InProv: Visualizing Provenance Graphs with Radial Layouts and Time-Based Hierarchical Grouping

In provenance research, the large scale of data sets often complicates analysis and understanding. One solution is visualization, a tool that enables scientists and analysts to understand large data sets. The standard format for visualizing provenance is the node-link diagram. However, while effective for understanding local activity, the node-link diagram fails to offer a high-level summary of the relationships within a provenance graph. By focusing on the node-link diagram as the de facto method for graph visualization, the community has failed to explore alternative means that may be more effective. Visualizing filesystem provenance with a radial-based tree layout that is sorted by the time at which system activity occurred instead provides increased accuracy for identifying the high-level activity of a data set. The first contribution of this research is a task taxonomy for filesystem provenance data analysis based on my interviews with domain experts. The second contribution, developed in order to make InProv more effective by identifying the most important nodes and processes in a system, is a new time-based hierarchical grouping method for provenance data. The third contribution is the design of InProv, a radial layout visualization tool for browsing filesystem provenance data over time. Finally, I contribute statistically significant evidence that our radial based layout for filesystem provenance data is more accurate and easier to use than traditional node-link diagrams. A copy of InProv will be made open source-available. In the meantime, please email [email protected] to request a copy.