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Towards Understanding Multimodal Interaction for Visual Data Analysis

Ruoff, Marcel; Maedche, Alexander

Abstract:
Multimodal interaction for visual data analysis and exploration provides new opportunities for empowering users to engage with data. However, it is not well understood which input modalities should be leveraged for certain information visualization (InfoVis) operations and how user would prefer to utilize them during data analysis and exploration. In order to close this research gap, we performed an user-elicitation study to examine how users utilize touch, speech, mid-air hand gestures and a combination of those for various InfoVis operations on large interactive displays. We believe this analysis will help us identify associated challenges and provide knowledge for the development of systems that provide multimodal interaction capabilities for visual data analysis and exploration.



Zugehörige Institution(en) am KIT Institut für Wirtschaftsinformatik und Marketing (IISM)
Publikationstyp Poster
Publikationsdatum 28.10.2020
Sprache Englisch
Identifikator KITopen-ID: 1000128180
Veranstaltung 31st IEEE Conference on Information Visualization (2020), Online, 25.10.2020 – 30.10.2020
Bemerkung zur Veröffentlichung Die Veranstaltung fand wegen der Corona-Pandemie als Online-Event statt
Schlagwörter Information Visualization; Multimodal Interaction; Interaction Techniques; Visual Analytics
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