Reflections on the evolution of the Jigsaw visual analytics system

Abstract

Analyzing and understanding collections of textual documents is an important task for professional analysts and a common everyday scenario for nonprofessionals. We have developed the Jigsaw visual analytics system to support these types of sensemaking activities. Jigsaw’s development benefited significantly from the existence of the VAST Contest/Challenge that provided (1) diverse document collections to use as examples, (2) controlled exercises with a set of analytic tasks and solutions for judging results, and (3) visibility and publicity to help communicate our ideas to others. This article describes our participation in a series of VAST Contest/Challenge efforts and how this participation helped influence Jigsaw’s design and development. We describe how the system’s capabilities have evolved over time, and we identify the particular lessons that we learned by participating in the challenges.