Visually Exploring Relations Between Structure and Attributes in Multivariate Graphs

The visual analysis of multivariate graphs is a challenging problem. We address the particular task of studying relations between the structure of a graph and the multivariate attributes associated with it. To facilitate this task, we propose a novel interactive visualization approach. The core idea is to show structure and calculated attribute similarity in an integrated fashion as a matrix. A table can be attached to the matrix on demand to visualize the underlying attribute values in detail. To support the visual comparison of structure and attributes at different levels, several interaction techniques are provided, including matrix reordering, selection and emphasis of subsets, rearrangement of sub-matrices, and column rotation for detailed comparison. To demonstrate the utility of our techniques, we apply them to explore relations between structure and attributes in a network of soccer players.