Conclusion

Natalia Andrienko, Gennady Andrienko, Georg Fuchs, Aidan Slingsby, Cagatay Turkay and Stefan Wrobel
Additional contact information
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 14 in Visual Analytics for Data Scientists, 2020, pp 409-422 from Springer

Abstract: Abstract This chapter very briefly summarises the main ideas and principles of visual analytics, while the main goal is to show by example how to devise new visual analytics approaches and workflows using general techniques of visual analytics: abstraction, decomposition, selection, arrangement, and visual comparison.We take an example of an analysis scenario where the standard approaches presented earlier in this book do not work, and we demonstrate the possibility to construct a suitable new approach starting with abstract operations and then inventively elaborating these abstractions according to the specifics of the data and analysis tasks.

Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-56146-8_14

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DOI: 10.1007/978-3-030-56146-8_14

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