Too Big To See: The Need for Design Strategies to Visualize Multiple Spatiotemporal Datasets

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Too Big To See: The Need for Design Strategies to Visualize Multiple Spatiotemporal Datasets

(Short paper)

Keywords: 4D Data Visualization; Information Arts; Strategic Design; Spatiotemporal Semiotics.

Tracking software paired with 3D modeling now provides animations of movement in nearly every context of our highly sensed world. However, few visualizations exist that show adjacent systems, usually because of wildly divergent data. One such spatiotemporal adjacency is crucial to our safety – our increasingly cluttered skies rapidly filling with drones, budget airlines, helicopters, weather collection sensors and Asian satellites. The scale, number, tiered altitudes and variant speeds of aerial hardware are a physical reality that can only be understood through the moving image. However, no visual model exists to reveal all the machines when stratified causing our culture to lack an understanding of the expanding system. Can stratified aerial traffic be represented through a hybrid of informative data visualization and evocative information arts? What are semiotic strategies and taxonomic delineations that can merge into a visual language understandable across the growing number of cultures now involved in aerial movement and its dangers? This paper will present a creative context to explore visual strategies for better cognitive and perceptual understanding of multi-tiered, spatiotemporal data. Creative design tools will provide insight into finding meaning in dynamic data and may lead to advances in understanding other sets of Big Data.