Early warning contributes to reduce the damages when updated and reliable information is collected before a hazard happens, so that early response can be orchestrated. Integrating volunteers and citizens into data collection can help to get a better picture of the situation, since they are intelligent sensors equipped with mobile devices that can be used everywhere to collect and share information. In this paper we discuss the architecture of a digital knowledge ecosystem to support such participatory early warning process. This DKE deals with a complex knowledge coproduction problem by separating information according to its meaning, quality and reliability. The use of technological tools is aimed at supporting a self-organized, scalable and sustainable process. The different agents and interactions involved and some design requirements are drawn from a use case in the context of the Spanish early warning system.
CITATION STYLE
Díaz, P., Onorati, T., & Aedo, I. (2017). A digital knowledge ecosystem to increase participation in emergency warnings and alerts management. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10232 LNCS, pp. 700–711). Springer Verlag. https://doi.org/10.1007/978-3-319-57186-7_50
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