Eser Kandogan, Danny Soroker, et al.
VDA 2014
Understanding what insights people draw from data visualizations is critical for human-in-the loop analytics systems to facilitate mixed-initiative analysis. In this paper we present results from a large user study on insights extracted from commonly used charts. We report several patterns of insights we observed and analyze their semantic structure to identify key considerations towards a unified formal representation of insight, human or computer generated. We also present a model of insight generation process, where humans and computers work cooperatively, building on each other's knowledge, where a common representation acts as the currency of interaction. While not going as far as proposing a formalism, we point to a few potential directions for representing insight. We believe our findings could also inform the design of novel human-in-the-loop analytics systems.
Eser Kandogan, Danny Soroker, et al.
VDA 2014
Christopher S. Campbell, Eser Kandogan, et al.
POLICY 2005
Paul P. Maglio, Christopher S. Campbell, et al.
ICAC 2005
Sandeep Gopisetty, Sandip Agarwala, et al.
IBM J. Res. Dev