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Methods Towards Create A Business Intelligence Webinternet Website In Sharepoint 2010
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Received: 15 April 2021 / Revised: 12 May 2021 / Accepted: 14 May 2021 / Published: 17 May 2021
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(This article is from the Special Issue Smart City Innovation and Resilience in the Era of Artificial Intelligence)
The connection between urban services, the fragmentation of urban data, and the need for multiple evaluations and decisions for urban sustainability require new solutions to solve these problems. this difficulty. Ontologies have become effective and useful tools for practitioners to develop applications that require information and process interactions, big data management, and the use of reason of knowledge. We investigate how and where ontologies have been used to support smart city services and we provide a general overview of what issues have been addressed and what has been achieved so far with the paper. request ontology. For this purpose, we have done a complete literature review to identify ontologies, and methods and technologies that ontologies play an important role in the creation of a smart city. no. As a result of the review process, we also presented a classification of the sub-domains of the city mentioned by the ontologies we found, and the research problems that were considered now from the scientific community. We highlight those semantic technologies that have been found to be most effective in developing the smart city concept and, finally, discuss in more detail some open issues.
Smart city; smart energy; smart home; urban planning; crisis management; smart health; smart service; a strong city; ontology; semantic machine
The smart city is a fuzzy concept that includes both the city’s services and the technology that enables them [1]. A smart city is a complex cyber-socio-technical system [2] in which people, cyber artifacts, and systems interact together for the purpose of achieving goals related to living in city. This process is supported by services for monitoring and awareness of the construction of urban conditions by sensing anthropic and environmental phenomena, such as traffic and weather, and by analyzing and gathering information. In addition, technological services dedicated to fulfilling the needs of citizens and protecting their lives also appear, regarding, for example, the protection of the environment circulation and important defense, public safety, and economy. According to [3], the precondition for creating a smart city is the construction of sectoral applications, which encompass the construction of wireless infrastructures, smart buildings, smart transportation, smart public services, social management , smart city management, smart healthcare, green. city, and smart tourism. Another perspective of the smart city is developed by Chourabi et al. [4], which advocates focusing on the effectiveness of management and organization, technology, governance, the context of law, people and communities, business, infrastructure, and the natural environment.
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The connection between the concept of the smart city and the technology has been treated by many studies and analysis of data from different perspectives. Among them, we mention intelligent learning cites from big data control perspective [5, 6, 7], those from the perspective of smart city services and platforms [8, 9], those from cognitive applications [10, 11 , 12], and those from specific applications such as recommendations [1] and risk management [13].
According to Silva et al. [14], sustainability is one of the challenges for the implementation of the smart city as it is linked to a better life. In particular, a sustainable city is able to support the balance of the ecosystem with, respectively, infrastructure and management, energy and climate change, pollution and waste, and, finally, health, economic and social problems. In order to achieve it, decision-makers must deal with the complexity and variety of urban knowledge and information by using knowledge tools to integrate the above mentioned in city.
The goal of our study is in the development and use of ontologies to create shared knowledge about the various aspects of the smart city and create a basis for the development of smart services, such as technologies for sustainable cities as shown by our findings. For this purpose, we have adopted a bottom-up method to retrieve both the functions of the ontologies and the smart city centers defined by them. An ontology is a clear representation of shared concepts [15, 16]. It is a conceptual model of a part of reality, which includes the interactive elements of a registered application [17]. This is a useful place to solve smart city challenges and the need for multi-disciplinary knowledge. The idea to create ontologies about the whole smart city, such as the Km4City ontology [18], or for ontology catalogs [19, 20], is in fact some steps towards this goal. However, the system-of-systems view of the smart city hinders the possibility of having a unique and complete ontology to cover various technologies and specific applications. Moreover, during our analysis, we found that many sectoral ontologies have been created, but several of them are not available in the public as artifacts, or they have not been preserved in time (for example as, some of those linked from [19]). In addition, our work shows that there is a need for a rigorous study: which should be used now, what knowledge of ontologies is presented in the data representation, and what kind of ontology can be used explained by the research community to help improve the economy. smart city services.
More specifically, the purpose of the current work is to answer the following research questions through a qualitative literature review. (RQ1) How do smart city sectors ontologies, semantic methods, and semantic technologies are used today? (RQ2) To which technologies ontologies, semantic methods, and semantic technologies provide added value? (RQ3) For each of the above mentioned, which are the problems encountered, and the most affected, the semantic process, and the semantic technology used? (RQ4) How the smart city sectors semantic technologies are used in general?
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The qualitative data analysis was carried out in a process that consisted of three phases: planning and design, data collection and semantic analysis, and implementation. The first stage is aimed at identifying the purpose of the audit, the scope of the audit, and the steps to be taken. The second is the purpose of identifying the steps to be taken and evaluating the data of the data provided by the SCOPUS database. The final stage concerns answering the above research questions and reporting the main findings.
The main observation behind the results of the data analysis is that the technological development supports the development of the smart city concept but it also opens new challenges and opportunities. Although several ontologies, projects, and applications have been created, especially for certain sectors, they do not provide all the solutions to the problems they solve. In addition, as the concept of the smart city has evolved from social and technological perspectives, there is a continuous space for information using the modern language used to promote decision making and smart city services.
The rest of the paper is organized as follows. Section 2 provides a detailed description of the literature review process. Chapter 3 presents the results of the analysis based on the smart city analysis. The answers to the research questions are summarized in Section 4. Finally, Section 5 provides conclusions and outlines some research issues for developers of smart city ontologies and applications.
In addition, given the breadth of the analysis, the paper has a structure to facilitate the reader, the findings related to the whole smart city can be read independently from the deep in content based results. Thus, readers interested in the general concepts of smart city ontologies and their semantic labels will focus on Chapter 1 and Chapter 4; readers want to know about the work
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