This paper describes results from an observational, exploratory study of visual data exploration in a large, multi-view, flexible canvas environment. Participants were provided with a set of data exploration sub-tasks associated with a local crime dataset and were instructed to pose questions to a remote mediator who would respond by generating and organizing visualizations on the large display. We observed that participants frequently posed requests to cast a net around one or several subsets of the data or a set of data attributes. They accomplished this directly and by utilizing existing views in unique ways, including by requesting to copy and pivot a group of views collectively and posing a set of parallel requests on target views expressed in one command. These observed actions depart from multi-view flexible canvas environments that typically provide interfaces in support of generating one view at a time or actions that operate on one view at a time. We describe how participants used these “cast-a-net” requests for tasks that spanned more than one view and describe design considerations for multi-view environments that would support the observed multi-view generation actions.

Index Terms: Human-centered computing - Empirical studies in visualization

This work was supported initially by NSF award IIS 1445751 and currently by NSF award CNS 1625941.

https://doi.org/10.1111/cgf.13976

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Aurisano, J., Kumar, A., Alsaiari, A., Di Eugenio, B., Johnson, A.E., Many At Once: Capturing Intentions to Create And Use Many Views At Once In Large Display Environments, Eurographics Conference on Visualization (EuroVis) 2020, vol 39, no 3, M. Gleicher, T. Landesberger von Antburg, and I. Viola, May 25th, 2020. https://diglib.eg.org/handle/10.1111/cgf13976