Interactive web-based visualization of large dynamic graphs

The visualization and analysis of large graphs plays an essential role in various application fields. Since the size of graphs grew exponentially in the past few years, it became a challenge to reduce the visual clutter of dense and occluded graphs. By abstracting the structure of a node-link diagram, containing thousands of nodes and edges, visual clutter is reduced drastically, supporting the analysis of underlying patterns in an interactive approach. Additional visual techniques are used to overcome the challenge of representing the evolution of structural diagram changes and relationships between entities in dynamic graph visualization. The recent publications of large static and dynamic graph visualization techniques are using rich clients based on fast processing GPU algorithms, as well as distributed approaches for cluster-computing frameworks. Even though these techniques are capable of processing large-scale graphs interactively, they are also restricted by the user’s hardware or are more complex and expensive than simple client-server solutions. This thesis aims to provide an alternative approach, at providing a distributed, cross-platform, server-client application, able to visualize large node-link graphs, consisting of thousands of elements, interactively in a standard web-browser. We describe an aggregation strategy based on meta-elements, that provides an adjustable level of detail interface and visualizes the hierarchy of cumulative elements throughout multiple abstraction layers. By highlighting structural changes over time in dynamic graphs in combination with tools, such as panning and zooming and overview and detail, our system allows for dynamic graph exploration. We will demonstrate the usability of our technique by providing a complete prototype and present benchmarks on different graphs. Furthermore, we evaluate technical aspects of our approach as well as its applicability to large real-world graphs.