SensePath: Understanding the Sensemaking Process Through Analytic Provenance

Abstract

Fig. 1: Four linked views of SensePath. A:The timeline view shows all captured sensemaking actions in temporal order. B: The browser view displays the web page where an action was performed. C: The replay view shows the screen capture video and can automatically jump to the starting time of an action when it is selected in another view. D: The transcription view displays detailed information of selected actions (the highlighted ones in the timeline view). Abstract-Sensemaking is described as the process of comprehension, finding meaning and gaining insight from information, producing new knowledge and informing further action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complex datasets. Currently, it is often a manual and time-consuming undertaking to comprehend this: researchers collect observation data, transcribe screen capture videos and think-aloud recordings, identify recurring patterns, and eventually abstract the sensemaking process into a general model. In this paper, we propose a general approach to facilitate such a qualitative analysis process, and introduce a prototype, SensePath, to demonstrate the application of this approach with a focus on browser-based online sensemaking. The approach is based on a study of a number of qualitative research sessions including observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Based on the study results and a follow-up participatory design session with HCI researchers, we decided to focus on the transcription and coding stages of thematic analysis. SensePath automatically captures user's sensemaking actions, i.e., analytic provenance, and provides multi-linked views to support their further analysis. A number of other requirements elicited from the design session are also implemented in SensePath, such as easy integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was used by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing better understanding of the sensemaking process.

SenseMap: Supporting browser-based online sensemaking through analytic provenance

“…Capturing low level events is relatively straightforward but provides little semantics [8]. Capturing provenance at "action" level is more common because it can be done automatically but could provide meaningful information [23,32]. However, capturing "sub-task" and "task" is more challenging because such information is usually part of the user's thinking, to which systems do not have direct access [14,41].…”

“…Information discovered during browser-based sensemaking can be collected at different levels of granularity: a web page URL [12], a page element such as table and form HTML tags [17], or a specific fragment of text [23]. Finer-grained capture allows users to record what they want with higher accuracy.…”

“…SensePath [23] captures user sensemaking actions and provides a set of visualization and analysis tools enabling other people such as HCI researchers to explore the user's sensemaking process through analysis of the captured actions.…”

“…We apply the same capture mechanism described in SensePath [23]. More specifically, the following aspects of actions are captured: Type: The default action when the user opens a web page is browsing.…”

“…Icons help users to recognize action types faster and we use the same icon set as shown in Figure 2 of the SensePath paper [23]. If the action type is the default browsing, the favorite icon of its web page is used instead.…”