graphVizdb: A Scalable Platform for Interactive Large Graph Visualization

2016 IEEE 32nd International Conference on Data Engineering (ICDE)(2016)

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摘要
We present a novel platform for the interactive visualization of very large graphs. The platform enables the user to interact with the visualized graph in a way that is very similar to the exploration of maps at multiple levels. Our approach involves an offline preprocessing phase that builds the layout of the graph by assigning coordinates to its nodes with respect to a Euclidean plane. The respective points are indexed with a spatial data structure, i.e., an R-tree, and stored in a database. Multiple abstraction layers of the graph based on various criteria are also created offline, and they are indexed similarly so that the user can explore the dataset at different levels of granularity, depending on her particular needs. Then, our system translates user operations into simple and very efficient spatial operations (i.e., window queries) in the backend. This technique allows for a fine-grained access to very large graphs with extremely low latency and memory requirements and without compromising the functionality of the tool. Our web-based prototype supports three main operations: (1) interactive navigation, (2) multi-level exploration, and (3) keyword search on the graph metadata.
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关键词
graphVizdb,interactive large graph visualization,offline preprocessing phase,graph layout,Euclidean plane,spatial data structure,R-tree,graph abstraction layers,granularity level,interactive navigation,multilevel exploration,keyword search,graph metadata
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