Visualizing the commonalities between hierarchically structured data queries

In this paper we present an information visualization approach for visualizing the intersection between multiple feature hierarchies. In cases where a dataset has multiple complex features of interest, especially ones that have been hierarchically clustered, it is often very difficult to grasp the commonalities between them. Understanding the overlap between features can help researchers discover correlations or hot spots in their data. Our method steps back from actual data features, simplifying their representation, and presenting them in a fashion which facilitates interpretation of their inter-feature relationships. We call this new representation a knowledge graph, and we show how it can be used to investigate the overlap of multiple features in a photo database and a social network dataset.