Discovering Requirements for the Technology Design to Support Disaster Resilience Analytics

Introduction

When standing to watch on a ship, a sailor looks both internally and externally to assess risk to the vessel. Internally, a watch will assess ship systems and condition of the vessel, and externally, monitors the sea state and relative position to other vessels. Much of this is easily automated through modern technology and the information is readily available, however, there are other important factors a boat watch must consider: what is the condition of the crew? Are they overwork? Well rested? Has an illness recently affected their effectiveness? This impacts the vessel’s ability to accomplish its task as a weakened crew increases risk. Additionally, other vessels in the area are easily monitored minute to minute via technology but knowing their onboard conditions (a mechanical failure or a medical emergency discoverable through a simple radio call to the boat) can affect or explain erratic navigation and decrease the danger to all nearby. An observation deck, based on the ancient concept of a ship’s crow’s nest, the highest part of the boat that assesses risk and reiterates the process of assessment with each subsequent watch. Risk assessment not just by measurable or easily observable information, but social activity and states providing a holistic determination regarding the level of safe operation while underway. This paper addresses the needs for designing technologies to enable such an analogous view of the state of a community for disaster resilience (NIST, 2018).

Risk management and analysis has been discussed widely in crisis management literature (Blaikie et al., 1994; Cutter et al., 2008; Peduzzi et al., 2009). Although the crisis informatics (Palen and Anderson, 2016) research has mainly focused on the use of Information and Communication technologies (ICTs) for better emergency response, understanding public behavior in the response, and the design of efficient response technologies. The areas of technologies range from big data analytics to interactive visual analytics including information and knowledge management, machine learning, information retrieval, data mining, network science, social media mining, simulation and modeling, and information visualization across a genre of structured to unstructured big data sources (Castillo, 2016). Likewise, the existing tools are available as open source as well as proprietary emergency management platforms (Kumar et al., 2011; Imran et al., 2014; Sheth et al., 2017; Poblet et al., 2017; Karuna et al., 2017). However, the intended use-case of such existing technologies and tools has been centered around response coordination after a disaster event (Hristidis et al., 2010; Teodorescu, 2014; Imran et al., 2015; Simon et al., 2015; Reuter and Kaufhold, 2017; Li et al., 2017; Poblet et al., 2018). There is a lack of research focus on technologies design requirements to assist different phases of crisis management and likewise, exploring and evaluating the cross-phase uses of the disaster response-centric technologies to create more resilience for a community.