Toward effective insight management in visual analytics systems

Although significant progress has been made toward effective insight discovery in visual sense making approaches, there is a lack of effective and efficient approaches to manage the large amounts of insights discovered. In this paper, we propose a systematic approach to leverage this problem around the concept of facts. Facts refer to patterns, relationships, or anomalies extracted from data under analysis. They are the direct products of visual exploration and permit construction of insights together with user's mental model and evaluation. Different from the mental model, the type of facts that can be discovered from data is predictable and applicationindependent. Thus it is possible to develop a general Fact Management Framework (FMF) to allow visualization users to effectively and efficiently annotate, browse, retrieve, associate, and exchange facts. Since facts are essential components of insights, it will be feasible to extend FMF to effective insight management in a variet...

• Type: Conference
• Year: 2009
• Where: APVIS
• Authors: Yang Chen, Jing Yang, William Ribarsky
• Keywords: APVIS 2007, APVIS 2009, Effective Insight, Mental Model, Visual Sense