Towards visual data science - An exploration

Abstract

Visual perception is one of the most essential abilities for humans. This ability allows us to discover the world around us and to understand interdependencies with regard to both global context and particular concrete problem statement. We present in this paper an exploration of visualization and visual analytics approaches. Thereby, we focus on the field of data science with data-centric analytic methods and applications. Data science is closing the gap between visualization techniques, traditional hypothesis-driven methods and processing of mostly huge, heterogeneous and noisy data. A combination of smart visualization, advanced analytical methods and additional (domain) knowledge, mostly provided by humans, makes it possible to gain insights and discover new opportunities for problem solving.