Evaluating exploratory visualization systems: A user study on how clustering-based visualization systems support information seeking from large document collections

Yujie Liu, Scott Barlowe, Yaqin Feng, Jing Yang, Min Jiang
2012 Information Visualization  
Iterative, opportunistic and evolving visual sensemaking has been an important research topic as it assists users in overcoming ever-increasing information overload. Exploratory visualization systems (EVSs) maximize users' information gain through learning and have been widely used in scientific discovery and decision making contexts. Although many EVSs have been developed recently, there is a lack of general guidance on how to evaluate such systems. Researchers face challenges such as
more » ... ding the cognitive learning process supported by these systems. In this paper, we present a formal user study on Newdle, a clusteringbased EVS for large news collections, shedding light on a general methodology for EVS evaluation. Our approach is built upon cognitive load theory that takes the users as well as the system as the foci of evaluation. The carefully designed procedures allow us to thoroughly examine the users' cognitive process as well as control the variability among human subjects. Through this study, we analyze how and why clustering-based EVSs benefit (or not) users in a variety of information seeking tasks. We also summarize leverage points for designing clustering-based EVSs.
doi:10.1177/1473871612459995 fatcat:mkxs5grpuveirf325ilehx3mzy