Supporting Communication and Coordination in Collaborative Sensemaking

Abstract

When people work together to analyze a data set, they need to organize their findings, hypotheses, and evidence, share that information with their collaborators, and coordinate activities amongst team members. Sharing externalizations (recorded information such as notes) could increase awareness and assist with team communication and coordination. However, we currently know little about how to provide tool support for this sort of sharing. We explore how linked common work (LCW) can be employed within a `collaborative thinking space', to facilitate synchronous collaborative sensemaking activities in Visual Analytics (VA). Collaborative thinking spaces provide an environment for analysts to record, organize, share and connect externalizations. Our tool, CLIP, extends earlier thinking spaces by integrating LCW features that reveal relationships between collaborators' findings. We conducted a user study comparing CLIP to a baseline version without LCW. Results demonstrated that LCW significantly improved analytic outcomes at a collaborative intelligence task. Groups using CLIP were also able to more effectively coordinate their work, and held more discussion of their findings and hypotheses. LCW enabled them to maintain awareness of each other's activities and findings and link those findings to their own work, preventing disruptive oral awareness notifications.

InsideInsights: Integrating Data‐Driven Reporting in Collaborative Visual Analytics

“…The whole process is iterative, meandering, and prone to branching [BPW∗93, SvW08]: sometimes, the analyst will backtrack to explore a different avenue of inquiry; sometimes entire paths will be abandoned; and sometimes the current strand of investigation proves to be the right one. Supporting this type of workflow is a challenge in itself, and in collaborative scenarios it is also a challenge to share, hand off, and communicate insights from such a process, as amply pointed out in past work [HA08, SHA08, KPHH12, MT14, RTH18, ZGI∗18]. In addition, there is no watertight boundary between analysis and presentation [PC05]; sometimes a presentation may even return back to exploration.…”

“…C3 ‐ Fragmented Workflows. An overarching challenge is the non‐linear nature of collaborative data analysis [SHA08, HA08, KPHH12,MT14]. An analysis frequently alternates between exploration and reporting, with the same analysis parts often revisited several times.…”

“…Furthermore, data analysis is seldom confined to a single person; multiple collaborators will often contribute to the same analysis, or intermediate results can be shared with stakeholders. Thus, an important aspect of collaborative data analysis is to enable communication of insights even before the analysis has concluded [MT14, ST15, ZGI∗18]. However, transferring knowledge is especially difficult for non‐routine and ill‐defined tasks [SHA08], hence effective communication requires a correspondingly rich mechanism to match the complexity of exploratory data analysis.…”

Active Reading of Visualizations

“…However, some interactions in visualizations, such as annotation mechanisms, can be discussed in terms of active reading. In visualization, such mechanisms have primarily been designed with the intent of communicating thoughts to others during collaborative [41] and crowdsourced analysis [24,69], public discussion of narrative visualizations [30], and for authors of narrative visualizations to explain data [60]. Sense.us [24] is an exception, in that it went beyond offering the possibility of placing of text in sidebars or behind icons by providing a freeform graphical annotation layer.…”

Interactive Presentation of Geo-Spatial Climate Data in Multi-Display Environments

“…Recently, Mahyar and Tory introduced a tool that supports the communication in collaborative sense-making by revealing relationships between collaborators' findings. In this way, awareness of each other's activities can be maintained [20].…”