Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs

Jian Zhao (1) , Michael Glueck (2) , Petra Isenberg (3) , Fanny Chevalier (4) , Azam Khan (2)

1 FXPAL - FX Palo Alto Laboratory
2 Autodesk Research
3 AVIZ - Analysis and Visualization
4 MJOLNIR - Computing tools to empower users

During asynchronous collaborative analysis, handoff of partial findings is challenging because externalizations produced by analysts may not adequately communicate their investigative process. To address this challenge, we developed techniques to automatically capture and help encode tacit aspects of the investigative process based on an analyst’s interactions, and streamline explicit authoring of handoff annotations. We designed our techniques to mediate awareness of analysis coverage, support explicit communication of progress and uncertainty with annotation, and implicit communication through playback of investigation histories. To evaluate our techniques, we developed an interactive visual analysis system, KTGraph, that supports an asynchronous investigative document analysis task. We conducted a two-phase user study to characterize a set of handoff strategies and to compare investigative performance with and without our techniques. The results suggest that our techniques promote the use of more effective handoff strategies, help increase an awareness of prior investigative process and insights, as well as improve final investigative outcomes.

Keywords: handoff; structured externalizations; interactive visual analysis; Collaboration; handover; sensemaking

Domains: Computer science

Jian Zhao, Michael Glueck, Petra Isenberg, Fanny Chevalier, Azam Khan. Supporting Handoff in Asynchronous Collaborative Sensemaking Using Knowledge-Transfer Graphs. IEEE Transactions on Visualization and Computer Graphics, 2017, 24 (1), pp.340-350. ⟨10.1109/TVCG.2017.2745279⟩. ⟨hal-01565560⟩