A Taxonomy of Visual Analytics in Decision Support Systems

• Gustavo Romão Gonzales Universidade Federal do ABC http://orcid.org/0000-0002-1784-8310
• Lívia Castro Degrossi Fundação Getúlio Vargas https://orcid.org/0000-0001-6897-1186
• Flavio Eduardo Aoki Horita Universidade Federal do ABC https://orcid.org/0000-0002-7138-9223

DOI: https://doi.org/10.5753/sbsi.2021.15358

Abstract

Decision Support Systems (DSS) are part of the daily life of all environments, acting in support of the decision-making process, assisting the data usage as a basis, enabling more efficient and advantageous decisions. The increase in the volume of digitally produced data brings countless opportunities and organizations have improved their DSS as a means of discovering new information hidden in this data. As a means of solving the problem of data overload with one of the difficulties, Visual Analytics (VA) is applied supporting use and exploration of this data. However, the implementation of VA in a DSS is not a trivial task, currently requiring development and evaluation techniques. The present work aims to present a VA taxonomy in SAD. To this end, the project adopted a systematic methodology for the establishment of taxonomy. The main contribution of this project is to present a taxonomy that can classify and describe the DSS architectures that implements VA.

Keywords: Taxonomy, Decision Support System, Visual Analytics, Software Engineering

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