• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.9
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• pp.290-298
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• 2019

This study investigated a total of 22 types (15 types of natural disasters and seven types of social disasters) of disaster and safety data based on the National Daily Situation Report, Disaster Yearbook and annual Disaster Annals issued by the Ministry of Public Administration and Security. Disaster safety data were collected from the daily situation report of MOIS (Ministry of the Interior and Safety). The number of total data cases were 1,760, of which 656 were natural disasters and 1,104 were social disasters. The disasters were then patternized according to their characteristics. The patterning was conducted to set up the disaster and safety data system designed to keep disaster situations under prompt and effective management. The study analyzed the data associated with the activities in the response and recovery stages according to the disaster type. Furthermore, based on the management activities performed with the flow of time following a disaster, this study classified and proposed disaster and safety data patterns to achieve effective disaster management work by analyzing the characteristics of a disaster and safety data and disaster and safety management procedures. Disasters of high similarity were classified by merging and deleting them. This was done to consider the scalability and mutual linkage so that it can be used in the establishment of national statistical data, such as the disaster annual report and disaster annuity.

• Journal of the Society of Disaster Information
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• v.20 no.2
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• pp.462-469
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• 2024

Purpose: This study aims to analyze data on disaster safety education for migrant youth and to examine the corresponding social perceptions. Method: Data on disaster safety education for migrant youth were collected and analyzed using Textom and Ucinet. The data used in the study were searched on portal websites from 2016 to 2023 using the keywords 'migrant youth+ disaster + safety education'. Result: The analysis results showed that 'education (306)' had the highest frequency, followed by 'safety (287)', 'school (97)', 'society (85)', and 'support (77)'. The keyword with the high degree of centrality, closeness centrality, and betweenness centrality were 'education', 'safety' and 'society'. 'Family' ranked higher in betweenness centrality than the rankings of frequency analysis, degree centrality and closeness centrality, indicating that 'family' plays a significant role as a mediator in the network of disaster safety education for migrant youth. Conclusion: By examining social awareness about disaster safety education for migrant youth, the findings will be used to develop policies and strategies for disaster safety education that consider the unique vulnerabilities of migrant youth in disaster situations.

• International Journal of Internet, Broadcasting and Communication
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• v.13 no.4
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• pp.154-168
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• 2021

The purpose of this study is to develop and validate the disaster safety awareness scale for high school students. For this purpose, the previously developed disaster safety awareness scale and related prior research was analyzed. Questionnaire data was collected from March 22 to May 25, 2021 from 1054 students (male: 569, female: 485) in the first, second, and third grades of 5 high schools in 3 cities. Through the process of revising, supplementing, and reviewing the items extracted through preliminary research and preliminary test together with experts and students, a final disaster safety awareness scale consisting of 24 items was developed. This scale consists of four sub-factors: 'disaster prevention', 'disaster response A', 'disaster response B', and 'disaster recovery'. Good reliability and validity were secured through exploratory and confirmatory analyses. The significance of this study is that it laid a basic and objective foundation for high school students' disaster safety awareness research by developing a validated scale in a situation where the development of disaster safety awareness scales for high school students was still insufficient. It can be used as useful data for fire safety education as well as a psychological measurement tool for fostering fire safety awareness.

• The Journal of Information Systems
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• v.27 no.2
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• pp.175-196
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• 2018

Purpose The purpose of this study is to identify problems of current educational facility data management and recommend a standardized terminology classification system as a solution. In addition, the research aims to present a preemptive and integrated disaster and safety management framework for educational facilities by seeking efficient business processes through secured data quality, systematic data management, and external data linkage and analysis. Design/methodology/approach A terminology classification system has been established through various processes including filtering and analysis of related data including laws, manuals, educational facilities accidents, and historical records. Furthermore, the terminology classification system has been further reviewed through several consultations with experts and practitioners. In addition, the accumulated data was refined according to the established standard terminology and an Excel database was developed. Based on the data, accident patterns occurred in educational facilities over the past 10 years were analyzed. Findings In the study, a template was developed to collect consistent data for the standardized disaster and safety management terminology classification system in educational facilities. In addition, the standardized data utilization methods are presented from the viewpoint of 'education facility disaster safety data management', 'data analysis and insight', 'business management through data', and 'leaping into big data management'.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.80-86
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• 2021

The purpose of this study is to diagnose the level of disaster safety perception (disaster safety importance, accident possibility, personal safety, and regional safety) of local residents, and to analyze the impact of individual and accident cause characteristics. The analysis method used multiple regression analysis, and the main analysis results are as follows. First, disaster safety importance and accident possibility were higher as residents who had experience in safety education and were willing to visit the safety experience center in the province. Second, disaster safety importance was higher as the cause of the accident was the lack of response 119 and police. And accident possibility was higher as the cause of the accident was the lack of prior treatment by the state and local governments. Third, personal safety and regional safety were higher for men, and especially personal safety was lower as residents with children. The results of this study can be used as basic data for establishing regional customized disaster safety policies based on the perception of local residents, who are policy consumers.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.83-90
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• 2019

In addition to the proliferation of intelligent information technology, the field of disaster management is being approached from a multifaceted perspective. In particular, as the interest in establishing a disaster safety management system using data increases, there is an increasing need for a large amount of big data distribution generated in real time and a systematic management. Furthermore, efforts are being made to improve the quality of data in order to increase the prevention effect of disasters through data analysis and to make a system that can respond effectively and to predict the overall situation caused by the disasters. Disaster management should seek both precautionary measures and quick responses in the event of a disaster as well as a technical approach to establishing governance and safety. This study explores the policy implications of the significance and structure of disaster safety management governance using data.

• International Journal of Internet, Broadcasting and Communication
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• v.14 no.2
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• pp.171-182
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• 2022

In this study, by classifying latent groups for disaster safety awareness focusing on the four sub-factors of the developed disaster awareness scale of high school students, the characteristics of each group were examined, and the differences between latent classes according to inter-individual differences were investigated. As a result of analysis based on the data of a total of 1054 high school students, the disaster safety awareness of high school students was classified into three latent groups. Each latent group was named 'High Safety Awareness Type(SAT)', 'Normal SAT', and 'Low SAT' according to its characteristics. In all four fire safety awareness sub-factors, 'High SAT', which had a high score, accounted for 56.5% of the total, and 'Normal SAT', which had a moderate score in the sub-factors, had the lowest ratio at 20.3%. There were no significant differences by gender, grade, and academic achievement of the latent group. These results are not only meaningful as the first study of the latent profile analysis of high school students on disaster safety awareness, but also help to identify the characteristics of individuals in each latent group with more subdivisions and provide useful data for disaster safety awareness education according to individual differences. The implications of this study and suggestions for follow-up studies were discussed.

• Journal of the Society of Disaster Information
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• v.16 no.4
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• pp.682-690
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• 2020

Purpose: This study builds a database by collecting and refining disaster occurrence data and real-time weather and atmospheric data. In conjunction with the public data provided by the API, we propose a service model for the Big Data-based Urban Safety Index. Method: The plan is to provide a way to collect various information related to disaster occurrence by utilizing public data and SNS, and to identify and cope with disaster situations in areas of interest by real-time dashboards. Result: Compared with the prediction model by extracting the characteristics of the local safety index and weather and air relationship by area, the regional safety index in the area of traffic accidents confirmed that there is a significant correlation with weather and atmospheric data. Conclusion: It proposed a system that generates a prediction model for safety index based on machine learning algorithm and displays safety index by sector on a map in areas of interest to users.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.43-57
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• 2022

In this paper, we propose a method of analyzing research papers published by researchers belonging to university departments in the field of disaster & safety for the scientometric analysis of the research status in the field of disaster safety. In order to conduct analysis research, the dataset constructed in previous studies was newly improved and utilized. In detail, for research papers of authors belonging to the disaster prevention and safety engineering type department of domestic universities, institution identification, cited journal identification of references, department type classification, disaster safety type classification, researcher major information, KSIC(Korean Standard Industrial Classification) mapping information was reflected in the experimental data. The proposed method has a difference from previous studies in the field of disaster & safety and data set based on related keyword searches. As a result of the analysis, the type and regional distribution of organizations belonging to the department of disaster prevention and safety engineering, the composition of co-authored department types, the researchers' majors, the status of disaster safety types and standard industry classification, the status of citations in academic journals, and major keywords were identified in detail. In addition, various co-occurrence networks were created and visualized for each analysis unit to identify key connections. The research results will be used to identify and recommend major organizations and information by disaster type for the establishment of an intelligent crisis warning system. In order to provide comprehensive and constant analysis information in the future, it is necessary to expand the analysis scope and automate the identification and classification process for data set construction.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.3
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• pp.345-352
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• 2020

Forest fires generate many types of risk as well as a wide and varied range of damage. Various studies and systems have emerged in response to wildfire disasters. International wildfire disaster safety management systems apply advanced technologies such as utilizing big data, GIS-based systems, and decision-making systems. This study analyzes South Korea's and other countries' forest fire disaster safety management systems, and suggests alternatives for wildfire disaster safety management in Korea. First, a means of integrating information, including field information, obtained by domestic agencies is proposed. Second, a method of applying big data to the disaster response system is proposed. Third, a decision-making system is applied to an existing GIS-based system. When applying the above countermeasures to Korea's existing disaster safety management system, various information and data can be visualized and thus more easily identified, leading to more effective decision-making and reduced fire damage.