IEEE VIS 2024 Content: Aardvark: Composite Visualizations of Trees, Time-Series, and Images

Best Paper Award

Aardvark: Composite Visualizations of Trees, Time-Series, and Images

Devin Lange - University of Utah, Salt Lake City, United States

Robert L Judson-Torres - University of Utah, Salt Lake City, United States

Thomas A Zangle - University of Utah, Salt Lake City, United States

Alexander Lex - University of Utah, Salt Lake City, United States

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Room: Bayshore I + II + III

2024-10-15T16:25:00Z GMT-0600 Change your timezone on the schedule page
2024-10-15T16:25:00Z
Exemplar figure, described by caption below
Live-cell microscopy imaging results in multimodal data composed of trees, time-series, and images. The visualization system Aardvark combines these data modalities into composite visualizations. The tree-first visualization (left) shows the cell relationships as a node-link tree visualization, horizon charts show the time series data and image snippets display alongside the horizon charts. The time-series-first visualization (top right) shows the time-series data as line charts with images and cell relationships superimposed. Finally, the image-first visualization (bottom right) shows the full microscopy image, with cell movement and relationships superimposed.
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Keywords

Visualization, Cell Microscopy, View Composition

Abstract

How do cancer cells grow, divide, proliferate, and die? How do drugs influence these processes? These are difficult questions that we can attempt to answer with a combination of time-series microscopy experiments, classification algorithms, and data visualization.However, collecting this type of data and applying algorithms to segment and track cells and construct lineages of proliferation is error-prone; and identifying the errors can be challenging since it often requires cross-checking multiple data types. Similarly, analyzing and communicating the results necessitates synthesizing different data types into a single narrative. State-of-the-art visualization methods for such data use independent line charts, tree diagrams, and images in separate views. However, this spatial separation requires the viewer of these charts to combine the relevant pieces of data in memory. To simplify this challenging task, we describe design principles for weaving cell images, time-series data, and tree data into a cohesive visualization. Our design principles are based on choosing a primary data type that drives the layout and integrates the other data types into that layout. We then introduce Aardvark, a system that uses these principles to implement novel visualization techniques. Based on Aardvark, we demonstrate the utility of each of these approaches for discovery, communication, and data debugging in a series of case studies.