Atlas: Local Graph Exploration in a Global Context

Interactive Data VisualizationTime-Series & Network Graph VisualizationData Scientists & AnalystsHCI ResearchersStatisticians & Data Scientists

Graphs are everywhere, growing increasingly complex, and still lack scalable, interactive tools to support sensemaking. To address this problem, we present Atlas, an interactive graph exploration system that adapts scalable edge decomposition to enable a new paradigm for large graph exploration, generating explorable multi-layered representations. Atlas simultaneously reveals peculiar subgraph structures, (e.g., quasi-cliques) and possible vertex roles in connecting such subgraph patterns. Atlas decomposes million-edge graphs in seconds, scaling to graphs with up to 117 million edges. We present the results from a think-aloud user study with three graph experts and highlight discoveries made possible by Atlas when applied to graphs from multiple domains, including suspicious yelp reviews, insider trading, and word embeddings. Atlas runs in-browser and is open-sourced.

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https://hci.top/en/papers/iui/4582/2019

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IUI
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Year
2019
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4 authors
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Interactive Data Visualization, Time-Series & Network Graph Visualization
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Data Scientists & Analysts, HCI Researchers, Statisticians & Data Scientists
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Abstract only
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