Digital Twin Modeling of Smart Cities

This paper presents a novel knowledge representation framework for smart city planning and management that enables the semantic integration of heterogeneous urban data from diverse sources. Currently, the combination of information across city agencies is cumbersome, as the increasingly available datasets are stored in disparate data silos, using different models and schemas for their description. To overcome this interoperability barrier, the presented framework employs a modular and scalable system architecture, comprising a comprehensive ontology capable of integrating data from various sectors within a city, a web ontology browser, and a web-based knowledge graph for online data discovery, mapping, and sharing across stakeholders. Linked Data, Semantic Web technologies, and ontology matching techniques are key to the framework's implementation. The paper ultimately showcases an application example, where the framework is used as a semantic enrichment mechanism in a platform for urban analytics, focusing particularly on human-generated data integration.

Big Data Research, 2017

Semantic Web technologies and in particular Linked Open Data provide a means for sharing knowledge about cities as physical, social, and technical systems, so enabling the development of smart city applications. This paper presents the case of Catania with the aim of sharing the lessons learnt, which can be reused as reference practices in other cases with similar requirements. The importance of achieving syntactic as well as semantic interoperability-as a result of transforming heterogeneous sources into Linked Data-is discussed: semantic interoperability must be solved at data level in order to ease the development of smart city applications. This claim is supported by showing how this issue impacts on the design of two smart city applications. As main contributions, the paper describes: (i) methods, procedures, and tools used for transforming heterogeneous sources into Linked Data; (ii) an ontology design pattern for modelling urban public transportation routes; (iii) methods, procedures and tools for ensuring semantic interoperability during the transformation process; (iv) the design of two smart city applications based on Linked Data. All produced data, models, and prototypes are publicly accessible online.

2015

of the presentation (<100 words) The presentation will expose experience and results regarding the integrated solutions around Km4City model, tools and roadmap. According to READY4SmartCities EC project, Km4City is the most complete open ontology for smart cities, The solution is supported by a set of tools for massive and parallel data harvesting (from static to real time data), quality improvement, reconciliation, reasoning, making decision, API, to pose queries services with visual tools. Km4City models and tools are adopted in Sii-Mobility SmartCity MIUR project, RESOLUTE H2020; and it is in place in the Florence and Tuscany Area. Extended abstract of the presentation (at most 2 pages in 11pt A4 format) Despite the huge work performed by Public Administrations (PAs) on producing and publishing open data they are not typically semantically interoperable each other and neither with the many private data available in the city. Open data coming from PAs contains information about...

2017

The meaning of the word “city” has evolved since the first urban civilization was labeled as such more than 5,000 years ago. The concept of Smartness in Cities appeared initially because of the advancements in information technology; now cities are working diligently towards being considered “Smart”. However, the term Smart City is still conceptually vague and sometimes biased towards the use of information technology, and not on the city. This article a) presents an ontological framework of Smart City which is logically constructed but grounded in the literature of Smart Cities, and b) maps 373 journal articles— published in 2016 on the topic “smart city”—onto the framework. The mapping reveals that Smart City research in 2016 mainly focuses on the Smart part of the framework, specifically the structural elements, while the City part remains largely unexplored.

Journal of Visual Languages & Computing, 2014

Presently, a very large number of public and private data sets are available around the local governments. In most cases, they are not semantically interoperable and a huge human effort is needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity and reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to smart-city ontology and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users. The paper presents the process adopted to produce the ontology and the knowledge base and the mechanisms adopted for the verification, reconciliation and validation. Some examples about the possible usage of the coherent knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection.

Creative City Design, 2024

In any society, software designed for a smart city in an environment based on the Internet of Things (IoT), provide smart urban models and user requirements for a better life and citizens' interaction with this smart city. However, the existing requirements extracting methods, due to several reasons like integration, interoperability, preventing data redundancy, possible interference and lack of integration and semantic queries, are not suitable and the mentioned problems are usually visible in some of these software systems. This article presents a comprehensive ontology of the smart city at the level of the existing meta-classes along with the way of inheritance and cooperation of these classes to integrate, prevent data redundancy and semantic query capability by using the experts' opinions. The classes required for the construction of this ontology were first collected by the snowball method from the urban target community and then refined and finalized by the Delphi method using the opinions of experts including university professors, industrial and business owners, as well as city officials. For the first time, three major classes are embedded in this model as super classes that all classes can inherit from. Thus, the framework presented in this article, while covering various aspects of a smart city, can be used to determine the software classes of a smart city, including high level classes and most important sub-classes, along with the localization capability for each community based on priorities of that community.

Computers, Environment and Urban Systems, 2000

Cooperation of information systems is essential for providing decision support for urban management applications. This involves sharing data across collections of the heterogeneous information systems that are used to manage large urban infrastructures. The objective of this work is to de®ne a spatial ontology to describe key features of urban applications, providing a foundation for semantic reconciliation among heterogeneous spatial information sources. We propose a multi-layered ontologies de®nition framework consisting of ontology layers which are composed of a generic functional structure and one or more domain ontologies. The functional structure embodies general ontological concepts described as abstract data types. The domain ontologies are created by specializing the properties and constraints of the functional structure. Inter-ontology relationships are de®ned to integrate information across functional ontological layers and used to query multiple domain ontologies. #

Presently, a very large number of public and private data sets are available around the local governments. In most cases, they are not semantically interoperable and a huge human effort is needed to create integrated ontologies and knowledge base for smart city. Smart City ontology is not yet standardized, and a lot of research work is needed to identify models that can easily support the data reconciliation, the management of the complexity and reasoning. In this paper, a system for data ingestion and reconciliation of smart cities related aspects as road graph, services available on the roads, traffic sensors etc., is proposed. The system allows managing a big volume of data coming from a variety of sources considering both static and dynamic data. These data are mapped to smart-city ontology and stored into an RDF-Store where they are available for applications via SPARQL queries to provide new services to the users. The paper presents the process adopted to produce the ontology and the knowledge base and the mechanisms adopted for the verification, reconciliation and validation. Some examples about the possible usage of the coherent knowledge base produced are also offered and are accessible from the RDF-Store and related services. The article also presented the work performed about reconciliation algorithms and their comparative assessment and selection.

Digital Twins are becoming fundamental tools to monitor the status of entities, predict their future evolutions, and simulate alternative scenarios to understand the impact of possible changes. More recently, Digital Twin solutions have been applied in the context of Smart Cities. Thanks to the large deployment of sensors, together with the increasing amount of information available for municipalities and government organizations, it is possible to build wide virtual reproductions of urban environments including structural data and real-time information that can undoubtfully help city councils and decision makers to face future challenges in the urban development and improve the citizen quality of life. In this paper, the Snap4City Smart City Digital Twin framework is presented, which is capable to respond to requirements identified in recent literature and by international forums. The proposed architecture provides an integrated solution for data gathering, indexing, computing, and...

This paper addresses the problem of low impact of smart city applications observed in the fields of energy and transport, which constitute high-priority domains for the development of smart cities. However, these are not the only fields where the impact of smart cities has been limited. The paper provides an explanation for the low impact of various individual applications of smart cities and discusses ways of improving their effectiveness. We argue that the impact of applications depends primarily on their ontology, and secondarily on smart technology and programming features. Consequently, we start by creating an overall ontology for the smart city, defining the building blocks of this ontology with respect to the most cited definitions of smart cities, and structuring this ontology with the Protégé 5.0 editor, defining entities, class hierarchy, object properties, and data type properties. We then analyze how the ontologies of a sample of smart city applications fit into the overall Smart City Ontology, the consistency between digital spaces, knowledge processes, city domains targeted by the applications, and the types of innovation that determine their impact. In conclusion, we underline the relationships between innovation and ontology, and discuss how we can improve the effectiveness of smart city applications, combining expert and user-driven ontology design with the integration and orchestration of applications over platforms and larger city entities such as neighborhoods, districts, clusters, and sectors of city activities.