PROJECT TITLE :
SensePath: Understanding the Sensemaking Process Through Analytic Provenance
Sensemaking is described as the process of comprehension, finding that means and gaining insight from info, manufacturing new knowledge and informing additional action. Understanding the sensemaking process allows building effective visual analytics tools to make sense of large and complicated datasets. Currently, it is typically a manual and time-consuming enterprise to comprehend this: researchers collect observation knowledge, transcribe screen capture videos and suppose-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 method, and introduce a prototype, SensePath, to demonstrate the application of this approach with a specialize in browser-primarily based on-line sensemaking. The approach relies on a study of a number of qualitative analysis sessions together with observations of users performing sensemaking tasks and post hoc analyses to uncover their sensemaking processes. Primarily based on the study results and a follow-up participatory style session with HCI researchers, we decided to target 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 any analysis. A variety of other needs elicited from the planning session are implemented in SensePath, like simple integration with existing qualitative analysis workflow and non-intrusive for participants. The tool was employed by an experienced HCI researcher to analyze two sensemaking sessions. The researcher found the tool intuitive and considerably reduced analysis time, allowing higher understanding of the sensemaking process.
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