Bridging the gap between decision-making and emerging big data sources: An application of a model-based framework to disaster management in Brazil

Understanding the decision-making process in disaster risk monitoring and early-warning: A case study within a control room in Brazil

“…This conclusion is in line with previous works that investigated decision-making and human factors in different control rooms [9,29]. For overcoming this challenge, common people can provide reliable and accurate volunteered geographic information from vulnerable areas [17], which thus supplements traditional data collection tools and enhances decision-making in control rooms [20,1,34,19]. Findings of this work however show that as any other information, this should reflect the decision-makers' requirements, otherwise it may be useless or even misused.…”

“…The first stage in answering this question was achieved in our previous work when a preliminary version of the decision-making process was modeled by means of a standard modeling notation [21]. This version was later extended and refined in another work [19], which also sought to link the tasks of the decision-makers with existing data sources. This paper goes beyond the modeling and development of diagrams that described the decision-making process by interpreting the factors that could influence it.…”

“What is a Sociologist Doing Here?” An Unconventional People-Centered Approach to Improve Warning Implementation in the Sendai Framework for Disaster Risk Reduction

“…(3) partnerships with federal, state, and local agencies to exchange environmental data and information were formed; (4) computer scientists also developed a GIS visualization platform to receive these kinds of data; (5) people were hired to work in the monitoring room and to be part of the decisionmaking process in the warning chain, which also includes civil protection units at the federal, state, and municipal levels, as well as at-risk communities; (6) protocols for this warning chain were also necessary, especially because the roles and responsibilities of the organizations were not clear-the competition between governmental agencies (Lund 2006) was real; and (7) capacity building tutorials and educational materials on warning system implementation at local level were recognized as important, but there is no consensus about who is responsible for engaging people in warning system. Many of these steps and tasks were recommended in the warning system checklists published by the United Nations International Strategy for Disaster Reduction (UNISDR 2006a) and the World Meteorological Organization (WMO 2018); some barriers for their implementation were sporadically researched using questionnaires and interviews (Lumbroso et al 2016;Horita et al 2017Horita et al , 2018, but not the everyday practices and discourses of warning implementation during a period of time, as institutional ethnography permits. This article contributes to this debate, providing insights about the means of implementation of warning systems (Zia and Wagner 2015).…”

A Review of Studies on Participatory Early Warning Systems (P-EWS): Pathways to Support Citizen Science Initiatives

“…On a technological perspective, efforts have been concentrated on developing systems, methodologies, and approaches rather than understanding citizens' requirements or ways of better engaging citizens in EWS (Villagrán de León et al, 2006;Quansah et al, 2010;Kou and Wu, 2014;Horita et al, 2017). In contrast, practice and research still lack studies that investigate how citizens can be involved in citizen science to support early warning systems.…”