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.