Dataset for Qualitative investigation of data-driven decision making within a control room for disaster monitoring and early-warning in Brazil

With the emergence of big data and new data sources, a challenge posed to today's organizations consists of identifying how to align their decision-making and organizational processes to data that could help them make better-informed decisions. This paper presents a study in the context of disaster management in Brazil that applies oDMN +, a framework that connects decision-making with data sources through an extended modeling notation and a modeling process. The study results revealed that the framework is an effective approach for improving the understanding of how to leverage big data in the organization's decision-making

A qualitative analysis of the early warning process in disaster management

Early warning systems are an important means of improving the efficiency of disaster response and preparedness. However, in its analysis of the technological aspects of the infrastructure, the literature has failed to carry out an investigation of early warning process. This paper has sought to take a step toward understanding this issue by carrying out a qualitative analysis of the early warning process in disaster management. This has involved participatory observations and conducting interviews with practitioners from the National Center for Monitoring and Early Warning of Natural Disasters (CEMADEN). The results have shown that this research area is a promising way of increasing efficiency and reducing the response time to warnings. This might be achieved by conducting a process analysis, which could provide evidence and information about bottlenecks or investigate the misuse of information systems or tasks by the players involved

Disasters are never natural: Emerging media to map lives and territories at risk

Disasters are not natural; they occur as communities occupy spaces that are pre- dictably dangerous and exposed to natural and anthropogenic hazards. Societies can invest resources to mitigate and prepare for these extreme events and organize their territories and where people live in ways that place those with the least resources at the most risk. Safe infrastructures, fast response during an emergency, resources for reconstruction, and the ability to create safe spaces are unequally distributed within cities, regions, countries, and the world. Some of the most vulnerable communities live in places that face multiple hazards with few resources to challenge rare but devastating events like fires, landslides, and earthquakes. It is in these territories where collaborative systemic interventions that integrate as many voices as possible are necessary. It is in these places where mental health interventions cannot be iso- lated from urban planning or the strengthening of community resilience