• Journal of the Society of Disaster Information
• /
• v.7 no.2
• /
• pp.140-150
• /
• 2011

Life Environment is rapidly changing and large scale disasters are increasing from the global warming. Although the disaster repair resources are deployed to the disaster fields, the prevention of the disasters is the most effective countermeasures. the disaster sign data is based on the rule of Heinrich. Automatic extraction of the disaster sign data from the web is the focused issues in this paper. We defined the automatic extraction processes and applied information, such as accident nouns, disaster filtering nouns, disaster sign nouns and rules. Using the processes, we implemented the disaster sign data management system. In the future, the applied information must be continuously updated, because the information is only the extracted and analytic result from the some disaster data.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.20 no.9
• /
• pp.290-298
• /
• 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
• /
• v.7 no.3
• /
• pp.220-228
• /
• 2011

Disaster sign data is confirmed data by the experts to the collected data from web and users. In this paper, we focused to make the risk scores to the data based on ontology technology. To analyse the data, first of all, we defined the ontological structure for 4 kinds of disaster types which consists of the bridges, workplaces, buildings, and walls. Base on the ontologies, collected the accidents examples, and then extract the risk rules from the examples. The rules are adjusted with frequencies and weights, and managed to the ontology DB. The rules apply to the disaster sign data, and then calculates the risk scores. It plays role of the index to the risk rates. The disaster sign data management system was implemented and the rules were verified to the system. Because the quality of the risk scores to the disaster sign data depends on the data of the accidents examples's qualities, we assure that the system's performance will be monotonic increasing following up the data upgrades. Continuously, data management is needed. Also the quality control of the rules are needed.

• Ecology and Resilient Infrastructure
• /
• v.6 no.4
• /
• pp.236-242
• /
• 2019

In this study, we developed the system that can collect and store environmental disaster data into the database and use it for environmental disaster management by converting structured and unstructured documents such as images into electronic documents. In the 4th Industrial Revolution, various intelligent technologies have been developed in many fields. Environmental disaster information is one of important elements of disaster cycle. Environment disaster information management refers to the act of managing and processing electronic data about disaster cycle. However, these information are mainly managed in the structured and unstructured form of reports. It is necessary to manage unstructured data for disaster information. In this paper, the intelligent generation approach is used to convert handout into electronic documents. Following that, the converted disaster data is organized into the disaster code system as disaster information. Those data are stored into the disaster database system. These converted structured data is managed in a standardized disaster information form connected with the disaster code system. The disaster code system is covered that the structured information is stored and retrieve on entire disaster cycle. The expected effect of this research will be able to apply it to smart environmental disaster management and decision making by combining artificial intelligence technologies and historical big data.

• Journal of Wellbeing Management and Applied Psychology
• /
• v.6 no.4
• /
• pp.51-61
• /
• 2023

Purpose: This study aims to provide basic data to improve disaster nursing competency by identifying nursing students' disaster awareness, disaster preparedness, and disaster nursing competency and confirming the relationship among them. Research design, data, and methodology: The subjects of this study were 310 students attending the Department of Nursing at E University in Gyeonggi-do, and the data was collected from April 13 to May 24, 2023. Results: Disaster awareness averaged 72.91±7.46 points, disaster preparedness averaged 2.82±2.81 points, and disaster nursing competency averaged 44.11±10.76 points. Disaster preparedness and disaster nursing competency were significantly higher in subjects with disaster nursing education experience than in those without experience. Disaster awareness showed a significant positive correlation with disaster preparedness (r=.20, p <.001), and also with disaster nursing competency (r=.37, p <.001). Disaster preparedness showed a significant positive correlation with disaster nursing competency (r=.49, p <.001). It was found that the disaster nursing competency was high when the disaster awareness (B=0.472, p<.001), and the disaster preparedness (B=1.561, p<.001) was high. Conclusions: The results show it is possible to improve students' disaster nursing competency by strengthening education on disaster awareness and disaster preparedness. Thus, specific efforts and future research are needed to develop disaster nursing education.

• Journal of Information Science Theory and Practice
• /
• v.9 no.4
• /
• pp.35-49
• /
• 2021

In a situation where there are multiple diverse datasets, it is essential to have an efficient method to provide users with the datasets they require. To address this suggestion, necessary datasets should be selected on the basis of the relationships between the datasets. In particular, in order to discover the necessary datasets for disaster resolution, we need to consider the disaster resolution stage. In this paper, in order to provide the necessary datasets for each stage of disaster resolution, we constructed a disaster type and disaster management process ontology and designed a method to determine the necessary datasets for each disaster type and disaster management process step. In addition, we introduce a method to determine relationships between datasets necessary for disaster response. We propose a method for discovering datasets based on minimal relationships such as "isA," "sameAs," and "subclassOf." To discover suitable datasets, we designed a knowledge exploration model and collected 651 disaster-related datasets for improving our method. These datasets were categorized by disaster type from the perspective of disaster management. Categorizing actual datasets into disaster types and disaster management types allows a single dataset to be classified as multiple types in both categories. We built a knowledge exploration model on the basis of disaster examples to ensure the configuration of our model.

• Korean Journal of Remote Sensing
• /
• v.38 no.6_3
• /
• pp.1789-1803
• /
• 2022

With the increase of data and the development of AI technology, the strategies and policies related to integrated data are being actively established to increase the usability of data all over the world. Recently, in the research field, infrastructure projects and management systems are being prepared to utilize research data at the initiative of the government. Also, in Korea, platforms for searching and sharing research data are being actively developed. The National Disaster Management Research Institute (NDMI) has been conducting extensive research on disaster & safety as a national institute, but data-oriented management and utilization are insufficient. Because it still lacks consistent data management systems, metadata for outcomes of research, experts on data and policies for utilization of data to research. In order to move to the data-based research paradigm, we defined the master plans and verified a target model for the integrated management and utilization of disaster & safety research data. In this study, we found out the need to establish differentiated data governance, such as data standardization and unification of the data management system, and dedicated organization for managing data, based on the necessity and actual demands of NDMI. In order to verify the effectiveness of the target model reflecting the derived implications, we intend to establish a pilot mode. In the future, major improvement measures to establish a disaster & safety research data management system will be implement.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.1
• /
• pp.411-417
• /
• 2024

In the event of a disaster, it is essential to establish a disaster recovery plan and disaster recovery system to minimize disruption to major IT infrastructure and provide continuous business services. In the process of building a disaster recovery system, data replication is a key element of data recovery to provide uninterrupted and continuous business services in the event of a disaster. The data replication method can be determined depending on the system configuration environment and disaster recovery goal level. In this paper, we present a method for determining a data replication method suitable for the configuration environment and disaster recovery target level when building a disaster recovery system. In addition, the replication method decision procedure is applied to build a disaster recovery system and analyze the construction results. After establishing the disaster recovery system, a test was conducted to determine whether the service was transferred to the disaster recovery center in a disaster situation and normal service was provided, and the results were analyzed. As a result, it was possible to systematically select the optimal data replication method during the disaster recovery system construction phase. The established disaster recovery system has an RTO of 3.7 hours for service conversion to the disaster recovery center to provide continuous business services, and the disaster recovery level, which was Tier 2, has been improved to the target level within 4 hours of RTO and RPO=0.

• Journal of the Korean Society of Safety
• /
• v.33 no.3
• /
• pp.65-70
• /
• 2018

Terrain data for disaster analysis in hazardous or disaster areas is not only important but also needs to be built quickly. In particular, the introduction of drones is in the early stages of research using drones in a variety of fields such as shooting, analyzing and managing hazardous areas. It is expected that drone will be faster, safer and more effective than existing data collection method in case of small scale disaster hazard area and disaster area where equipment or manpower input is difficult. Therefore, in this study, drone shooting was performed for hazardous areas in mountainous roads located in Samcheok city, Gangwon province, and ground reference points were measured by RTK-GPS. The measured data were converted into DSM (Digital Surface Model) data by coordinate correction using Pix4D postprocessing program and then applied to the analysis of the hazard area of mountainous area. As a result, it was shown that it is effective to identify the risk by using the basic terrain data obtained from the drones.

• Journal of Environmental Impact Assessment
• /
• v.16 no.5
• /
• pp.373-379
• /
• 2007

Natural hazards such as typhoon, flood, landslide affect both coastal and inland areas more often according to increasement of severe and unusual weather. To provide adequate coastal disaster mitigation strategies, coastal disaster prevention system using GIS is very useful. Application methods of digital map on this issue was discussed in this study. For developing of coastal disaster prevention system, the data structures related to disaster monitoring is needed to be revised for interdisciplinary framework. To improve the current coastal disaster mapping methods, GIS based new model for coastal disaster mapping was suggested. In this study, coastal GIS showed the attribute data and structures of coastal disaster mapping.