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

- An extended model-based framework connects decision-making to big data sources.
- A better understanding of decision-making is achieved with the framework.
- A modeling process is outlined for systematically using the framework in practice.
- Decision-making can be improved through the use of standard models and notations.
- Lessons were learned from a case study on a Brazilian disaster early-warning center.

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.