Orientation and Navigation Support in Resource Spaces Using Hierarchical Visualizations

Abstract

In this article we investigate how orientation and navigation in (extensive) spaces consisting of digital resources can be supported by using hierarchical visualizations. Such spaces can consist of heterogeneous sets of digital resources as for instance articles from Wikipedia, textbooks, and videos. Due to easier access to digital resources in the Internet age, a manual exploration of these spaces might lead to information overload. As a result, techniques need to be developed in order to automatically analyze and structure sets of resources. We introduce a prototypical implementation of a visualization pipeline that extracts information dimensions from resources in order to group them into semantically similar clusters, and visualizes these clusters using two different visualizations: a treemap visualizing clusters and nested subclusters, and a rooted tree visualizing groups of semantically similar resources as subtrees. In a lab study we evaluated the two visualizations and compared them to two control groups. The results may hint to users’ better understanding of the resources’ underlying knowledge as compared to using typical approaches (e.g. web search results as list) when using hierarchical visualizations.