Representing and assessing distributed situation awareness in multi-agency disaster response: A hypergraph-based methodology
This paper introduces a novel hypergraph-based methodology for representing and assessing distributed situation awareness (DSA) in multi-agency disaster response. The fundamental ideas and motivations of our methodology stem from the following widely acknowledged understandings and phenomenons: (a) DSA’s representation should be approached from social, information and task dimensions; (b) DSA is one of the collective behaviors that emerge from the interactions; (c) the interactions in the real world are not pairwise. Our methodology delineates the collaboration, co-activation, and co-existence interactions among social, information, and task elements as higher-order interactions. We then construct these interaction systems using hypergraph-structured data derived from disaster response scenarios. Subsequently, these systems are encoded into hypergraphs, which are validated against our dataset and proven to be practical tools for depicting higher-order interaction patterns. Analytical techniques tailored to hypergraphs are applied, yielding insights intrinsic to hypergraphs regarding DSA in emergency response. Moreover, we integrate these interaction systems into a comprehensive framework that allows for the visualization and quantitative analyses of DSA evolution dynamics. We propose several indicators of evolution, discussing their trends and implications throughout the development of the emergency response. We locate the system deficiencies by revealing a mismatch between the positions of specific elements in the network and their functions. We also identify the saturation phase in the DSA evolution process. • We adopt distributed situation awareness in emergency response to disasters. • Distributed situation awareness is assessed by a hypergraph-based method. • A mismatch between the positions of elements and their functions has been revealed. • The evolution dynamics of distributed situation awareness have been studied.
Authors
- Xiaoling Guo (ORCID: https://orcid.org/0000-0002-8547-4285)
- Chong Gao (ORCID: https://orcid.org/0009-0008-9145-7140)
- Hui Jiang
Institutions
- University of Chinese Academy of Sciences (CN)
Publication Details
- Journal
- International Journal of Disaster Risk Reduction
- Published
- 2024-08-10
- DOI
- https://doi.org/10.1016/j.ijdrr.2024.104747
- Citations
- 2
- Primary Topic
- Complex Network Analysis Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.56
Funders
- National Natural Science Foundation of China