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
3 AVIZ - Analysis and Visualization
Inria Saclay - Ile de France
4 MJOLNIR - Computing tools to empower users
CRIStAL - Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189, Inria Lille - Nord Europe
Abstract : 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.
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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, Institute of Electrical and Electronics Engineers, 2017, 24 (1), pp.340-350. ⟨10.1109/TVCG.2017.2745279⟩. ⟨hal-01565560⟩

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