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Interaction Taxonomy for Tracking of User Actions in Visual Analytics Applications

Landesberger, Tatiana von and Fiebig, Sebastian and Bremm, Sebastian and Kuijper, Arjan and Fellner, Dieter W. (2014):
Interaction Taxonomy for Tracking of User Actions in Visual Analytics Applications.
Springer, Berlin, Heidelberg, New York, pp. 653-670, DOI: 10.1007/978-1-4614-7485-2₂₆, [Book Section]

Abstract

In various application areas (social science, transportation, or medicine) analysts need to gain knowledge from large amounts of data. This analysis is often supported by interactive Visual Analytics tools that combine automatic analysis with interactive visualization. Such a data analysis process is not streamlined, but consists of several steps and feedback loops. In order to be able to optimize the process, identify problems, or common problem solving strategies, recording and reproducibility of this process is needed. This is facilitated by tracking of user actions categorized according to taxonomy of interactions. Visual Analytics includes several means of interaction that are differentiated according to three fields: information visualization, reasoning, and data processing. At present, however, only separate taxonomies for interaction techniques exist in these three fields. Each taxonomy covers only a part of the actions undertaken in Visual Analytics. Moreover, as they use different foundations (user intentions vs. user actions) and employ different terminology, it is not clear to what extent they overlap and cover the whole Visual Analytics interaction space. We therefore first compare them and then elaborate a new integrated taxonomy in the context of Visual Analytics. In order to show the usability of the new taxonomy, we specify it on visual graph analysis and apply it to the tracking of user interactions in this area.

Item Type: Book Section
Erschienen: 2014
Creators: Landesberger, Tatiana von and Fiebig, Sebastian and Bremm, Sebastian and Kuijper, Arjan and Fellner, Dieter W.
Title: Interaction Taxonomy for Tracking of User Actions in Visual Analytics Applications
Language: English
Abstract:

In various application areas (social science, transportation, or medicine) analysts need to gain knowledge from large amounts of data. This analysis is often supported by interactive Visual Analytics tools that combine automatic analysis with interactive visualization. Such a data analysis process is not streamlined, but consists of several steps and feedback loops. In order to be able to optimize the process, identify problems, or common problem solving strategies, recording and reproducibility of this process is needed. This is facilitated by tracking of user actions categorized according to taxonomy of interactions. Visual Analytics includes several means of interaction that are differentiated according to three fields: information visualization, reasoning, and data processing. At present, however, only separate taxonomies for interaction techniques exist in these three fields. Each taxonomy covers only a part of the actions undertaken in Visual Analytics. Moreover, as they use different foundations (user intentions vs. user actions) and employ different terminology, it is not clear to what extent they overlap and cover the whole Visual Analytics interaction space. We therefore first compare them and then elaborate a new integrated taxonomy in the context of Visual Analytics. In order to show the usability of the new taxonomy, we specify it on visual graph analysis and apply it to the tracking of user interactions in this area.

Publisher: Springer, Berlin, Heidelberg, New York
Uncontrolled Keywords: Forschungsgruppe Visual Search and Analysis (VISA), Forschungsgruppe Semantic Models, Immersive Systems (SMIS), Business Field: Visual decision support, Research Area: Human computer interaction (HCI), Interaction analysis, Taxonomies, User behavior, Visual analytics, Graph visualization
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-1-4614-7485-2₂₆
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