Search

Visualisations are powerful communication tools that have the potential to help societies assess and manage natural hazard and disaster risks. However, the diversity of risk management contexts and user characteristics is a challenge to develop understandable and useable visualisations. We conducted a systematic literature review to understand the current state developing disaster risk visualisations following design best practices and accounting for the heterogeneity between end-users and disaster risk contexts. We find that, despite being widely recommended, tailoring visualisations to users through the process of user-centred design remains a relatively unexplored topic within disaster risk. To address this, we present a unifying user-centred design framework for disaster risk visualisation, based on existing visualisation frameworks. The framework contains three phases: the Define phase, which aims to define and characterise the disaster risk management context and end-user group who will benefit from a visualisation; the Design phase, which is highly iterative and presents an opportunity to test how users interpret different design elements; and the Refine phase, which focuses on evaluating how users understand, respond to, and make decisions based on the visualisation. The framework is sufficiently flexible to be applied to any disaster risk management and natural hazard context to identify challenges and design effective disaster risk visualisations that are understandable and useable.

While social network analysis continues to enjoy considerable attention, literature on social network data collection often lacks explicit attention to methods. This presents special challenges to approaching the problems of undertaking social network analysis and of studying disaster preparedness, planning, and, ultimately, risk reduction. In this paper, we address this issue by presenting our synthesis of several strategies for network analyses from our processes for network identification and data collection in a longitudinal study of multi-jurisdictional, inter-agency wildfire response networks in the American Northwest. In the course of this ongoing project, the process of detecting and collecting data on pre-existing and emergent networks in the real world was not a matter of one theoretical or empirical judgement, but rather several. We alternated between: (1) spatio-ecological detection of jurisdictions adjacent to areas at-risk for large wildfires; (2) a hybrid approach to selecting actors and agencies identified as common participants in wildfire response networks; and (3) event-based detections of parties to specific wildfire response networks. We conclude with steps for thinking through network identification and bounding, integrating networks, conceptualizing rosters and ties in initial and events-based phases, and how to manage longitudinal network data collection. Published version