A Decision Support Systems and Visual Analytics Architectural Definition Methodology
Decision Support Systems (DSS) are growing over the years. Due to the need for information, DSS is taking advantage of the increased access to the Internet and increased use of smartphones as a means of massive data production. This large volume of data (big data) is making the market more competitive, which ultimately lead to more accurate decision-making. Here, Visual Analytics (VA) emerges as a means to allow better use and exploration in these data volumes. However, the implementation of VA in a DSS is not a trivial task, currently requiring implementation and evaluation methods. The present work aims to present a new methodology for the architectural definition of DSS that implements VA. This methodology will consist of a taxonomy, responsible for classifying and selecting architectural decisions in the context of the project, and an architectural definition process, comprising two software views (e.g., one for the DSS and another for the VA). For doing so, the project adopted Design Science for the definition and evaluation of artefacts, a systematic methodology for establishing the taxonomy, based by Nickerson et al. (2013) and, eventually, the architectural model "4+1" from Kruchten (1995). The main contribution of this project is to present a methodology capable of specifying the architectural design of a DSS implementing VA.