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

Use este identificador para citar ou acessar este item: http://dx.doi.org/10.5072/FK2/JQYQKQ

DOI:	http://dx.doi.org/10.5072/FK2/JQYQKQ
Título:	Dataset for Qualitative investigation of data-driven decision making within a control room for disaster monitoring and early-warning in Brazil.
Assunto:	Computer and Information Science;Earth and Environmental Sciences
Descrição:	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.
Autor(es):	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
Outros identificadores:
Fomento:	CNPq CAPES
Número do Projeto:
Termo de uso:
Data:	23-Ago-2018
Data de Disponibilização:	1-Ago-2019
Formato:	text/plain
Tipo:
Editora / Evento / Instituição:	Flavio Eduardo Aoki Horita
Idioma :
Aparece nas coleções:	Repositório de Dados de Pesquisa da Universidade Federal do ABC

Metabuscador de dados de pesquisa