Volkswagen Data Lab
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Jan-Frederik Kassel is a researcher in the Human-Computer Interaction Group at the University of Hannover. His main areas of interest are Human-Computer Interaction and Personalised Visual Analytics. He is an external Ph.D. student located at the Volkswagen Data Lab in Munich.
More information will be coming soon.
Immersive Navigation in Visualization Spaces through Swipe Gestures and Optimal Attribute Selection
Proceedings of the 2nd Workshop on Immersive Analytics: Exploring Future Interaction and Visualization Technologies for Data Analytics
Exploratory data analysis is an essential step in discovering patterns and relationships in data. However, the exploration may start without a clear conception about what attributes to pick or what visualizations to choose in order to develop an understanding of the data. In this work we aim to support the exploration process by automatically choosing attributes according to an information-theoretic measure and by providing a simple means of navigation through the space of visualizations. The system suggests data attributes to be visualized and the visualization's type and appearance. The user intuitively modifies these suggestions by performing swiping gestures on a tablet device. Attribute suggestions are based on the mutual information between multiple random variables (MMI). The results of a preliminary user study (N = 12 participants) show the applicability of MMI for guided exploratory data analysis and confirm the system's general usability (SUS score: 74).
Visualizing Scheduling: A Hierarchical Event-Based Approach on a Tablet
Proceedings of the 17th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct
The amount of logistical data in the automotive industry drastically increases due to digitalization and data that is automatically generated due to Auto-ID-Technologies. However, new methods need to be devised to make sense of this data, in particular when users are mobile, and when users need to collaborate to solve complex logistical tasks, such as resource scheduling. We propose a visualization method for hierarchical event data that is designed for tablets. The main design goals have been to foster collaboration and enable mobility. Our think aloud user study shows that both the event recognition and understanding of the participants improved with the proposed solution.