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Click here to download Stan’s paper.
Avalanche forecasters typically work in teams, relying on the continuity of their shared understanding of avalanche conditions. Shift changes can disrupt this continuity as incoming forecasters need time to get up to speed with current conditions. While the conceptual model of avalanche hazard offers a structured way to describe existing conditions, it lacks important contextual information that informs hazard assessments. Without this context, forecasters can be left searching for clarifying information that could otherwise have been communicated. Handoff notes can provide this context but can be cumbersome to write because they require additional effort outside of the forecasters’ core hazard assessment process.
Collaborative Visual Analytics offers practical methods to address handoff challenges by streamlining the process of collecting and organizing contextual information within existing analytic workflows, easing the burden of notetaking. While these methods have already demonstrated their value in domains like healthcare and investigative intelligence analysis, their effectiveness critically depends on them being appropriately integrated into a specific context of application. In collaboration with Avalanche Canada, we explore early design prototypes to understand how they might perform operationally and how to better tailor them to avalanche forecasting. Overall, forecasters thought our tools were easy to integrate into daily workflows and helpful for coordinating work. However, they also highlight specific challenges to be addressed. Drawing on lessons learned, we provide recommendations for successful implementation of such systems. This research highlights how dedicated digital handoff support tools could improve the efficiency and efficacy of team collaboration in avalanche forecasting.