Knowledge Model for Disaster Dataset Navigation
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Korea Institute of Science and Technology Information
2021-12-01
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| Series: | Journal of Information Science Theory and Practice |
| Subjects: | |
| Online Access: | https://data.doi.or.kr/10.1633/JISTaP.2021.9.4.3 |
| Summary: | 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. |
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| ISSN: | 2287-9099 2287-4577 |