Please use this identifier to cite or link to this item: http://dx.doi.org/10.5072/FK2/JQYQKQ
DOI: http://dx.doi.org/10.5072/FK2/JQYQKQ
Title: Dataset for Qualitative investigation of data-driven decision making within a control room for disaster monitoring and early-warning in Brazil.
Subject: Computer and Information Science;Earth and Environmental Sciences
Description: 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.
Authors: Flavio Eduardo Aoki Horita
URI: http://dx.doi.org/10.5072/FK2/JQYQKQ
https://dataverse.ufabc.edu.br/dataset.xhtml?persistentId=doi:10.5072/FK2/JQYQKQ
Other Identifiers:  
Sponsorship: CNPq
CAPES
Sponsor ID:  
Rights:  
Date: 23-Aug-2018
Available Data: 1-Aug-2019
Format: text/plain
Type:  
Publisher: Flavio Eduardo Aoki Horita
Language :  
Appears in Collections:Repositório de Dados de Pesquisa da Universidade Federal do ABC



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