By Topic

Information provenance and the knowledge rediscovery problem

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

1 Author(s)
D. P. Groth ; Sch. of Informatics, Indiana Univ., Bloomington, IN, USA

Visualizations leverage innate human capabilities for recognizing interesting aspects of data. Even if users might agree on what is interesting about a visualization, the steps that they use in the knowledge discovery process may be significantly different. This results in an inability to effectively recreate the exact conditions of the discovery process, which we call the knowledge rediscovery problem. Because we cannot expect a user to fully document each of their interactions, there is a need for visualization systems to maintain user trace data in a way that enhances a user's ability to communicate what they found to be interesting, as well as how they found it. We present a model for representing user interactions that articulates with a corresponding set of annotations, or observations that are made during the exploration. Such ability is critical to addressing the knowledge rediscovery problem, and is a fundamental component for systems that must provide information provenance.

Published in:

Information Visualisation, 2004. IV 2004. Proceedings. Eighth International Conference on

Date of Conference:

14-16 July 2004