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MAKING CITIES INTEROPERABLE IN TURKEY
H. Bayraktar1, D. Y. Bayar 1, G. Bilgin 1, *
1 Ministry of Environment and Urbanization, Directorate General of Geographic Information Systems, 06530 Çankaya Ankara,
Turkey - (huseyin.bayraktar, dyildirim.bayar, gokhan.bilgin)@csb.gov.tr
KEY WORDS: Smart Cities, Interoperability Model, Interoperability in Smart Cities, Technical Interoperability, Semantic
Interoperability, Organizational Interoperability, Smart City Interoperability Model of Turkey
ABSTRACT:
The population of cities is increasing rapidly day by day, and it is predicted that this increase will continue in the following years.
Accordingly, population growth creates a significant pressure in many different domains of cities such as infrastructure, traffic,
energy, and environment. Smart cities come forward as a useful option to struggle with the pressure on cities caused by
overwhelming population growth and to make cities liveable and sustainable. Smart city approach creates gains in the fields of
sustainable development, competitiveness and environmental sustainability with its ability to transform information into economic,
social and environmental benefits. However, smart city services and applications are mostly designed as independent and unrelated
units so this approach causes isolated and heterogeneous data and technology islands. As the result, data flow problem occurs
between vertical applications and service suppliers, and this interoperability problem causes emergence of independent silos in smart
cities. Such silos hinders data integration, prevent citizens and public administrations benefit fully from smart cities, and cause
vendor lock-in. In order to use the full potential of smart city approach, it’s vital to secure interoperability systems and applications
of smart cities. In this study, interoperability terms and their necessity for smart city ecosystem will be addressed. Afterwards, Smart
City Interoperability Model’s (SCIM) contributions to semantic, technical and operational interoperability will be discussed.
* Corresponding author
1. INTRODUCTION
Population of cities is increasing unprecedentedly day by day.
In 1950, %30 of the world’s total population was residing in
cities and this number increased up to %54 in 2014 (United
Nations Department of Economic and Social Affairs, 2014).
Global population is expected to rise to 8.6 billion in 2030, 10.1
billion in 2050 and 12.7 billion in 2100 (United Nations
Department of Economic and Social Affairs, 2019).
Smart cities come forward as a useful option to struggle with
the pressure on cities caused by overwhelming population
growth and make cities liveable and sustainable. Smart city
approach creates gains in the fields of sustainable development,
competitiveness and environmental sustainability with its ability
to transform information into economic, social and
environmental benefits.
In this context, ICT is the key-enabler for implementing
innovative solutions, services and applications to make cities
“smart” (Petrolo et al., 2015). Especially IoT (Internet of
Things) technologies are being leveraged in many domains all
around the world, including smart cities (A. Gyrard and M.
Serrano, 2016).
However, smart city services and applications are mostly
designed as independent and unrelated units (J. Hwang et al.,
2019) so this approach causes isolated and heterogeneous data
and technology islands. As the result, data flow problem occurs
between vertical applications and service suppliers, and this
interoperability problem causes emergence of independent silos
in smart cities (Brutti et al., 2019). Such silos use different
communication technologies, architectures and standards as
well (A. Kazmi et al., 2018) and hinder data integration, prevent
citizens and public administrations benefit fully from smart
cities and causing vendor lock-in (A. Brutti et al., 2018).
“Interoperability” establishes a relationship between
heterogeneous systems to ensure exchanging data and
coordinating processes (B. Molina et al., 2014). Integrating such
heterogeneous devices and system also contribute to enabling
IoT technologies in smart cities (A. Gharaibeh et al., 2017).
2020-2023 Smart Cities Strategy and Action Plan of Turkey
(SAP) was published in December 2019 to ensure
interoperability by bringing a holistic perspective to smart city
policies at the national level, to prioritize investments in line
with the determined policies, and to ensure that the investments
are implemented with the right projects and activities (Bayar et
al., 2020).
Within the context of SAP, 26 actions are defined in total, and
sixteenth action is determined as “Smart City Terminology,
Smart City Data Dictionary, Interoperability Model and
Reference Architectural Model will be created.”, and one of the
subgoals of the action is “SCIM will be prepared” (The Ministry
of Environment and Urbanization of Turkey, 2019).
This paper will, in Section 2, discuss the interoperability term
and the levels of interoperability. After that, in Section 3,
interoperability within the scope of SAP was discussed and
recommendations for smart city stakeholders that are expected
to contribute to technical, semantic and operational
interoperability were mentioned. Finally, Section 4 concludes
the paper.
2. INTEROPERABILITY IN SMART CITIES
The concept of interoperability was used for the first time in the
military field. In the study of the US Department of Defence in
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVI-4/W5-2021
The 6th International Conference on Smart City Applications, 27–29 October 2021, Karabuk University, Virtual Safranbolu, Turkey
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91
1977, it was defined as "The ability of systems, units or forces
to provide services to and accept services from other systems,
units, or forces and to use the services so exchanged to enable
them to operate effectively together." (DOD, 1977) (Kubicek et
al., 2011). One of the definitions of the term interoperability,
which is especially important for information systems, is
defined as "the ability of two or more systems or components to
exchange information and to use the information that has been
exchanged" in the Institute of Electrical and Electronics
Engineers (IEEE) dictionary named "IEEE Standard Computer
Dictionary" (IEEE, 1990). Another definition of this term is
defined in the European Interoperability Framework as “the
ability of organisations to interact towards mutually beneficial
goals, involving the sharing of information and knowledge
between these organisations, through the business processes
they support, by means of the exchange of data between their
ICT systems.” (European Commission, 2017).
In line with these definitions, issues to ensure interoperability
can be addressed at three different levels: technical, semantic
and organizational (Novakouski and Lewis, 2012).
Technical interoperability: The data used and produced within
the concept of smart cities is usually locked-in one system,
domain or service provider and it is challenging to make the
data shared and re-used by other applications, providers and
systems (Karpenko et al., 2018).
In general terms, technical interoperability ensures data
exchange. Therefore, it copes with protocol, connectivity, time
management and other hardware and software related issues
(Diallo et al., 2011). As data is one of the core components of
smart cities (Wang et al., 2014), technical interoperability could
be considered as the base of the whole interoperability
ecosystem. Breaking silos between various applications is only
possible by ensuring technical interoperability.
Figure 1. Interoperability Levels (Novakouski and Lewis, 2012)
Semantic Interoperability: While technical interoperability
deals with technical issues during the exchange of data,
semantic interoperability focuses on the “meaning” of data.
Usually, stakeholders of cities tend to collect data for their
applications or projects and mostly the data is not structured in a
standard way to share with other smart city stakeholders that
can reuse the data in similar smart city applications (Chaturvedi
and Kolbe, 2019).
The aim of semantic interoperability is to use explicit semantic
descriptions, thus, it will be possible to facilitate information
and systems integration (Kalfoglou et al., 2005). With semantic
interoperability it is possible to create a common understanding
between the requested service and data (Heiler, 1995). Also,
leveraging relative ontologies can support semantic
interoperability (Gyrard et al., 2018).
Organizational Interoperability: Organizational
Interoperability is the ability of organizations to communicate
and transfer data effectively, even if they are using different
information systems based on separate infrastructure (ETSI,
2008). (Hellman, 2010) addressed the barriers to organizational
interoperability as low competency, lack of measurable,
economic restrictions, absence of national joint efforts, project
archipelago, disharmony in legislation, anaemic arenas,
invisible best practice, the human factor, ubiquitous
heterogeneity.
In order to establish organizational interoperability, it is
necessary to address all administrative units in the ecosystem,
and determine their roles and the functions under their
responsibility (Yazici and Özdemirci, 2019).
3. SMART CITY INTEROPERABILITY MODEL OF
TURKEY
Lately, cities carry out separate heterogeneous solutions related
to different smart city domains. In order to use the full potential
of the smart city approach, it’s vital to secure interoperability
between these solutions (Brutti et al., 2019).
Solving interoperability issues in a particular focus area can be
relatively easy by using a set of common standards. However,
each of the smart city domains has developed independently
from other areas for years and has created its own terminology.
Therefore, there are many applications already running in every
field and numerous datasets have been defined. Although it is
theoretically possible to create a semantic model to cover all
these areas and wait for the stakeholders in all these areas to
leave the existing data structures, switch to this model will bring
a huge cost in practice.
Instead of such a transition, it would be more realistic to match
existing datasets with a determined model so that it can be
understood by all stakeholders. For this reason, with SCIM,
existing frameworks and standards have been proposed that will
contribute to the work of all smart city stakeholders in terms of
semantic, technical and organizational aspects, rather than
introducing new standards and models.
3.1 Semantic Interoperability
As a result of systematic research on the subject of
interoperability in smart cities, two semantic models that can be
directly called "Smart Cities Interoperability Models" have been
identified. The first one of these models is PAS 182 & ISO/IEC
30182 – Smart City Conceptual Model (BSI, 2014).
On the one hand, PAS 182, which defines an effective
framework for establishing interoperability, outlines various
concepts and the interrelationships between them. This
comprehensive framework, defined by concepts and
relationships, is general enough that it can be used to describe
data from any industry regarding smart cities.
On the other hand, the smart city conceptual model provided by
PAS 182 does not claim to remove all obstacles to
interoperability. Decision makers should consider issues such as
ensuring compliance, confidentiality, security, integrity,
availability and data quality.
Component
Technology
/Standard
Explanation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVI-4/W5-2021
The 6th International Conference on Smart City Applications, 27–29 October 2021, Karabuk University, Virtual Safranbolu, Turkey
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92
Smart City
Conceptual
Model
PAS 182
The smart city concept
model (SCCM), outlined
in PAS 182 by the
British Standards
Institute (BSI), addresses
the lack of
interoperability by
defining an overarching
framework of concepts
and relationships that can
be used to describe data
from any industry.
Smart City
Onthology
SAREF4CITY
SAREF4CITY document
is a technical
specification document
prepared as an extension
of SAREF for the Smart
Cities domain.
Context
Information
Management
FIWARE
FIWARE-NGSI v2 is an
application programming
interface that aims to
manage the entire
lifecycle of context
information, including
updates, queries,
registrations and
subscriptions.
Data
interoperability
framework
ITU-T
Technical
Specification
D3.3
Created by the ITU-T
FG-DPM (Data
Processing and
Management Focus
Group to support IoT and
Smart Cities &
Communities) focus
group, this technical
specification document
outlines a framework for
supporting data
interoperability in IoT
environments. Relevant
requirements and
technologies that support
data interoperability are
defined in this technical
specification.
Table 1. Recommended Technologies and Standards for
Semantic Interoperability in Smart Cities
This model is a theoretical study that has been created in
general that can address almost all vertical areas of the smart
city. This model will gain meaning with a mapping work that
stakeholders will create to adapt to this model in order to ensure
unity of meaning, instead of changing the existing models. In
the case of using this model in Turkey, smart city stakeholders
should do a matching study for their own datasets. Since the
perspective of the model is significantly inclusive, it is thought
that a match can be obtained for almost any dataset. With the
model, it is possible to collect data from different organizations,
facilitate reuse of the data and break the silos within smart
cities.
Another semantic study is the SAREF4CITY model. The
requirements of this model are built on three usage scenarios: e-
Health and Smart Park, Air Quality Monitoring and Mobility,
Street Lighting. For this reason, it is clear that SAREF4CITY is
not a general model like PAS 182. However, since it is based on
the main applications of smart cities, its practical value is quite
high. In addition, it is possible to use directly rather than a
mapping mechanism like PAS 182 as it contains class structures
that software can directly reference. Essentially, even if these
two models overlap to a certain extent, they are far from being
alternatives to each other. Both are possible and necessary on a
case-by-case basis.
Practical field experience shows that interoperability has many
other dimensions besides conceptual models. Rather than
focusing on a single model that will transcend all these
dimensions, it would be more beneficial and realistic to focus
on maintaining certain minimum interoperability mechanisms.
It is understood and recommended that the frequently used
FIWARE Context Information Management API will be an
important interoperability mechanism.
Another conclusion reached from the field examples examined
is that it is necessary to ensure that many heterogeneous objects
work together in order to make interoperability possible in
practice. One of the main alternatives to FIWARE, especially in
the world of the Internet of Things, is the interfaces provided by
OneM2M. These two different structures were successfully
combined in a project for the cities of Busan in South Korea and
Santander in Spain (J. Hwang et al., 2019).
Since smart city objects are usually chosen for different needs,
searching for FIWARE compliance requirement or OneM2M
compliance requirement may cause problems in procurement. If
possible, it is recommended to create an architecture that will
support these two different structures together.
The recommended standards and frameworks that can
contribute to semantic interoperability are listed in Table 2.
3.2 Technical Interoperability
As mentioned before, technical interoperability generally copes
with data exchange between independent systems and
infrastructures. Smart cities should be capable of collecting,
analysing and distributing data, and smart city data should
remain re-usable (Brutti et al., 2019). Open standards and
protocols can be utilized as a key enabler to deal with technical
interoperability. If possible technical interoperability should be
ensured through the use of formal technical specifications.
Another interoperability barrier demonstrated by field
experience is vendor dependency. It is observed that some
solutions provided by well-established companies, especially in
information and communication technologies, lead to
monopolization and vendor dependency over time. For this
reason, it is recommended to emphasize the open technical
specifications and compliance with international standards.
In this context, standards that can be used for smart city
components are proposed in the SCIM. Dissemination of these
standards to all components and technology infrastructure will
contribute to the interoperability of smart cities. The
recommended standards are listed in Table 2 for smart
environment, smart transportation and smart energy
components, respectively.
Component
Technology
/Standard
Explanation
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVI-4/W5-2021
The 6th International Conference on Smart City Applications, 27–29 October 2021, Karabuk University, Virtual Safranbolu, Turkey
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93
Environmental
sensors
NTCIP
1204v03
National Transportation
Communications for ITS
Protocol Environmental Sensor
Station (ESS) Interface
Protocol is an interface
protocol for environmental
sensor systems. Although it
was created for the USA, it is
an open standard and is
suitable for different country
needs. If the definitions in this
standard are followed,
interoperability can be
increased and vendor
dependency can be reduced.
Traffic Data
Exchange
DATEX II
DATEX II is the electronic
language used in Europe for
the exchange of traffic
information and traffic data. It
is mostly used in center-to-
center communications.
SCADA/EMS
/DMS
IEEE 1815
Distribution Network Protocol
version 3 (DNP3) is the
American version of IEC
60870-5 developed as a
SCADA / EMS / DMS
standard by a user group to
meet the needs of North
American electrical
installations for transmission
and distribution applications. It
can be used for other industries
such as water, wastewater, oil,
gas and transportation.
Table 2. Recommended Standards for Specific Smart City
Domains
3.3 Organizational Interoperability
SAP was prepared with a common sense of the smart city
ecosystem of Turkey, including public institutions and
organizations, local governments, private sector, non-
governmental organizations and universities.
Within the scope of the preparation studies lasting 10 months;
policy documents and relevant legislation were examined,
workshops and focus group meetings were held and large-scale
surveys applied to local governments. In SAP, the roles of all
public institutions, local governments and universities are
defined for a total of 26 actions within the concept of smart
cities.
It is considered that identifying the definitions of duties and
responsibilities will serve for organizational interoperability by
accelerating action-based inter-institutional work and avoiding
authority confusion in the future.
Moreover, smart city maturities of municipalities are being
assessed and reported annually so the achievements of
municipalities within the scope of their responsibilities for
smart city transformation are being monitored and suggestions
for the improvement of the maturity level are provided
(Bayraktar et al., 2020).
4. CONCLUSIONS
The population of cities is increasing day by day, and the smart
city approach stands out as a useful concept in terms of cities'
ability to cope with the pressure caused by the population
growth. However, the fact that smart city systems are generally
created for project-based purposes causes smart city
applications and the infrastructures used by these applications to
be established independently and isolated from each other.
In order to provide interoperability by bringing a holistic
perspective to smart city policies at the national level, to
prioritize investments in line with the determined policies and to
ensure that the investments are implemented with the right
projects and activities, SAP has been published in December
2019 (Bayar et al., 2020). With SCIM, existing frameworks and
standards have been proposed that will contribute to the work of
all smart city stakeholders and has been prepared to cope with
interoperability issues rather than introducing new standards
and models. SCIM addresses interoperability under three main
topics: semantic interoperability, technical interoperability and
organizational interoperability.
Within this paper, initially, these interoperability terms and their
necessity for the smart city ecosystem is discussed. Then, the
contributions made to the ecosystem in terms of semantic,
technical and organizational aspects with SCIM is mentioned.
Technical interoperability, as mentioned before, can be defined
as data exchangeability between separate systems and it can be
provided with specific standards. Hence, technical standards are
recommended for smart city components within the scope of
SCIM.
Since technical interoperability is about data exchange,
semantic interoperability deals with the meaning of data. As for
semantic interoperability, two semantic models that can be
directly called "Smart Cities Interoperability Models” have been
identified and recommended.
One of the two detected smart cities interoperability models is
PAS 182 & ISO/IEC 30182 – Smart City Concept Model. This
model is a theoretical study that can address almost all vertical
areas of the smart city. Another semantic study is the
SAREF4CITY model. The requirements of this model are built
on three usage scenarios (e-Health and Smart Park, Air Quality
Monitoring and Mobility, Street Lighting). Since this model
includes application-oriented scenarios, it is understood that
there is no general model like PAS 182. However, since it is
based on the main applications of smart cities, its practical value
is quite high. It is also possible to use SAREF4CITY directly
rather than a mapping mechanism such as PAS 182, as it
contains class structures that software can directly reference.
Essentially, even if these two models overlap to a certain extent,
they are far from being alternatives to each other.
In the context of organizational interoperability, all institutions
and organizations within the smart city ecosystem at the
national scale and their duties and responsibilities within the
scope of SAP have been determined. Thus, conflicts of
authorities are prevented and a contribution has been made to
the organizational interoperability of smart cities.
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XLVI-4/W5-2021
The 6th International Conference on Smart City Applications, 27–29 October 2021, Karabuk University, Virtual Safranbolu, Turkey
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94
This study contributes to the literature on how to deal with
interoperability problems for smart cities on a national scale. As
future work, interoperability issues will be addressed in the
context of Reference Architectural Model of Interoperability of
Turkey (RUMI).
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The 6th International Conference on Smart City Applications, 27–29 October 2021, Karabuk University, Virtual Safranbolu, Turkey
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