
Disaster Risk Reduction (DRR) is a complex field in which a huge amount of data is used to plan preventive measures, get prepared to natural disasters, and effectively respond when they strike. This work focuses on the definition of a co-design methodology to integrate a crowdsourcing solution in the DRR processes. We define the proposed methodology, and implement it involving operators and experts in the DRR domain (crisis managers, technical services, first responders). We show how a participatory design approach helps in the design of a crowdsourcing solution that experts are willing to integrate into their DRR procedures.
© ACM, 2017. This is the author's version of the work. It is posted here by permission of ACM for your personal use. Not for redistribution. The definitive version was published in Q. N. Nguyen, A. Frisiello, and C. Rossi. 2017. Co-design of a Crowdsourcing Solution for Disaster Risk Reduction. In Proceedings of I-TENDER '17, Incheon, Republic of Korea, December 12, 2017, 6 pages. https://doi.org/10.1145/3152896.3152898
HCI design and evaluation methods, Human-centered computing
HCI design and evaluation methods, Human-centered computing
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 3 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
