Abstract
Multi-View Visualization (MV) is a technique employed in large-display interaction platforms like network security situational awareness and industrial platforms. However, due to the high technical cost, complexity of physiological measurements, and inadequacy of subjective scales, large-display interaction designs often lack assessment for situational awareness and rely on back-end coding schemes. This lack of convenient and effective measurement impacts interaction design quality, leading to misunderstandings of system intention by human operators. This paper proposes a Quantitative Analysis of Situation Awareness (QASA) for MV layout in large-display interaction design. Through multiple experimental measurements (N=50) validated by eye-movement testing, we compared situational awareness results of various layouts and analysed their differences. The Actual Situational Awareness (ASA) difference between layouts was 13.3%, while the ASA difference of a single view in each layout reached 26.8%. After applying this method to improve industrial testbeds, the ASA of the new system increased by 9.2%. The practical results suggest that QASA can guide and evaluate MV design to enhance the situational awareness level of application systems. Effective situational awareness assessment helps optimize designs for complex data systems, mitigate conflicts between human operators and the system, and ensure that human operators make informed decisions.
Keywords
Situational Awareness; Multi-view Visualization; Situational Awareness Measurement; Layout.
DOI
https://doi.org/10.21606/iasdr.2023.481
Citation
Ji, P.,and He, X.(2023) Multi-view visualization layout design method for large displays based on quantitative analysis of situation awareness, in De Sainz Molestina, D., Galluzzo, L., Rizzo, F., Spallazzo, D. (eds.), IASDR 2023: Life-Changing Design, 9-13 October, Milan, Italy. https://doi.org/10.21606/iasdr.2023.481
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License
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Multi-view visualization layout design method for large displays based on quantitative analysis of situation awareness
Multi-View Visualization (MV) is a technique employed in large-display interaction platforms like network security situational awareness and industrial platforms. However, due to the high technical cost, complexity of physiological measurements, and inadequacy of subjective scales, large-display interaction designs often lack assessment for situational awareness and rely on back-end coding schemes. This lack of convenient and effective measurement impacts interaction design quality, leading to misunderstandings of system intention by human operators. This paper proposes a Quantitative Analysis of Situation Awareness (QASA) for MV layout in large-display interaction design. Through multiple experimental measurements (N=50) validated by eye-movement testing, we compared situational awareness results of various layouts and analysed their differences. The Actual Situational Awareness (ASA) difference between layouts was 13.3%, while the ASA difference of a single view in each layout reached 26.8%. After applying this method to improve industrial testbeds, the ASA of the new system increased by 9.2%. The practical results suggest that QASA can guide and evaluate MV design to enhance the situational awareness level of application systems. Effective situational awareness assessment helps optimize designs for complex data systems, mitigate conflicts between human operators and the system, and ensure that human operators make informed decisions.