Introduction to Visual Analytics by an Example

Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Aidan Slingsby, Cagatay Turkay and Stefan Wrobel
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Natalia Andrienko: Fraunhofer Institute Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven
Gennady Andrienko: Fraunhofer Institute Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven
Georg Fuchs: Fraunhofer Institute Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven
Aidan Slingsby: City, University of London, Northampton Square, Department of Computer Science
Cagatay Turkay: University of Warwick, Centre for Interdisciplinary Methodologies
Stefan Wrobel: Fraunhofer Institute Intelligent Analysis and Information Systems IAIS, Schloss Birlinghoven

Chapter Chapter 1 in Visual Analytics for Data Scientists, 2020, pp 3-25 from Springer

Abstract: Abstract An illustrated example of problem solving is meant to demonstrate how visual representations of data support human reasoning and deriving knowledge from data.We argue that human reasoning plays a crucial role in solving non-trivial problems. Even when the primary goal of data analysis is to create a predictive model to be executed by computers, this cannot be done without human reasoning and derivation of new knowledge, which includes understanding of the analysis subject and knowledge of the computer model built. Reasoning requires conveying information to the human’s mind, and visual representations are best suited for this. Visual analytics focuses on supporting human analytical reasoning and develops approaches combining visualisations, interactive operations, and computational processing. The underlying idea is to enable synergistic joint work of humans and computers, in which each side can effectively utilise its unique capabilities. The ideas and approaches of visual analytics are therefore very relevant to data science.

Date: 2020
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DOI: 10.1007/978-3-030-56146-8_1

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