Visualizing Spatial Dependencies in Network Topology
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Increasingly, the data available to network analysts includes not only relationships between entities but the observation of entity attributes and relations in geographic space. Integrating this information with existing dynamic network analysis techniques demands new models and new tools. This paper introduces extensions to the ORA dynamic network analysis platform intended to meet this need. In particular, we present new visualization techniques for displaying the network topology of large, noisy datasets embedded in geographic space. We present these extensions and demonstrate them on some sample datasets.
- Operations Research
- Computer Systems