Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)

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Ontology-Based Knowledge Modeling of Muli-factors for Severe Weather Risks in Snow Sports

Authors
Shuangfeng Wei1, Xiaobo Sun1, Shaobo Zhong2, *
1School of Geomatics and Urban Spatial Information, Beijing University of Civil Engineering and Architecture, Beijing, China
2Beijing Research Center of Urban Systems Engineering, Beijing, China
*Corresponding author. Email: zhongshaobo@gmail.com
Corresponding Author
Shaobo Zhong
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-064-0_100How to use a DOI?
Keywords
Severe weather; Risk management; Knowledge model; Ontology; Snow sports
Abstract

With the frequent occurrence of severe weather events in winter snow sports, it is important to ensure the agility of response to meteorological emergencies and the intelligence of decision making. To solve the semantic heterogeneity of risk information and insufficient knowledge representation related to severe weather in snow sports, we proposed a knowledge modeling approach driven by ontology to integrate multi-level meteorological risk elements, and constructed a relatively complete knowledge model of severe weather risk. This study found that the unified expression of decentralized concepts and semantic relations within the domain improved the current normalized description of hazard factors and risk emergency for severe weather events in snow sports, providing theoretical support for meteorological risk prediction and emergency response for the upcoming 2022 Beijing Winter Olympics.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
978-94-6463-064-0
ISSN
2589-4900
DOI
10.2991/978-94-6463-064-0_100How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Shuangfeng Wei
AU  - Xiaobo Sun
AU  - Shaobo Zhong
PY  - 2022
DA  - 2022/12/27
TI  - Ontology-Based Knowledge Modeling of Muli-factors for Severe Weather Risks in Snow Sports
BT  - Proceedings of the 2022 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022)
PB  - Atlantis Press
SP  - 974
EP  - 982
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-064-0_100
DO  - 10.2991/978-94-6463-064-0_100
ID  - Wei2022
ER  -