From Tech-Solutionism to Community-Centred Data Capability for Disaster Preparedness
Bibliographic Data
| ID | 22009479 |
|---|---|
| Authors | A Mccosker (0000-0003-0666-3262, Swinburne University of Technology), Yong-Bin Kang (0000-0002-0120-2582, Swinburne University of Technology), Frances Shaw (0000-0001-8690-653X, Swinburne University of Technology), K Albury (0000-0001-9043-8126, Swinburne University of Technology) |
| Year | 2025 |
| Publication date | 2025-01-02 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | AoIR Selected Papers of Internet Research (JOURNAL) |
| Journal identifiers | ISSN: 2162-3317 • E-ISSN: 2162-3317 |
| Publisher | University of Illinois Libraries (PUBLISHER) |
| DOI | 10.5210/spir.v2024i0.14000 |
| OpenAlex | W4407195777 |
| Language | EN |
The urgency of enhancing community resilience in the face of escalating disasters necessitates a shift in disaster preparedness strategies. This paper presents a novel approach developed in collaboration with the Australian Red Cross, focusing on community-centred data practices for disaster resilience. Recognising the limitations of traditional digital humanitarianism, which largely relied on crowdsourcing and social platform data, our project shifts the paradigm towards empowering communities with data capabilities. We developed a Community Resource Mapping Pipeline, and a prototype platform to map community resources and strengths, emphasising community-led processes and local data capability development to improve local disaster preparedness and response. Our organisational participatory approach involved workshops with stakeholders to co-shape research questions and platform design within a human-centred framework. Our prototype demonstrates the potential of community-led data capability building in enhancing disaster preparedness, underscoring the importance of involving communities in both data collection and decision-making
Business · Computer security · Data science · Disaster preparedness · Emergency management · Political science · Preparedness · Big Data and Business Intelligence · Computer Science
| Highly cited | No |
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