predictable in our
complex society. Ubiquitous computing, crowd-
sourcing, and open data, to name just a few exam-
ples, are creating masses of data that governments
struggle to make sense of for policy modeling.
Increasingly, policy makers are perceiving vi-
sualization and data analysis as critical to this
sense-making process. Current practice uses visu-
alization mainly during postprocessing. Although
this is an important step in the right direction,
a more promising trend is the integration of vi-
sualization tools with simulation and automated
analysis. This is clearly in line with the general
approach employed by various domains that apply
VA techniques for interactive analysis.
Here, we examine the current and future roles
of information visualization, semantics visualiza-
tion, and VA in policy modeling. Many experts
believe that you can’t overestimate visualization’s
role in this respect. For example, the recent EU
roadmap for this area goes as far as saying that
“ensuring appropriate visualisations can … be con-
sidered a key component of a mature democracy.”1
The Policy-Making Process
Policies are usually defined as principles, rules, and

statements that assist in decision-making and that
guide the definition and adoption of procedures
and processes. Typically, government entities or
their representatives create public policies, which
help guide governmental decision-making, legisla-
tive acts, and judicial decisions.
Some policy-modeling research emphasizes theo-
retical formal modeling techniques for decision-
making, whereas some applied research focuses on
process-driven approaches. These approaches de-
termine effective workflows through clearly defined
processes whose performance is then monitored
(for example, as in business process modeling).
This applied-research approach is widely seen as
one way to effectively create, monitor, and opti-
mize policies. One aspect of process-driven policy
making is the clear definition of the sequence of
steps in the process. This ensures the consider-
ation of the most relevant issues that might affect
a policy’s quality, which is directly linked to its
effectiveness.
Ann Macintosh published one of the most
widely used policy-making life cycles; it comprises
these steps:2
1. Agenda setting defines the need for a policy or
a change to an existing policy and clarifies the
problem that triggered the policy need or change.
2. Analysis clarifies the challenges and opportuni-
ties in relation to the agenda. This step’s goals
are examining the evidence, gathering knowl-
edge, and a draft policy document.

3. Policy creation aims to create a good workable
policy document, taking into consideration a
variety of mechanisms such as risk analysis or
pilot studies.
4. Policy implementation can involve the develop-
ment of legislation, regulation, and so on.
5. Policy monitoring might involve evaluation and
review of the policy in action.
The entire life cycle is a loop.
IEEE Computer Graphics and Applications 85
Other, more specific process definitions are avail-
able, but these often vary significantly. Depending
on the domain—for example, in the social sciences
versus in computer science—the definition has dif-
ferent scopes and thus very different process steps.
For adopting visualization in policy making, we
simplified the general model and introduced three
iterative stages (see Figure 1):
1. Information foraging supports policy definition.
So, this stage requires visualization techniques
that obtain relations between aspects and
circumstances, statistical information, and
policy-related issues. Such visualized informa-
tion enables optimal analysis of the need for
a policy.

2. Policy design must visualize the correlating top-
ics and policy requirements to ensure a new
or revised policy’s functional interoperability.
3. Impact analysis evaluates the designed policy’s
potential or actual impact and performance,
which must be adequately visualized to support
the policy’s further improvement.
All phases involve heterogeneous data sources to
allow the analysis of various viewpoints, opinions,
and possibilities. Without visualization and inter-
active interfaces, handling of and access to such
data is usually complex and overwhelming because
too much data is available. The key is to provide
information in a topic-related, problem-specific
way that lets policy makers better understand the
problem and alternative solutions.
Today, many data sources support policy model-
ing. For example, linked open government data ex-
plicitly connects various policy-related data sources
(for instance, see http://data.gov.uk/linked-data).
Linked data provides type-specific linking of infor-
mation, which facilitates information exploration
and guided search to get an overview and—later
on—a deeper understanding of a specific topic.
Massive, multidimensional databases for statisti-
cal data also exist—for example, the EuroStat data-
base (http://epp.eurostat.ec.europa.eu).
Currently, policy-modeling approaches don’t use
visualization intensively either for the general pro-
cess or in any of the three stages. The first research
prototypes are close to traditional information
visualization techniques, and no visualization ap-

proach addresses all the required policy-modeling
aspects. As we mentioned before, the goal of intro-
ducing more visualization and VA techniques goes
one level further. The objective is to ensure more ef-
ficient and effective policy modeling by integrating
visual methods and automatic analysis methods.
Visual Support for Policy Modeling
The simplified policy-modeling process in Figure 1
enables an abstract view of policy evolution. This
model can provide only an overview of the stake-
holders, political processes, and activators for new
or changed policies. Nevertheless, it gives a good
foundation for identifying the application of in-
formation and communications technology (ICT)
to policy creation. In particular, graphical systems
that give insight into the heterogeneous, complex,
and huge amount of data and information can be
adapted to the model’s stages.
Here, we look at various visualization disciplines
in this context and classify visualization method-
ologies on the basis of the human’s and computer’s
roles in the transformation from data to insight.
In this process, visualization supports users in var-
ious ways. One example is integrated intelligence
that recognizes patterns or clusters in data or that
considers human abilities or interaction patterns
when providing adaptive visualization techniques.
In this context, we categorize visualization for
policy modeling into information design, infor-
mation visualization, semantics visualization, VA,
and knowledge discovery in databases (KDD).
Figure 2 illustrates this separation of roles, in
which the computer’s role increases and the hu-

man’s role decreases from left to right. For example,
Information
foraging
Policy design Impact analysis
Figure 1. A simplified policy-modeling process. All three stages
involve
heterogeneous data sources to allow the analysis of various
viewpoints,
opinions, and possibilities.
Information
design
Information
visualization
Human
Computer
Visual
analytics
Knowledge
discovery in
databases
Semantics
visualization
Figure 2. The computer’s and human’s roles in visualization
disciplines in
policy modeling.3 From left to right, the computer’s role

increases and
the human’s role decreases.
86 September/October 2012
Graphically Speaking
in information design, the computer plays no role
per se, whereas in KDD, automatic methods process
the underlying data typically without user interac-
tion. We consider semantics visualization very rel-
evant for policy modeling, as we explain later.
Information Design
Political decisions often progress through stages
involving stakeholders with heterogeneous skills,
knowledge and preferences, and positions in the
political chain. The actual decision-making often
occurs higher on that chain, with lower-level dis-
cussions or workshops taking analysts’ input into
account to help determine policy changes. At this
lower level, the data and information should be
presented adequately. The main target is to con-
vey a matter of interest and present the essential
issues.
Information design investigates the rules for ad-
equate information presentation and the commu-
nication of knowledge. Here, humans with their
communication skills are the major actors and use
outcomes from perception science. Information
design focuses on visualization to support human
communication during policy making.

Information Visualization
To achieve a summary of the most important data
and information relevant for decision-making,
political analysts must aggregate vast amounts of
data, analyze it, and form an overview of it. For
these tasks, they can apply information visualiza-
tion techniques. Often, automatic analysis prepro-
cesses the data, and the analysts usually visualize
only these techniques’ outcomes. The analysts can
visually and interactively browse through the re-
sults and detect the most relevant information to
condense for decision-makers.
Every stage of policy modeling can involve in-
formation visualization. For example, information
foraging could use Gapminder (www.gapminder.
org) to explore the evolution of a nation’s wealth
to analyze the need for new policies.
Semantics Visualization
The increasing amount of semantically annotated
open data, especially in the area of linked govern-
ment data, justifies investigating semantic tech-
nologies for visualization related to policy making.
Semantic-technology research focuses on data’s
machine readability, whereas semantics visualiza-
tion focuses on human-centered approaches for
conveying information. Semantics visualization
goes beyond ontology visualization, which focuses
on visualizing a formal knowledge description in
a certain domain. It provides a comprehensible,
interactive view of semantics.4
In visualization, semantics is the meaning-
ful relation between two or more data entities.

These relations can be described explicitly by for-
mal semantic languages (for example, OWL—Web
Ontology Language) or gathered implicitly with
semantic-mining methods. With the ability to
correlate linked government data to data from do-
mains unrelated to politics, analysts can find new
relations and visualize them for decision-makers.
Semantics visualization is applicable to all three
stages of our simplified policy-making model. In-
formation foraging can employ the search, explora-
tion, and decision-support methods we’ve described.
Policy design can employ semantically structured
policy formalisms and visual authoring environ-
ments. Impact analysis can employ logical infer-
ences, predicate logic, and fuzzy cognitive maps to
provide a comprehensible comparison of scenarios.
Visual Analytics
For complex analysis tasks—for example, during
impact analysis—political analysts might have to
incorporate complex algorithms and deal with vast
amounts of data. Political analysts can’t be ex-
perts in every computational discipline that might
contribute to the analysis. So, interactive visual
displays could help them access the complex com-
putational models.
VA exactly addresses this problem by combining
computers’ data-processing capabilities with the
strength of humans’ visual perception. On the one
hand, computers process vast amounts of data for
aggregation, structuring, or summarization. This
provides users with intuitive visual access to the
data. On the other hand, users can visually detect
interesting patterns in visualizations and can con-

trol computers to get a more precise analysis. So,
VA can help political analysts incorporate complex
ICT into policy making.
KDD
VA strongly involves KDD techniques because it
employs interactive visual displays to control and
use automatic data analysis tools. KDD uses vi-
sualization techniques only in restricted ways—for
example, in GUIs to set automatic analysis tech-
niques’ parameters.
Researchers are already applying KDD tech-
niques to policy making, especially during infor-
mation foraging and impact analysis. For example,
a large KDD community focuses on automatically
extracting public opinions from the Web. A VA ap-
proach would couple visualization techniques with
such KDD techniques to directly involve policy
makers in opinion analysis.
Two Use Cases for Policy Modeling
Two European Commission-funded projects that
focus on integrating visualization into policy mod-
eling are ePolicy and Fupol.
ePolicy
The ePolicy (Engineering the Policy-Making Life
Cycle; www.epolicy-project.eu) project aims to
provide a decision-support system for policy mak-
ers. To do this, the project is engineering a policy-

making life cycle for regional energy planning. The
life cycle will bring to policy makers’ attention
both global concerns (for example, regional en-
ergy incentives’ impacts, budget constraints, and
objectives) and individual concerns (for example,
opinions and reactions), guiding them toward bet-
ter policy implementation.
Technically, ePolicy integrates these perspectives
through global-level optimization, individual-level
social simulation, game theory for managing con-
flicts and regulating the interaction between these
two levels, and opinion mining (see Figure 3). The
project’s goals are to uniquely combine these re-
search areas and provide intuitive visual-interactive
access to the underlying techniques.
The project integrates information visualiza-
tion and VA into policy making, especially during
policy design and impact analysis. It uses infor-
mation visualization mainly to visualize the vast
amounts of data generated by automatic analysis
tools such as opinion mining or social simulation.
It closely connects VA tools to these analysis tools
to set parameters and interactively control them
for advanced impact analysis.
This project uses visualization techniques partic-
ularly to make complex analysis processes accessible
for political analysts supporting decision-makers
who are setting political agendas.
Fupol
Fupol (Future Policy Modeling; www.fupol.eu), a
four-year project that started in late 2011, will

integrate multichannel social computing, crowd-
sourcing, and semantics visualization into political
decision-making. It will consolidate heterogeneous
technologies into a core system, which will auto-
matically collect, analyze, interpret, and visualize
opinions expressed on the Internet. This will en-
able governments to gain a better understanding
of citizens’ needs. A new governance model will
support policy design and implementation. The
approach is based on complexity science; it aims
to reduce complexity through a spiral life cycle for
policy design that’s appropriate for complex soci-
etal problems.
Visualization
Global-level
optimization
Policy-making
life cycle
Policy
scenarios
E-participation
Postevent
opinion mining
Pre-event
opinion mining
Game theory
interaction

Equilibrium
point
Implementation
strategies
Individual-level
simulation
Figure 3. The policy-making life cycle in the ePolicy project,
which aims to provide a decision support system
for policy makers.
88 September/October 2012
Graphically Speaking
The policy design cycle will follow the three stages
in Figure 2. Information foraging will apply seman-
tics and information visualization to support new
policy requirements and changes. Furthermore, Fu-
pol will use opinion mining and analysis to gather
information on information transparency and vi-
sualize it for politicians and citizens. This stage
will consider using data from the linked-open-
data initiative and other social and semantics data
sources for visualization. Usage behavior analysis
will be important in this stage. The visualization
methods (see Figure 4) will be able to automati-
cally adapt the visual structure, visual complexity,
and data to be visualized to stakeholders’ abilities
and interests.5
Policy design will employ process-driven visualiza-

tions. Users’ observed usage patterns will be analyzed
to dynamically adapt functionalities and user guid-
ance in a policy creation workflow that’s strongly
supported by visualizations and simulations.
In impact analysis, semantics visualizations will
employ predicate and fuzzy logic to visualize a
policy’s impact.
The project is at an early stage that focuses on
requirements analysis with the participating cities.
Its outcomes will include the governance model,
a policy knowledge database, an ICT framework
based on cloud computing, and pilot applications
for several European cities and one Chinese city.
The European Commission is investing heav-ily in policy-
modeling research through the
ICT for Governance and Policy Modeling initia-
tive. The Crossroad (http://crossroad.epu.ntua.gr)
project has set the tone for various projects in this
area, such as ePolicy and Fupol. For the visualiza-
tion and VA aspects, Crossroad has relied on the
European VA research roadmap that the VisMaster
coordination project presented in 2010.6 To create
this roadmap, VisMaster pulled together European
VA experts; the project also had links to a roadmap
written in the US and Canada.
The EU projects on governance and policy mod-
eling have just started; it will be interesting to
see how far they can introduce visual elements to
policy modeling. For example, the European FET
(Future & Emerging Technologies) Flagship Initia-
tives (http://cordis.europa.eu/fp7/ict/programme/

fet/flagship/home_en.html) include the FuturICT
pilot project, which brings together ICT research,
complex-systems research, and the social sciences.
Figure 4. Semantics visualization for political information
analysis. The figure illustrates the SemaVis
visualization framework4 in the information-foraging phase of
policy modeling. Using semantics enables the
visual abstraction of information in categories, the visualization
of relations and dependencies of information
entities, and geographic and time-related correlations. (Source:
Fraunhofer IGD; used with permission.)
One goal is to give governments and citizens much
more capable tools for policy modeling and policy
analysis, including a strong visual component.
Similar projects are under way elsewhere, es-
pecially in Canada and the US. One example is
Vaccine (Visual Analytics for Command, Control,
and Interoperability Environments; www.purdue.
edu/discoverypark/vaccine), a US Department of
Homeland Security Center of Excellence that’s
using VA to enhance policy modeling for public
safety and public health.
All these initiatives point in one common direc-
tion: visualization and VA are vital for informed
decision-making and policy modeling in a highly
complex information environment overloaded with
data and information. We expect that policy mod-
eling will be a common application domain in

upcoming US and European visualization confer-
ences. In the end, it might determine not only our
policy makers’ efficiency and proficiency but also
citizens’ involvement and confidence in future
policy modeling.
References
1. Crossroad—a Participative Roadmap for ICT Research
in Electronic Governance and Policy Modeling, tech. re-
port, 2010; http://crossroad.epu.ntua.gr/files/2010/
02/CROSSROAD_D4.3_Final_Roadmap_Report-v1.
00.pdf.
2. A. Macintosh, “Characterizing E-participation in
Policy-Making,” Proc. 37th Ann. Hawaii Int’l Conf.
System Sciences (HICSS 04), IEEE CS, 2004.
3. D.A. Keim et al., “Event Summary of the Workshop
on Visual Analytics,” Computers and Graphics, vol.
30, no. 2, 2006, pp. 284–286.
4. K. Nazemi, C. Stab, and A. Kuijper, “A Reference
Model for Adaptive Visualization Systems,” Human-
Computer Interaction: Design and Development Ap-
proaches, vol. 1, J.A. Jacko, ed., LNCS 6761, Springer,
2011, pp. 480–489.
5. P. Sonntagbauer, “Fupol at a Glance,” Dec. 2011;
www.fupol.de/?q=node/6.
6. D.A. Keim et al., Mastering the Information Age:
Solving Problems with Visual Analytics, Eurographics
Assoc., 2010.

Jörn Kohlhammer is the head of the information visualiza-
tion and visual analytics department at Fraunhofer IGD.
Contact him at [email protected]
Kawa Nazemi leads the Semantics Visualization group
at Fraunhofer IGD. Contact him at [email protected]
fraunhofer.de.
Tobias Ruppert is a researcher in the information visual-
ization and visual analytics department at Fraunhofer IGD.
Contact him at [email protected]
Dirk Burkhardt is a researcher at Fraunhofer IGD. Con-
tact him at [email protected]
Contact department editor Miguel Encarnação at
[email protected]
computer.org.
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HOW IT ALLOWS E-PARTICIPATION IN POLICY-MAKING
PROCESS 1
How IT allows E-Participation in Policy-Making Process
Sourav Mukherjee

Senior Database Administrator &
PhD student at University of the Cumberlands
Chicago, United States
PROCESS 2
Abstract
With the art and practice of government policy-making, public
work, and citizen participation,
many governments adopt information and communication
technologies (ICT) as a vehicle to
facilitate their relationship with citizens. This participation
process is widely known as E-
Participation or “Electronic Participation”. This article focuses

on different performance
indicators and the relevant tools for each level. Despite the
growing scientific and pragmatic
significance of e-participation, that area still was not able to
grow as it was expected. Our diverse
set of knowledge and e-participation policies and its
implementation is very limited. This is the
key reason why e-participation initiatives in practice often fall
short of expectations. This study
collects the existing perceptions from the various
interdisciplinary scientific literature to
determine a unifying definition and demonstrates the strong
abilities of e-participation and other
related components which have great potential in the coming
years.
Keywords: E-participation, e-governance, Citizen, e-
democracy, public-work, ICT tools, e-
empowerment, e-engaging, technical tools, duality of e-
Participation, levels of participation.
PROCESS 3

How IT allows E-Participation in Policy-Making Process
In this information-age, led by Internet content, resources,
innovation in software and
technology and interdependence to multiple other systems in
getting the society changed. E-
participation, E-Governance, ICT tools, e-empowerment, e-
engagement are the interrelated
concepts or models help us effectively manage, participate,
govern and pursue the public work.
Regardless Of the omnipresence of e-Participation programs,
endeavors of social media-centered
and citizen-guided political discussions are extremely limited.
Therefore, there lies a very little
chance to control, study and realize the desired debate regarding
the traditional e-Participation
and a free or natural citizen debate on the social media
platforms. Currently, the interest has
made a radical shift towards harnessing the informal channels
part of the universal e-
Participation solution. Still, the unspoken belief of the duality
of e-Participation is yet to be

studied, investigated and hypothesized. To implement such
“duality of e-Participation”, requires
a robust social software foundation to empower decision makers
in getting access to the
government entrance relevant resources regarding the
continuing citizen debates on the social
media platforms.
Literature Review or Background
In the last couple of decades, a steady need to consider the
innovative application of ICTs have
been evolved to play a part that may enable the broader
audience to participate to independent
debate, the places where the roles are wider, broader and
deeper. This understanding has
stemmed in several secluded e-democracy guides and research
studies. It is crucial to strengthen
this work and distinguishes the degree of participation, the
technology utilized, the phase in the
PROCESS 4

policy-making process and numerous issues and restrictions,
including the possible benefits. E-
democracy is widely used in the ICT model to support and
encourage democratic decision-
making processes. In a few countries, e-democracy is used
synonymously used with e-voting.
However, the voting process is just a subset of the entire E-
democracy process. Voting is not
only the only criteria through which the citizens can impact the
policy-making or the decision-
making process. Rather e-democracy may be further divided
into two separate areas such as e-
participation and the other is e-voting. E-Voting has been
identified to go under many challenges
and difficulties, whereas the e-participation has a greater
prospect with regards to discussion and
dialogue between the government, policymakers and the
citizens. In many countries, the election
process is a concern to a high intensity of risk, whether it
includes tampering with the voting
machines, dishonest vote kiosks/booths, or merely hiding the
vote arrangement process of
supervision and public inspection. Nowadays because of the

advancement in software process,
hiding malware in the voting device is no way a difficult task.
Tampering with the voting results
are far easier and will continue to rise over a period such issue.
The malware deployed may have
an algorithm which can efficiently change the votes from one
candidate to the other and that may
do its job very easily without being noticed by the others.
Hence it requires a malware detector to
quickly identify if the voting machine is free from any such
scrupulous software. It has been
observed that most of the time the security improvements are
driven by any kind of breaches and
hence it requires policymakers, government agencies, and
security professionals to work together
to identify a better option to handle such issues. Due to this
reason, e-voting is not preferred. On
the other hand, when it comes to the e-participation there is a
large magnitude of government,
corporations using technology and expertise to provide access
to policy information. While some
governments and study centers have already carried out several
surveys in this area and explored

PROCESS 5
that there is no single approach to describe the problem and
detailing the outcome. Therefore e-
democracy is involved with the use of information and
communication technologies (ICT) to
connect citizens supporting the independent decision-making
practices and improving the
representative republic. The primary ICT method is the internet-
based approach, including
computers used in the home, office or in public locations,
mobile phones, and television. The
self-governing decision-making processes can be separated into
two major groups: one focus on
the electoral process, involving e-voting, and the other adopting
citizen e-participation in
independent policymaking.
Discussion
e-governance is the product of information and communication

technology (ICT) for providing
government public services, information exchange,
communication operations, incorporation of
various systems and services to customers or to other
businesses. This is nothing but governance
in an electronic environment using electronic media and tools.
Generally, the goals of the e-Governance are:
Serving the citizens through a better model
Leading towards transparency and accountability.
Enhance efficiency within government
Develop suitable connectivity between business and industry.
Due to the growing use of computers, Internets, smartphones,
changes our lifestyle and the way
we undertake and execute any work, learn and respond. Around
the world, governments are

PROCESS 6
started to realize the benefits of the value of e-governance. If
this is designed and implemented
appropriately, the e-governance process can greatly benefit the
people in terms of delivering
high-quality government services, simplifying the government
regulations, improving the citizen
participation, creating an enabling trust in the government, and
so on. For that reason,
policymakers and other officials are looking to implement e-
Government in countries around the
world.
Regarding e-empowerment, e-petitions and e-referenda are two
possible ways for the collection
of citizen opinions and remarks to control policy. The
expansion of online populations of
interest, in which certain policy concerns are debated and
different proposals are devised all over
again based on discussion forums, are also some instances of
empowerment online.
One of the most common ways to empower citizens are E-

empowering. In this policy-making
process, citizens are involved with encouraging active
involvement and assisting bottom-up
proposals to sway the political agenda. Since the bottom-up
viewpoint, citizens are evolving as
producers instead just users of the policy.
Therefore, I think that the levels of participation do include
enabling, engaging, and
empowering.
Stages in the policy-making process are very complicated as it
involved multiple parameters as
defined in the below picture to know when to engage the
citizens,
• Setting Agenda – identify the problem which we need to
address.
• Analysis – define the possible challenges and if there any
opportunities associated with
the agenda.
• Create policy – create a good workable policy document.
• Implementation – create a solid delivery plan.

PROCESS 7
• Policy monitoring – involves evaluation and review of the
policy.
Setting Agenda
Policy
Monitoring
Analysis
Implementation Create policy
Figure 1. Stages in the Policy-making process
ICT offers the flexibility to policy-makers to reach directly to
the users who are using the
services. Essentially citizens have more influence on policy
matter through discussion before

then the policy-making procedure kicks in. Consultation at the
phase of an outline policy
document involves citizens to have the communication skills to
understand the usual legalistic
terminology of the document before commenting appropriately.
Citizens are required to be well-
informed on issues before the above stage is reached and the
information must be more accurate,
readable and understandable.
ICT can promote empowerment, involvement and getting
government processes more effective
and understandable by sharing information and communication
among the people and
organizations within the government. Even governments can
improve on the quality and
awareness of the services they provide to the citizens and
increase the availability of the services
and the infrastructure.
PROCESS 8

This is enabled by e-government applications over the Internet
and other communication
networks that deliver services and information to people. ICT
can bind people and local groups
with information and resources outside their geographical
limits, inspiring information
distribution, knowledge exchange, data, and communication.
ICT also encourage the citizens to
participate in the democratic process in the form of electronic
forums and bulletin boards which
facilitate participation in the public conversations. To control
political and influential decision-
making processes, the organizations in the developing nations
like to participate in the
information-sharing process that improves governance and
collective energy. Even Though
people and organizations can efficiently use ICT to enhance
their information exchange and
communications, robust leadership and executive resources are
required to turn information into
organized engagement.
e-participation Tools and Techniques

Because of the versatility of the nature of the tools and
technologies, most of the tools, and the
variety of actors in the participation process, it is challenging to
identify and realize the
connections between citizens and technology. Such element
measures how members are
involved, and which devices will be possible to help
involvement efficiently.
Electronic participation services through ICTs should be
positioned at the center of the e-
participation process as they form the principle of e-
participation. Investigating such tools is
deemed a shred of convincing evidence for the significance of
the ICT tools in the achievement
of e-participation developments.
PROCESS 9
In the 2000s the European Commission (EC) financed numerous
e-participation projects under
the e-participation foundation act, the organizing of ICT, its

experience, and the newest
developments in an online collaboration were the common
features of the most popular projects.
Sobaci has established a framework for the applicable ICT tools
according to the various e-
participation’s purposes and the attributes desired to achieve
these intentions, also Phang and
Kankanhalli suggested another framework that offered five
ideas of e-participation and the finest
ICT tools to achieve them. One More framework was proposed
by Abu-Shanab and Al-Dalou’
that contained three levels and the appropriate technical tools
necessary for every level.
Furthermore, they recommended a catalog of performance
statistics linked to every level of e-
participation.
Conclusions and Future Study
E-Government is about finding another useful way in which
governments work together with the

citizens, administrative agencies, companies, workers, and other
participants. It enhances the
democratic process and new proposals to create life simpler for
people. The research area of e-
Government is wide, extensive and small, and several scholars
are engaged in various study
projects in numerous issues in the area. The difficulty of e-
participation practices findings from
the multi-specialties included in this area. A general
understanding was laid out about different
electronic policy-making terminologies and their veracity of
uses. Finally, more research is
necessary for further awareness, knowledge, and understanding
of such growing area, to
concentrate on the significance of mobile involvement and
social practices as two indispensables
PROCESS 10
tools for the government to improve the involved political
practices between the governments
and the citizens. While defining the potential of democracy,

governance and public work at the
beginning of the information age is an amazing opportunity and
responsibility. With the smart
and efficient use of ICTs and in combination with democratic
intent, we can create governments
more approachable. We can also unite citizens to efficiently
encounter public challenges, and
eventually, we can build a more workable future for the
advantage of the entire society and realm
in which we live.
References
[1] Macintosh, A. (2004). “Characterizing E-Participation in
Policy-Making”, in Proceedings of
the 37th Hawaii International Conference on System Science –
2004. IEEE.
[2] Clift, S. (2003). E-democracy, e-governance and public net-
work. Artículo en línea].
Publicus. Net.
[3] Slaviero C, Maciel C, Alencar F, Santana E, Souza P (2010)
Designing a platform to
facilitate the development of virtual e-participation

environments. Paper presented at the
ICEGOV ’10 proceedings of the 4th international conference on
theory and practice of
electronic governance, Beijing.
[4] Phang CW, Kankanhalli A (2008) A framework of ICT
exploitation for e-
participation initiatives. Commun ACM 51(12):128–132.
[5] Furdík K, Sabol T, DulinováV (2010) Policy modelling
supported by e-participation ICT
tools. In: MeTTeG’10. Proceedings of the 4th international
conference on methodologies,
technologies and tools enabling e-government. University of
Applied Sciences, Northwestern
Switzerland, Olten (pp 135–146).
[6] Maragoudakis M, Loukis E, Charalabidis Y (2011) A review
of opinion mining methods for
PROCESS 11
analyzing citizens’ contributions in public policy debate.
Proceedings of IFIP 3rd international

conference on e-participation—ePart 2011, August 29–
September 1, 2011, Delft, The
Netherlands.
[7] Butka P et al (2010) Use of e-Participation tools for support
of policy modelling at
regional level. The 5th Mediterranean conference on
information systems, September 12–14,
Tel Aviv Yaffo, Israel. http://web.tuke.sk/fei-
cit/Butka/publications.html. Accessed 24 Jan
2014.
[8] Mukherjee, S. (2019). Popular SQL Server Database
Encryption Choices. arXiv preprint
arXiv:1901.03179.
[9] Mukherjee, S. (2019). Benefits of AWS in Modern Cloud.
arXiv preprint arXiv:1903.03219.
[10] Sobaci, Z. (2010). What the Turkish parliamentary web site
offers to citizens in terms of
eparticipation: A content analysis. Information Polity: The
International Journal of Government
& Democracy in the Information Age, 15(3), 227-241.
[11] Phang, C., & Kankanhalli, A. (2008). A Framework of ICT

Exploitation for E-Participation
Initiatives. Communications of the ACM, 51(12), 128-132.
[12] Abu-Shanab E. & Al-Dalou’, R. (2012). E-participation
Initiatives: A Framework for
Technical Tools, Accepted and will be presented in the 2012
International Arab Conference of
e- Technology (IACe-T'2012), 57-64.
[13] Bernd W. Wirtz, Peter Daiser & Boris Binkowska (2018)
E-participation: A Strategic
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41:1, 1-
12, DOI: 10.1080/01900692.2016.1242620.
AUTHOR’S PROFILE
Sourav Mukherjee is a Senior Database Administrator and Data
Architect based out of Chicago.
He has more than 12 years of experience working with
Microsoft SQL Server Database

PROCESS 12
Platform. His work focusses in Microsoft SQL Server started
with SQL Server 2000. Being a
consultant architect, he has worked with different Chicago
based clients. He has helped many
companies in designing and maintaining their high availability
solutions, developing and
designing appropriate security models and providing query
tuning guidelines to improve the
overall SQL Server health, performance and simplifying the
automation needs. He is passionate
about SQL Server Database and the related community and
contributing to articles in different
SQL Server Public sites and Forums helping the community
members. He holds a bachelor's
degree in Computer Science & Engineering followed by a
master’s degree in Project
Management. Currently pursuing Ph.D. In Information
Technology from the University of the
Cumberlands. His areas of research interest include RDBMS,

distributed database, Cloud
Security, AI and Machine Learning. He is an MCT (Microsoft
Certified Trainer) since 2017 and
holds other premier certifications such as MCP, MCTS,
MCDBA, MCITP, TOGAF, Prince2,
Certified Scrum Master and ITIL.
Tools and Technologies for Planning the Development of
Smart Cities
Anastasia Stratigea, Chrysaida-Aliki Papadopoulou, and
Maria Panagiotopoulou
ABSTRACT At present, sustainable urban development
constitutes a major planning goal
for many urban environments coping with contemporary
challenges and problems con-
fronted by world cities. Towards this end, the concept of smart
cities emerges as a promis-
ing policy option for effectively dealing with sustainability
objectives. In this respect, the
focus of the present paper is on the development of an ICT-
enabled participatory planning
framework for guiding policy-making towards the planning of
smart cities. This frame-
work is in alignment with the argument that smart-city solutions
must start with the
“city” not with the “smart,” shifting from a technology-pushed
to an application-pulled

smart-city planning approach, matching different types of
“smartness” (technologies,
tools, and applications) with different types of urban functions
and contexts. It is also
built upon a digital platform, integrating tools and technologies
for data management
and e-participatory planning that can support city- and citizen-
specific decision
making, capable of dealing with objectives for urban
sustainability.
KEYWORDS smart city; Information and Communication
Technologies (ICT); sustainable
urban development; (e-)participatory planning; policy making
Introduction
In the shared vision of the European city of tomorrow, future
cities are considered
as:
. “places of advanced social progress, with a high degree of
social cohesion,
socially-balanced housing as well as social, health, and
education for all services
. “platforms for democracy, cultural dialogue, and diversity
. “places of green, ecological, or environmental regeneration
. “places of attraction and engines of economic growth.”
(European Union, 2011: vi)
or stated otherwise, cities represent a “promise for the future”
built upon concepts
such as freedom, innovation, creativity, opportunity, and

prosperity (Schaffers
et al., 2012).
Correspondence Address: Anastasia Stratigea, Department of
Geography and Regional Plan-
ning, School of Rural and Surveying Engineering, National
Technical University of Athens
– NTUA, Heroon Polytechniou str. 9, Zographou Campus,
Athens 15780 – Grecce.
E-mail: [email protected]
Journal of Urban Technology, 2015
Vol. 22, No. 2, 43 – 62,
http://dx.doi.org/10.1080/10630732.2015.1018725
# 2015 The Society of Urban Technology
mailto:[email protected]
This vision is far from the present reality, and it actually
constitutes a target to
be reached. In fact, contemporary cities are confronted with
considerable chal-
lenges, threatening sustainability targets towards their future
development.
Thus, sustainable urban development is currently considered as
a key planning
goal and has received much attention by policy makers and
urban planners (Stra-
tigea, 2012; Tao, 2013) because of:
. demographic (growing and aging of population) and cultural
shifts
. globally increasing urbanization patterns

. climate change challenges that are threatening the
sustainability of urban eco-
systems
. high rates of consumption of non-renewable resources
. deteriorating social cohesion which is expected to deteriorate
further through
evolving migration patterns that are triggered by political
instability, economic
recession, wars, and climate change in many neighborhoods.
In planning a sustainable future for cities, policy makers and
planners are
currently largely supported by the radical technological changes
and the new
potential these can offer for economic development,
organizational performance,
social equity, and quality of living in urban environments.
Broadband network
developments are affecting the interaction among various
actors. These
provide access to worldwide knowledge and information
(re)sources, and a
broad range of tools and applications that allow the
establishment of networks
and synergies among them (locally and globally), removing
space and time bar-
riers. Based on these new network opportunities that allow
competitiveness
gains and community development efforts (Stratigea, 2012), the
concept of
smart city emerges as a new paradigm for sustainable urban
development
that supports competitiveness, local prosperity, and social
inclusion in the

urban context. The widespread use of this concept is associated
with the
pivotal role it can play in coping with challenges emerging from
the global
pattern of urbanization (Walters, 2011).
Along these lines, the present paper focuses on the development
of an ICT-
enabled participatory planning framework supporting the “going
smart efforts”
of cities. Towards this end, in the next section we discuss the
three pillars of the
proposed participatory smart-city planning framework. The
third section
focuses on the steps of the proposed methodological framework,
and, finally,
we comment on the key components and obstacles hampering
the implemen-
tation of the proposed methodological framework.
(e-)Participatory Planning
A variety of terms found in the literature describe the
engagement of various
actors (policy makers, decision makers, stakeholders, citizens,
planners, experts,
and scientists) in the planning process (Saad-Sulonen and
Horelli, 2010). Accord-
ing to van Asselt and Rijkens-Klomp, participatory planning can
be defined as a
process that allows stakeholders and citizens to take part in the
decision-
making process and “ . . . share control over development
initiatives and the
decisions and resources that affect them” (van Asselt and
Rijkens-Klomp, 2002:

174). Engaging various actors in the decision-making process is
done to reach a
balance between different levels of power, interests, and
resources; to create a
44 Journal of Urban Technology
platform for actors to interact and communicate on an equitable
basis; to establish
a productive dialogue that allows participants to reach
consensus; to build com-
mitment and ownership of the final planning outcome; and to
empower individ-
uals to address problems and to set priorities (World Bank,
1996).
Participatory planning engages people in the formulation of
policy decisions
about a variety of problems on a variety of spatial scales. It
constitutes a new para-
digm in planning: a shift from a top-down, largely hierarchical
planning, aimed at
identifying problems, jointly setting up priorities, and
elaborating and adopting
strategies. As such, it leads to “ . . . better-informed and more
creative decision-
making” (HarmoniCOP Project, 2003: 2), while it enables actors
involved to
make more informed judgments and commit to the planning
outcome/decision
(Papadopoulou and Stratigea, 2014; Stratigea, 2009; van Asselt
and Rijkens-
Klomp, 2002). As pointed out by Martens (2013), participatory
planning envisages

a political arena, within which decision-making on shared issues
occurs through
the interaction and negotiation among various actors. Thus, it
largely constitutes a
platform for interaction that can support mutual learning, the
creation of partner-
ships and the empowerment of all parties involved (VSO, 2004)
(See Figure 1),
rather than an attempt at problem solving. Stated differently, it
constitutes a
process of collective analysis, learning, and policy action,
where the emphasis is
placed on the decision-making process rather than on sketching
the final planning
outcome.
In participatory planning, citizens and stakeholders first provide
the
opinions, views, visions, fears, desires, and empirical
knowledge that feeds the
subsequent stages of the process. These contributions delineate
the specific com-
munity context, both in territorial and in social terms, which in
turn define the
context of the planning process and the type of the planning
outcomes that best
fit each specific community context. Participatory planning
implies the sharing
of responsibility for decisions (Lefevre et al., 2000), which can
lead to win-win sol-
utions for both local decision-making institutions on the one
hand and the public
and stakeholders on the other (Stratigea, 2009). Finally,
participatory planning
Figure 1: Key dimensions of participatory planning. Source:

Adapted from VSO (2004).
Tools and Technologies for Planning the Development of Smart
Cities 45
exercises can improve the motivation of participants; sometimes
result in innova-
tive solutions to existing problems; and ensure that proposed
planning interven-
tions reflect the specific needs of the community.
More specifically, the contribution of citizens and stakeholders
can support
the identification of: (See Figure 2)
. planning problem(s): the type and intensity of the problem, as
perceived by those
affected by it
. community attributes: allow planning solutions to account for
the peculiarities of
the social system involved
. spatial context: notes the territorial attributes of the region
concerned
. planning goals, objectives, and targets: reflect priorities of the
planning context
(spatial, social)
. potential planning outcomes (plans): create a vision-driven
process for structuring
locally adjusted different planning outcomes

. planning evaluation context: sets the evaluation context
(criteria and their priori-
tization), based on participants’ views and visions
. policy options: identify locally-adjustable strategies, policy
paths and measures
for implementing the preferred planning outcomes
. feasibility of the proposed planning outcomes: seek consensus
or acceptance by the
community of the final plan.
Figure 2: The contribution of public participation at the various
planning stages. Source: Adapted from
Jain and Polman (2003).
Participatory planning is currently considered a policy response
to the
growing public expectations and willingness to take part in the
decision-
making process. It satisfies citizens’ and stakeholders’ requests
for more
democratic decision-making forms, while it also reinforces the
legitimacy of
decision-making and increases the effectiveness of
implementation of the final plan-
ning outcome (Craps et al., 2003; Stratigea, 2009). During
recent decades, the request
for more open and democratic decision-making has been largely
facilitated by ICTs,
which have set the ground for strengthening participation
through e-participation

tools and techniques. These enable the establishment of online
platforms for collec-
tive action, offering the potential of involving a large number of
interest groups and
thus enhancing interaction, democracy, and transparency of the
planning process;
and the gathering of a massive and diversified knowledge stock,
shedding light
on specific dimensions of the planning problem at hand.
Through such platforms,
traditional—face-to-face—ways of establishing interaction have
migrated to the
Web, providing planners and decision makers a variety of
options for “e-engaging”
participants at the various planning stages.
ICTs and Participatory Urban Planning
Everyday life has been greatly affected by the rapid and
pervasive development
and diffusion of ICTs, which are currently considered the means
for pursuing sus-
tainability objectives. As Caperna stated, “ . . . ICT . . .
pervades all sectors of the
economy, where it acts as integrating and enabling technologies
. . . their pro-
duction and use have important effects on the development of
economic, social,
and environmental areas” (Caperna, 2010: 340).
The role of ICTs has also been broadly acknowledged in coping
with contem-
porary complex problems of urban and regional environments
and has marked a
certain transition in the way and the context within which
solutions to these pro-

blems are sought. The ubiquitous potential of these technologies
can expand the
limits of understanding spatial issues through context-aware
information and
the virtual exploration of environments and communities (Foth
et al., 2009;
Mitchell, 2000). Moreover, these have set new perspectives in
the field of spatial
and participatory planning by creating new opportunities for
developing and
using e-planning and e-participation tools. Particularly in the
case of the urban
environment, ICT becomes a “main driving force for the
development of the infor-
mation/knowledge/network society” (Caperna, 2010: 346)
while, as Reed and
Webster write, “ . . . the dynamic nature of ICT ‘intervention’
in the city extends
and questions traditional ‘comprehensive planning’ notions
because the city
space becomes ‘fluid’ and dynamic, shaped by the technology
itself” (Reed and
Webster, 2010: 367). Because the Internet allows local people
to communicate on
a global scale, local residents have gained access to knowledge
that permits
them to make knowledgeable decisions at both the local and
global scale (Foth
et al., 2009).
ICTs have also enhanced the role of citizens in the production
of urban infor-
mation. In this respect, while planners and professionals,
hithertofore, were the
only producers and users of urban information, digitization
tools and technol-

ogies have empowered users as co-producers, a shift that has
added value to
such technologies, based on the huge and diverse types of
information that can
be produced by talented and mass user groups (Wallin et al.,
2010). Although a
Cities 47
lot of information produced by users has little to do with urban
planning issues
(usually they are more tourism, entertainment, and shopping
related), it rests
upon urban planners and decision-making institutions to take
advantage of this
potential and exploit urban and community informatics for
gathering information
useful for urban planning. In such cases, citizens are invited to
experience urban
space and report inefficiencies or place-based positive and
negative views. Thus,
the potential for citizen participation in seeking solutions to
urban problems is
enhanced (Manzo, 2003; Stratigea, 2012).
At this point, it should be noted that despite the remarkable
progress having
taken place in the field of digital tools and technologies, their
usefulness in the
context of urban planning issues is not yet fully understood.
This can be partly
explained by the (Wallin et al., 2010):

. lack of accessibility to various ICTs applications in many
urban environments
. lack of user-friendly applications
. limited awareness/understanding of the benefits arising from
their use
. lack of an overall purpose for their use, i.e. an urban strategy
or a plan to be
served by these technologies
. production of knowledge and tools targeted to specific
fields/disciplines, while
missing an integrated interdisciplinary view of their use.
In seeking sustainability objectives in the urban context, the
adoption of ICTs
appears to be a great opportunity and a challenge for planners,
decision makers,
and the public. It should also be noted that although “ICTs may
be seen as neutral
technologies, they can certainly be applied to serve different
political and social
purposes, or to respond to different principles and values”
(Anttiroiko and
Malkia, 2007; Buthimedhee et al., 2002; Silva, 2010: 2); and
can, therefore, play a
central role in supporting the participatory issues that lie at the
core of contempor-
ary planning opportunities and challenges. Planners seem to
realize the benefits
to be reaped by the adoption of ICTs for enriching the planning
context with a
more diverse range of citizens’/stakeholders’ views and thus
producing more

comprehensive and locally adapted plans. Decision makers are
also realizing
the potential of ICTs for engaging people in a policy dialogue
that will ensure
a mutual understanding of interests and reduce the number of
conflicts
(Taylor, 1998), that will ensure transparency, legitimacy, and
inclusiveness of the
decision-making process (Stratigea, 2009), that will promote
adaptation to con-
tinuously changing societal conditions (Innes and Booher, 1999)
and that will
support the creation of an innovative learning and knowledge-
building environ-
ment (Friedmann, 1998). Finally, the public seems to be
growing more mature, by
gaining access to a huge number of resources through ICTs,
which in turn
strengthen the willingness to participate and be an integral part
of the decision-
making process.
Clarifying the Concept of “Smart City”
. . . Over the past few years, the definition of ‘Smart Cities’ has
evolved to
mean many things to many people. Yet, one thing remains
constant: part
of being ‘smart’ is utilizing information and communications
technology
(ICT) and the Internet to address urban challenges
(http://www.cisco.
com/).

http://www.cisco.com/
http://www.cisco.com/
What is actually meant by “smart city?” Despite the remarkable
increase in the use
of this term, a distinct consistent comprehension of the concept
among prac-
titioners and academics still does not exist (Chourabi et al.,
2012). This results in
a cacophony of definitions observed in the literature, stressing
the need for
further conceptual research (Boulton et al., 2011). Some of the
definitions of
smart cities that have been introduced and adopted focus on
ICTs as the dominant
technology driver and enabler of urban growth, while others
provide a broader
perspective, including socio-economic, governance,and
participatory aspects in
order for sustainable urban development to be enhanced
(Manville et al., 2014).
Some significant definitions, put forward and used in both
practice and academia,
describe the smart city as:
. “ . . . a city that monitors and integrates conditions of all of its
critical infrastruc-
tures, including roads, bridges, tunnels, rail/subways, airports,
seaports, com-
munications, water, power, even major buildings, can better
optimize its
resources, plan its preventive maintenance activities, and
monitor security
aspects while maximizing services to its citizens” (Hall, 2000:
1);

. “ . . . a city built on the ‘smart’ combination of endowments
and activities of self-
decisive, independent, and aware citizens” (Giffinger et al.,
2007: 11);
. “ . . . a city that combines ICT and Web 2.0 technology with
other organizational,
design, and planning efforts to de-materialize and speed up
bureaucratic pro-
cesses and help to identify new, innovative solutions to city
management com-
plexity, in order to improve sustainability and livability”
(Toppeta, 2010: 4);
. “ . . . a city where investments in human and social capital and
traditional (trans-
port) and modern (ICT) communication infrastructure fuel
sustainable econ-
omic growth and a high quality of life, with a wise management
of natural
resources, through participatory governance” (Caragliu et al.,
2010: 70);
. “ . . . a city seeking to address public issues via ICT-based
solutions on the basis
of a multi-stakeholder, municipally-based partnership”
(Manville et al., 2014: 9).
Furthermore, various terms similar to “smart city” appear, such
as “wired” or
“smart” communities, “broadband” communities, “digital”
communities, “net-
worked” communities, “smart community network,”
“community informatics,”
and “intelligent” communities. (California Institute for Smart

Communities,
2001; Coe et al., 2001; Droege, 1997; ICF, 2007; Intel, 2007;
Keenan and Trotter,
1999; Komninos, 2002, 2006, 2009; Steventon and Wright,
2006). These terms are
interchangeably used by various researchers, all implying
communities that are
making “a conscious effort to understand and engage in a world
that is increas-
ingly connected” (Albert et al., 2009: 8). Although there are
certain differences
in the way the above terms are used, all definitions seem to
have three main
key dimensions in common, namely (Stratigea, 2012): the means
of communi-
cation (network infrastructures—technology—ICTs); the
process (networking
among various actors); and the goal pursued (public
involvement or other, e.g.
transport management).
At the heart of the smart city concept also lie (Stratigea, 2012):
. sustainability: seeking the management of urban functions in a
way that a
balance is maintained among environmental, social, and
economic objectives
. innovation: seeking to empower both people and places in
urban regions
Cities 49

. participatory governance: implying the way that rules are set
and implemented by
governing bodies in order to drive a more effective resource
management
pattern
. investments: on specific ICTs infrastructures and applications
that fit with the
needs of each specific urban environment.
The goal behind smart city development is the provision of
qualitative and inno-
vative services to citizens, economic activities, institutions, but
also visitors,
together with the production of a safe, pleasant, and highly
inclusive urban
environment (Stratigea, 2012).
Apart from the role played by digital technologies towards a
competitive and
sustainable future, what is also a distinguishing characteristic of
the smart-city
concept is the collaborative perspective, implying interaction
among various
city actors (policy makers, decision makers, planners,
stakeholders, citizens,
experts, and scientists). This reflects the user-driven and user-
centric research
approach of smart cities, compared to the rather technology-
based initiatives,
relating to the digital city or the u-city (ubiquitous) concepts.
More specifically,
the challenge is to redefine the smart city as an environment of
innovation,
empowerment, and participation of citizens, businesses, and
other stakeholders

in shaping their future, through the choices they have and
decisions they make;
or the challenge is to focus on change and transformation
towards a smarter
city, in the sense of a change towards shaping a better and more
participative,
inclusive, and empowering city, instead of imagining an ideal
future vision
(Schaffers et al., 2012). Thus the concept of Public
Participation (PP) as “ . . . the
involvement in knowledge production and/or decision-making
of those involved
in, affected by, knowledgeable of, or having relevant expertise
or experience on the
issues at stake” (van Asselt and Rijkens-Klomp, 2002: 168), is
of crucial impor-
tance, largely associated with its role as a tool to identify areas
of stakeholders’
mutual understanding and consensus that can drive policy
choices on specific
ICT infrastructure and applications that serve the needs of
citizens and local
stakeholders.
Based on the literature review and the empirical applications of
the concept of
smart city, a certain revision of the concept is taking place,
shifting from a technol-
ogy-driven to a more holistic approach by means of integrating
certain city
attributes/functions in pursuing smart and sustainable
development objectives.
The definition provided by Schaffers et al. (2012), which is also
adopted in this
work, states:

. . . The smart city concept is multi-dimensional. It is a future
scenario
(what to achieve), even more, it is an urban development
strategy (how
to achieve). It focuses on how Internet-related technologies
enhance the
lives of citizens. This should not be interpreted as drawing the
smart city
technology scenario. Rather, the smart city is how citizens are
shaping
the city in using this technology, and how citizens are enabled
to do so.
The smart city is about how people are empowered, through
using technol-
ogy, for contributing to urban change and realizing their
ambitions. The
smart city provides the conditions and resources for change. In
this
sense, the smart city is an urban laboratory, an urban innovation
ecosystem,
a living lab, an agent of change. Much less do we see a smart
city in terms of
a ranking. This ranking is a moment in time, a superficial result
of under-
lying changes, not the mechanism of transformation. The smart
city is the
engine of transformation, a generator of solutions for wicked
problems; it is
how the city is behaving smart (Schaffers et al., 2012: 57).
Planning the Smart City—A Participatory Methodological

Framework
In this section, the focus is on the exploitation of the smart city
concept and
respective ICT-enabled tools and technologies dealing with
sustainability chal-
lenges in urban environments. Towards this end, a collaborative
planning frame-
work is developed, where the concept of smart city and its
applications are used
for serving sustainability goals, i.e., economically strong,
socially inclusive, and
environmentally responsible urban development, in alignment
with the EU
2020 objectives for smart, sustainable, and inclusive urban
growth (JESSICA,
2012). This framework adopts a participatory planning
orientation, seeking city-
and citizen-specific smart applications, allowing for the
management of chal-
lenges faced by contemporary cities under the current social,
economic, and
environmental circumstances. The steps of this planning process
are supported
by ICT-enabled tools and technologies, drawn from state-of-the-
art of smart-city
initiatives. These are further enriched by ICT-enabled
participatory foresight
and evaluation tools and approaches, integrated in the planning
framework,
which aim at exploring and evaluating potential future
developments (scenarios)
and respective policy options of each specific urban context.
The proposed participatory methodological framework consists
of four suc-

cessive stages (See Figure 3):
Figure 3: Structure/stages of the proposed participatory
methodological framework—tools and
technologies at each stage.
Cities 51
. First stage: “Scanning” of smart city efforts/applications at a
global/European
level, with special emphasis on the identification/classification
of smart-city
strategies, efforts, and respective applications
. Second stage: Supports the establishment of:
- a pool of tools and technologies used for city-wide, geo-data
collection
and management
- a pool of tools and technologies supporting public (e-
)participation
aspects
- a pool of smart city applications, which can better
“communicate the
message” of smart city development, present fields of
application (e.g.,
transport, energy), and learn from the benefits reaped by cities
pioneering
in the field.
These are the outcomes of both tools and technologies already

used in various
smart cities’ examples (Stage I) and also tools and technologies
that exhibit certain
potential in fulfilling specific needs. The above established pool
of tools and
technologies can provide a range of options for decision makers
and planners,
which can be used for guiding “going smart” planning efforts in
city environ-
ments.
. Third stage: At this stage, a collaborative planning framework
is proposed for
smart city development. More specifically, efforts focus on
structuring and eval-
uating alternative options for smart-city development, based on
a forward-
looking, vision-building process towards urban regeneration,
which adopts:
- an integrated approach, exploring all potential fields of smart-
city appli-
cations that promote sustainable development
- a place-oriented and people-oriented approach, aimed at
incorporating
the peculiarities of the physical and social reality of each
specific urban
environment in designing smart-city applications
- a participatory approach, supporting the establishment of
broad urban
coalitions, through certain compromises and strategic choices in
co-oper-
ation with citizens and local stakeholders.

. Fourth stage: Web platform development, implementing the
“Smart City Plan-
ning Framework.” This platform combines/integrates tools and
technologies
presented at the previous stages that support decision makers
and planners
establishing an online communication/interaction with citizens
and stake-
holders for co-designing/co-deciding city- and citizen-specific
policies and
smart applications, serving sustainable future planning options.
The stages of the proposed methodological framework are
further discussed in the
following sections.
Stage I: Gathering Smart Cities’ Experiences
This stage focuses on examining the experience of smart cities
by reviewing several
literature resources, both at the global and the European level.
The main sources of
information can be scientific research papers, EU reports, White
Papers, and
policy documents; national reports on strategies towards smart
cities’ development;
reports based on the Smart Cities’ initiative
(http://www.smartcities.info/research);
reports produced by the FIREBALL Smart Cities Project
(www.fireball4smartcities.
eu); other reports on smart cities from the global scene, e.g.

United States, Canada,
and China. Work carried out at this stage can fall within two
layers:
. At the first layer, information on smart cities is gathered, both
at the global and
the European levels. This information is elaborated so that the
current state-of-
the-art can be clarified and concluded with a pool of smart-city
applications.
Furthermore, these are classified according to the specific
purpose they serve
and the technology used. The outcome of this stage can provide
a range of
policy options and respective ICT applications already used for
smart-city
development. Moreover, it can provide a core of themes/aspects
for smart-
city development for further consideration.
. At the second layer, emphasis is placed on problems and
challenges that are cur-
rently faced by cities and that are strongly affecting their future
economic,
social, and environmental conditions:
- changing social structure, characterized by social polarization,
segre-
gation, isolation, and violent incidents that threaten social
cohesion and
safety
- intensifying migration patterns due to a variety of factors,
such as
poverty, political instability, and wars

- changing demographic structures, mainly characterized by an
aging and
declining population
- an economic structure marked by factors such as the economic
recession,
which has dramatically influenced development in many cities,
mainly in
European neighborhoods, threatening sustainable urban
development by
severe unemployment, radical changes in economic structure,
poverty,
social exclusion, the “brain-drain” accompanying the high youth
unem-
ployment rates, environmental deterioration, and degradation of
quality
of life
- the depletion of natural resources due to urban sprawl and land
con-
sumption patterns, which place urban ecosystems under severe
pressure
- climate change threatening urban environments.
Work at this stage results in the listing of already established,
well-functioning,
smart-city applications/best practices that are tackling peculiar
issues faced by
single case study contexts—first layer; and the sketching of new
challenges that
need to be dealt with, going beyond already implemented smart
city applications
and posing the need for further developments in this particular
field—second
layer.

Stage II: Tools and Technologies
Smart cities can be also understood as places generating a
particular form
of spatial intelligence and innovation, based on sensors,
embedded
devices, large data sets, and real time information and response
(Schaffers
et al., 2012: 6).
Cities 53
http://www.smartcities.info/research
http://www.fireball4smartcities.eu
http://www.fireball4smartcities.eu
In planning the smart future development of a specific urban
environment, of
crucial importance is the management of big data—different
data layers concern-
ing the spatial structure and functioning of the city, its
infrastructures, the natural
and cultural resources, and the social context. Towards this end,
planners and
decision makers need to use a range of tools and technologies in
support of
data management. These can be used for enhancing planners’
potential to:
. better understand the environmental, economic, and societal
aspects of urban
environments as well as their interrelationships, upon which
livability and sus-

tainability perspectives of the urban context are built
. explore or anticipate or even map urban problems and
effectively allocate avail-
able resources for planning solutions
. properly communicate problems and/or potential
solutions/policies to plan-
ning recipients in seeking consensus and the more effective
implementation
of the planning outcome
. identify policy priorities in each specific urban context.
Moreover, in contemporary planning theories and approaches,
there is a
strong emphasis on the role of public participation in seeking
more effective plan-
ning solutions to societal problems (Pereira and Quintana,
2002). Public partici-
pation, as a knowledge and intelligence gathering tool, but also
as a
communication and consensus-building tool, contributes to
widening of the
scope of the planning exercise, reaching consensus in defining
priorities and allo-
cating scarce resources and effectively implementing plans.
(Stratigea, 2009).
Public participation can be understood and implemented in
many different
ways, ranging from providing information that empowers
stakeholders to
increasing the number of choices to consider (Aggens, 1998;
Arnstein, 1969;
Green and Hunton-Clarke, 2003; OECD, 2001).

In addition, when planning the “smart” future development of
urban regions,
it is important for decision makers planners, and citizens to gain
access to a variety
of good practices—examples—which can shed light on a range
of issues, such as
the type and range of existing applications; the core themes
tackled such as trans-
port and energy; the type of problems considered; the level of
public partici-
pation/citizen involvement in the decision-making process; the
acceptability of
these applications at each specific city context; and the
tools/technologies prac-
ticed. This information can be of value for both decision makers
and planners—
the creators/providers of such applications—for enriching their
knowledge and
views and also for using the examples as demonstrative material
in the context
of participatory processes; and for citizens/stakeholders—the
users of the appli-
cations—who, by previewing successful examples, can widen
their knowledge
and understanding on the specific issues/technologies that are to
be applied.
More specifically, work carried out at this stage supports the
identification/
description of tools and technologies, examples of their
application, and the
expected outcome/contribution to the smart city planning
context referring to
the following layers:
. First layer: incorporating tools and technologies that can be

used for big data
management, as well as geo-visualization and mapping
. Second layer: presenting available options as well as tools and
technologies for
dealing with citizens’/stakeholders’ engagement
. Third layer: presenting a range of sectoral or other types of
applications, which
arise from the literature review, representing a bulk of potential
options for
further elaboration in the context of smart-city development.
These can be
used for various purposes, e.g. to increase public awareness of
potential appli-
cations that can be developed in a specific smart-city context.
. These tools can be used to have planners and stakeholders
better understand
the urban context, identify spatial problems, and increase
citizen empower-
ment.
If public engagement in planning is a goal to be achieved, there
are now
many tools and technologies for doing so including classical
tools such as
focus groups, advanced web-based participatory technologies
(Kingston et al.,
2000; Wilson, 2008), crowd-sourcing platforms (Howe, 2006b;
Papadopoulou
and Giaoutzi, 2014; Surowiecki, 2004), and the user-oriented

open innovation
esosystems known as city living labs (Chesbrough, 2003;
Komninos, 2006
2009; Pallot, 2009). Examples of these living labs include:
- [email protected] Urban Lab—City of Barcelona: employed to
promote the use of public
spaces in the city of Barcelona in order for tests and pilot
programs on
products and services with an urban impact to be conducted
(sensoriza-
tion, urban planning, mobility, tourism, and education) in large-
scale,
real-life environments (Schaffers et al., 2012).
- Smart crowds—City of Trento, Italy: territorial lab, in which
citizens can
participate as volunteers in R&D and innovation projects and
products.
Usually participants are asked to test mobile, tablet, or desktop
appli-
cations and services in the context of a survey or to participate
in focus
groups (http://www.smartcrowds.net/).
- Smart Campus—City of Trento, Italy: is both a laboratory and
a commu-
nity, where students, teachers, researchers, and campus staff,
using
advanced ICTs, participate and collaborate in innovative design
pro-
cedures for smart services, in support of urban sustainability
objectives
(http://www.smartcampuslab.it/).
It should be noted that, in most cases, smart-city applications

consist of a combi-
nation of tools and technologies, aimed at improving the
efficiency of services and
decreasing costs while offering a wide range of “accessibility”
options to users. An
example of the combined use of tools and technologies is the
“TiMatOnGIS” plat-
form (Tourism in Matera On Geographic Information System),
in the city of
Matera, Italy, which successfully combines cloud computing,
crowdsourcing
tools, Volunteered Geographical Information (VGI),
collaborative mapping, and
Web-GIS services. TiMatOnGIS is a geographic database
(package of Web 2.0
and cloud computing based tools), which was developed by the
Laboratory of
Urban and Territorial Systems, University of Basilicata, and
aims to provide visi-
tors with significant information about Matera, while it also
allows them to inter-
act by providing geographical data, remarks, and comments via
Web-GIS services
and the TiMatOnGIS Blog. Apart from the visitors’ target
group, the platform also
provides tourist operators—the supply side—with the potential
to promote their
services or products as well as anything that could be
interesting or useful to tour-
ists (Murgante et al., 2011).
Cities 55
http://www.smartcrowds.net/
http://www.smartcampuslab.it/

Stage III: Smart City Planning Framework
In this section, a framework for sustainable smart city
development is presented,
supporting an integrated, city- and citizen-specific as well as
participatory-
oriented planning approach. The scope of this stage is to
provide input on the
range of ICT-enabled smart applications, tools, and
technologies, as well as plan-
ning tools that can strengthen the planners’ potential and
options for shaping the
sustainable future smart city.
A collaborative planning approach is adopted for identifying
city- and
citizen-specific applications for smart city development, i.e.
adjusting the smart-
city concept to the attributes and needs of a specific city
environment. These appli-
cations can be incorporated in desired smart city future
alternatives which, along
the lines of sustainability, can be structured and evaluated by
means of the follow-
ing distinct steps of the planning process (Khakee, 1998;
Giaoutzi and Stratigea,
2011):
. a learning step, consisting of an in-depth analysis of each city
. an evaluation step, comprising:
- a co-design process that aims at embodying the ideas,
concerns, visions,

and urban development priorities of citizens, stakeholders, and
private
and public agencies in the structuring of alternative scenarios of
future
smart city development
- a co-deciding process that addresses opinions, priorities, and
views of par-
ticipants in support of the evaluation of alternatives and sets
policy pri-
orities and policy measures that need to be enforced in pursuing
a certain
smart-city development alternative
. an action step, relating to the implementation of the policy
framework presented
before, that needs to be enforced for the effective
implementation of the selected
alternative plan.
These three steps form the backbone of each planning exercise
and are used for
building the smart-city planning framework, while they are
supported by a
wide range of tools and technologies dedicated to carrying out
specific tasks
within the planning process (Stratigea, 2009).
The focus of this stage is on facilitating ICT-enabled choices by
presenting
tools and technologies that support e-planning. In this respect,
it can provide a
pool of potential tools and technologies available to decision
makers and planners
and successful examples of applications of those tools and
technologies.

Stage IV: Web-Platform Development
The final stage aims at the development of a Web-platform,
which integrates ICT-
enabled tools and technologies for data management and public
participation as
well as participatory foresight and evaluation tools, serving the
goal of planning
the future development of the specific city as a smart city. In
this respect, the archi-
tecture of the proposed digital platform will be based on the
combination of tools
and technologies presented at the previous stages (II and III),
while work at this
specific stage will be enriched by the knowledge gathered and
options available
at Stage I (e.g., smart city applications, sectoral choices).
The development of the platform can form the base of a smart-
city planning
exercise, which needs to be part of a general planning approach
of each specific
city context for reaching sustainability goals and objectives.
More specifically, it
constitutes the basis for the direct participation of public and
private agencies,
planners, citizens, and local stakeholders, upon which city- and
citizen-specific
smart applications can be identified, coping with goals and
objectives of sustain-
able urban development. The above actors are considered as key

players in the
process of defining the type of applications to be used in each
specific city
context, while they are also considered as both co-creators
(content development),
but also consumers of these applications.
Discussion
The present article focuses on the development of a planning
framework support-
ing “going smart” planning efforts in cities. The paper first
presents the three
pillars of the proposed planning framework, namely: the
participatory planning
approach, shedding light on its rationale/usefulness for
sustainable urban
planning; the ICTs and their potential for urban management
purposes; and the
smart city, as a new ICT-enabled concept and a context, within
which environ-
mental, economic, and social innovation objectives in urban
environments can
be pursued.
Next in line is the creation of a pool of ICT-enabled tools and
technologies for
data management, but also citizens’ and stakeholders’
engagement, which in com-
bination with a range of participatory planning tools (foresight
tools, evaluation
tools, etc.), can support decision makers and planners to carry
out city- and
citizen-specific smart planning exercises. The scope behind the
implementation
of such a framework is to identify and apply ICT applications

that will improve
the management of urban functions. This is accomplished by the
integration of
technological innovations and potentials with participatory
planning approaches
in the urban context. Understanding each specific urban setting
is of crucial
importance for developing applications that are of relevance to
this specific city
context (Aurigi, 2013).
The role of planners is of crucial importance for the application
of the
proposed planning framework. In this respect, planners are
considered agents
of change, initiators, and managers of the whole participatory
experiment
(Briasoulis, 1999; Fischler, 2000a, 2000b; Forester, 1989;
Stratigea, 2010). More
specifically, planners have multiple roles, including convincing
decision-making
institutions to shift from purely bureaucratic to more democratic
decision-
making models by changing institutional codes and meanings
and engaging
stakeholders and the public and convincing stakeholders and the
public to
accept new, more inclusive and democratic decision-making
processes, contribut-
ing their empirical knowledge, their views, and their values to
the decision-
making process. In such a way, planners are responsible for
establishing the
“bridges” that will enable “public and democratic
argumentation” (Throgmorton,
1996: 257) among all partners involved in decision-making.

ICT-enabled features of the proposed methodological
framework include:
. Big data management tools and technologies that are used for
collecting, storing,
processing, visualizing, and communicating information. Such
information
can refer to the various layers of a specific city, e.g. transport
network,
Cities 57
energy network, various services, land uses, local assets, and
entertainment
spaces.
. Public (e-)Participation tools and technologies that enable the
participation of a
wide range of actors in the decision-making process, thus
leading to city- and
citizen-specific policy decisions as to the type of “smartness” to
be pursued
(e.g., transport, energy) and the type of applications needed.
These policy
decisions, being the outcome of a participatory planning
process, can reflect
the specific attributes of a city and its population, as well as the
challenges
facing that specific city. Tools and technologies considered at
this stage can
refer to Web-based participatory tools, crowdsourcing
platforms, living labs,

and social media. These tools are used to gather local
knowledge, thus enriching
planners’ and decision makers’ potential to meet the
population’s expectations
and needs when planning the development of a smart city.
. ICT-enabled digital platforms that integrate the first two sets
of tools and technol-
ogies and allow for the development and planning of a smart
city.
The existence of advanced and ubiquitous broadband
communication infra-
structures (mobile or fixed-line infrastructures) is essential for
the implementation
of the proposed methodological framework and the development
of the digital
platform, setting the ground for both the digital interaction
among actors and
the function of smart-city applications. Although the civilized
world is experien-
cing great progress, it should be borne in mind that advanced
infrastructures may,
even at present, be an issue for many regions of the world and
of Europe as
well (e.g., small isolated cities in rough terrains or lagging-
behind urban areas)
(Papadopoulou and Stratigea, 2014; Stratigea and
Panagiotopoulou, 2014).
Of crucial importance for the implementation of the Web-based
platform for
planning smart cities are the ICT skills of the local population
(Papadopoulou and
Stratigea, 2014). The higher the level of ICT skills, the higher
is the potential of

effective participation in planning a smart city. Of importance
is also the digital
divide, which can disturb the balance of citizens’ groups that
participate in the
planning process for smart-city development, to the detriment of
ICT illiterate
and thus less empowered population groups. For a balanced
outcome, the attenu-
ation of the digital divide among different city groups through
smart-city learning
models is important, as this will ensure a higher level of digital
inclusion and a
more representative balance of power of the various social
groups in decision-
making. In turn, this will strengthen the participatory context of
the whole plan-
ning effort as well as the legitimacy, transparency,
acceptability, and successful
implementation of the planning outcome.
At this point, it should be noted that the two issues of
broadband communi-
cation infrastructures and ICT skills of the local population are
critical to creating
smart communities (Stratigea, 2012). It is important to note that
there are many
small cities in the developed world that are still striving for
connectivity and
high quality broadband infrastructures (Papadopoulou and
Stratigea, 2014).
Moreover, ICT illiteracy, especially in specific population
groups (e.g., the
elderly, the poor, the illiterate), still remains an issue in many
regions of the world.
The proposed methodological framework is considered of

importance for
contributing to:
. Policy recommendations on city- and citizen-specific smart
applications that:
are the result of a systematic participatory planning process,
where a variety
of local actors (decision makers, local agencies, businesses,
institutions, citizens)
are engaged in a co-designing/co-deciding exercise; and are
seeking to support
planning goals and objectives of a specific urban context;
. Policy decisions on the deployment of the necessary
infrastructures and the
development of the selected ICTs applications, thus steering,
both private and
public decisions on certain investment plans.
When the framework presented in this paper is implemented,
additional pro-
blems might be revealed, but they too will be solved. We are
convinced that as
technological potential is married to societal will, urban
planners and other
decision makers will be able to use these new tools to create
“smart cities” that
are informed by the wisdom of their citizens
Notes on Contributors

Anastasia Stratigea is an associate professor at the Department
of Geography
and Regional Planning, School of Rural and Surveying
Engineering, National
Technical University of Athens.
Chrysaida-Aliki Papadopoulou is a PhD candidate at the
Department of Geography
Maria Panagiotopoulou is a PhD candidate at the Department of
Geography
Cities 59
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