Reducing the Cognitive Load of Visual Analytics of Networks Using Concentrically Arranged Multi-surface Projections Focusing Immersive Real-time Exploration

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Ameres, Eric
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The analysis of “Big Data” stretches traditional visualization to its breaking point. This is especially true of highly interconnected relational data that pervades the field. Seemingly in response to that Visual Analytics (VA) and the graphical visualization of data in general are often used only with the goal of simplification and presentation rather than as a tool for rich study and discovery. To maximize the use of visualization as an effective tool for generating new knowledge from complex data, we must understand and address issues of design based on human sensing, perception and overall cognitive processing especially with regard to learning. The Campfire and the visualization paradigm I have developed based on its form (Concentrical-ly Arranged Multi-surface Projections Focusing Immersive Real-time Exploration aka “CAMPFIRE”) are novel, and provide a form and affordances that inspire new methods for the exploration and structured visualization of data that are immersive and visuo-spatially rich. However, novelty is not a measure of effectiveness. Instructional media, instructional methods and their associated cognitive tasks such as evaluating a graph, chart or other visual information carry loading costs of different types that need to be mitigated and moderated by informed design. The proposal was that through the application of Cognitive Load Theory and by specifically designing with careful attention to the effect of split attention and increasing the use of spatiality as a distinct modality, it is possible to reduce cognitive load for certain types of visual analytics tasks. It should be possible to promote the efficacy and engagement of old and new methods of visual analytics by re-imagining their use of space and form, and by applying these theories and practices with that in mind. This is especially true for the radial visualization technique that relies heavily on form, and for display paradigms that can potentially instill a sense of spatial 3-dimensionality in the user. This thesis demonstrates and tests the Campfire style of visualization on a simulated network (graph) visualization type task (e.g., visually inspecting and comparing nodes in a connected graph). It shows that it is possible to better engage the user through heightened dimensionality vs. traditional flat display by creating affordances that offload certain types of spatial processing (rotation and translation) from the user back into the visualization system. This thesis also provides design-based analysis of a variety of cases to give insight into “best practices” and design recommendations with regard to Campfire style visual analytics. It also demonstrates the connections and parallels that this method has to other traditional visualization and information and statistical graphic theory and practice.
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Ameres, E. L. (2018). Reducing the cognitive load of visual analytics of networks using concentrically arranged multi-surface projections focusing immersive real-time exploration (Order No. 10789140). Available from Dissertations & Theses @ Rensselaer Polytechnic Institute; ProQuest Central Essentials; ProQuest Dissertations & Theses Global. (2086085516). Retrieved from
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