Toward flexible visual analytics augmented through smooth display transitions

Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in …

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Abstract

Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.

Figures

Four differently prioritized views of the food stall example data from Table 1. Left: Attributes and time are shown in full detail, space is omitted. Middle top: Attributes in full detail, time and space are omitted. Right: A map showing the location and type of the food stalls but not their labels (attribute with reduced detail, time omitted). Middle bottom: Time is fixed (reduced detail) and attributes shown, space omitted.

Visualizing time, space, and structural connections in separate views.

Time, space, and structural connections integrated in a single visual representation.

Prioritized views (red, green, blue) communicate data aspects (A, T , S, R) at different levels of detail (++, +, −).

Transitions between views may form different topologies.

Different visual outcome of interpolation in data space and visual space.

Smooth transition from a node-link representation to a matrix representation. Source: © 2007 IEEE. Reprinted, with permission, from Henry et al. (2007).

Transition from a 3D categorical representation (left) to a 2D representation (right).

BibTeX

@article{tominski_towardFlexibleVASmoothTransition_2021,
 abstract = {Visualizing big and complex multivariate data is challenging. To address this challenge, we propose flexible visual analytics (FVA) with the aim to mitigate visual complexity and interaction complexity challenges in visual analytics, while maintaining the strengths of multiple perspectives on the studied data. At the heart of our proposed approach are transitions that fluidly transform data between user-relevant views to offer various perspectives and insights into the data. While smooth display transitions have been already proposed, there has not yet been an interdisciplinary discussion to systematically conceptualize and formalize these ideas. As a call to further action, we argue that future research is necessary to develop a conceptual framework for flexible visual analytics. We discuss preliminary ideas for prioritizing multi-aspect visual representations and multi-aspect transitions between them, and consider the display user for whom such depictions are produced and made available for visual analytics. With this contribution we aim to further facilitate visual analytics on complex data sets for varying data exploration tasks and purposes based on different user characteristics and data use contexts.},
 author = {Tominski, Christian and Andrienko, Gennady and Andrienko, Natalia and Bleisch, Susanne and Fabrikant, Sara Irina and Mayr, Eva and Miksch, Silvia and Pohl, Margit and Skupin, André},
 doi = {10.1016/j.visinf.2021.06.004},
 journal = {Visual Informatics},
 number = {3},
 pages = {28--38},
 title = {Toward flexible visual analytics augmented through smooth display transitions},
 url = {https://linkinghub.elsevier.com/retrieve/pii/S2468502X21000310},
 volume = {5},
 year = {2021}
}