Evaluating visual and statistical exploration of scientific literature networks

Action Science Explorer (ASE) is a tool designed to support users in rapidly generating readily consumable summaries of academic literature. It uses citation network visualization, ranking and filtering papers by network statistics, and automatic clustering and summarization techniques. We describe how early formative evaluations of ASE led to a mature system evaluation, consisting of an in-depth empirical evaluation with four domain experts. The evaluation tasks were of two types: predefined tasks to test system performance in common scenarios, and user-defined tasks to test the system's usefulness for custom exploration goals. The primary contribution of this paper is a validation of the ASE design and recommendations to provide: easy-to-understand metrics for ranking and filtering documents, user control over which document sets to explore, and overviews of the document set in coordinated views along with details-on-demand of specific papers. We contribute a taxonomy of features for literature search and exploration tools and describe exploration goals identified by our participants.