Insight Provenance Modeling

task_hierarchyInsight provenance—a historical record of the process and rationale by which an insight is derived—is an essential requirement in many visual analytics applications. While work in this area has typically relied on either manually recorded provenance (e.g., user notes) or automatically recorded event-based insight provenance (e.g., clicks, drags, and key-presses), both approaches have fundamental limitations. Our aim in this project is to develop a new approach that combines the benefits of both approaches while avoiding their deficiencies. Toward this goal, we characterize users’ visual analytic activity at multiple levels of granularity. This characterization is driven by user studies of analysis activity in various domains, ranging from travel planning to intelligence analysis.
Moreover, we identify a critical level of abstrac- tion, Actions, that can be used to represent visual analytic activity with a set of general but semantically meaningful behavior types. In turn, the action types can be used as the semantic building blocks for Trails, a representation for the interconnected web of analysis paths that define an insight’s provenance. We present a catalog of common actions identified through observations of several different visual analytic systems. In addition, we define a taxonomy to categorize actions into three major classes based on their semantic intent. The concept of actions has been integrated into our lab’s prototype visual analytic system, HARVEST, as the basis for its insight provenance capabilities.


David Gotz and Michelle X. Zhou. Characterizing User’s Visual Analytic Activity for Insight Provenance. Information Visualization (Volume 8, Number 1, 2009).
[This article is available through Palgrave Macmillan. View the article by clicking here.]

David Gotz and Michelle Zhou. Characterizing Users’ Visual Analytic Activity for Insight Provenance. IEEE Visual Analytics Science and Technology (VAST), Columbus, Ohio (2008).
[PDF, 853k]

David Gotz, Michelle X. Zhou, and Zhen Wen. A Study of Information Gathering and Result Processing in Intelligence Analysis. ACM IUI 2006 Workshop on Intelligent User Interfaces for Intelligence Analysis, Sydney, Australia (2006).
[PDF, 451k]


Sch of Inform and Libr Science