Towards Understanding Edit Histories of Multivariate Graphs

Abstract

The visual analysis of multivariate graphs increasingly involves not only exploring the data, but also editing them. Existing editing approaches for multivariate graphs support visual analytics workflows by facilitating a seamless switch between data exploration and editing. However, it remains difficult to comprehend performed editing operations in retrospect and to compare different editing results. Addressing these challenges, we propose a model describing what graph aspects can be edited and how. Based on this model, we develop a novel approach to visually track and understand data changes due to edit operations. To visualize the different graph states resulting from edits, we extend an existing graph visualization approach so that graph structure and the associated multivariate attributes can be represented together. Branching sequences of edits are visualized as a node-link tree layout where nodes represent graph states and edges visually encode the performed edit operations and the graph aspects they affect. Individual editing operations can be inspected by dynamically expanding edges to detail views on demand. In addition, we support the comparison of graph states through an interactive creation of attribute filters that can be applied to other states to highlight similarities.