Reliable visual analytics, a prerequisite for outcome assessment of engineering systems

Auer Ekaterina and Luther Wolfram and Weyers Benjamin: Reliable visual analytics, a prerequisite for outcome assessment of engineering systems. In: Acta cybernetica, (24) 3. pp. 287-314. (2020)

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Various evaluation approaches exist for multi-purpose visual analytics (VA) frameworks. They are based on empirical studies in information visualization or on community activities, for example, VA Science and Technology Challenge (2006-2014) created as a community evaluation resource to “decide upon the right metrics to use, and the appropriate implementation of those metrics including datasets and evaluators” 1 . In this paper, we propose to use evaluated VA environments for computer-based processes or systems with the main goal of aligning user plans, system models and software results. For this purpose, trust in VA outcome should be established, which can be done by following the (meta-)design principles of a human-centered verification and validation assessment and also in dependence on users’ task models and interaction styles, since the possibility to work with the visualization interactively is an integral part of VA. To define reliable VA, we point out various dimensions of reliability along with their quality criteria, requirements, attributes and metrics. Several software packages are used to illustrate the concepts.

Item Type: Article
Heading title: Uncertainty modeling, software verified computing and optimization
Journal or Publication Title: Acta cybernetica
Date: 2020
Volume: 24
Number: 3
ISSN: 0324-721X
Page Range: pp. 287-314
Language: English
Publisher: University of Szeged, Institute of Informatics
Place of Publication: Szeged
Event Title: Summer Workshop on Interval Methods (11.) (2018) (Rostock)
Related URLs:
DOI: 10.14232/actacyb.24.3.2020.3
Uncontrolled Keywords: Számítástechnika, Kibernetika
Additional Information: Bibliogr.: p. 307-314 ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
Date Deposited: 2020. Jul. 30. 12:52
Last Modified: 2022. Jun. 21. 09:17

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