NicheWorks—Interactive Visualization of Very Large Graphs

TLDR

Large real‑world networks, often weighted and richly annotated, cannot be visualized with conventional layout algorithms because their size, density, and attribute complexity demand new or relaxed techniques to filter and focus attention on the screen. The authors aim to provide a system that simultaneously displays graph structure and node/edge attributes to uncover hidden patterns in such large, complex datasets. They present NicheWorks, a tool that implements scalable layout algorithms and a linked‑views interaction system to support exploration of massive graphs. Case studies demonstrate NicheWorks’ effectiveness in analyzing website structures and detecting international telephone fraud.

Abstract

Abstract The difference between displaying networks with 100–1,000 nodes and displaying ones with 10,000–100,000 nodes is not merely quantitative, it is qualitative. Layout algorithms suitable for the former are too slow for the latter, requiring new algorithms or modified (often relaxed) versions of existing algorithms to be invented. The density of nodes and edges displayed per inch of screen real estate requires special visual techniques to filter the graphs and focus attention. Compounding the problem is that large real-life networks are often weighted graphs and usually have additional data associated with the nodes and edges. A system for investigating and exploring such large, complex datasets needs to be able to display both graph structure and node and edge attributes so that patterns and information hidden in the data can be seen. In this article we describe a tool that addresses these needs, the NicheWorks tool. We describe and comment on the available layout algorithms and the linked views interaction system, and detail two examples of the use of NicheWorks for analyzing Web sites and detecting international telephone fraud.