Big data-driven disaster resilience

Abstract

Considering the importance of the potentiality of leveraging big data for enhancing resilience for disaster management, this study focused on the recent technology explored by various scholars on big data -based disaster resilience which can help people in all stages of disaster management. This study reveals that disaster resilience is a combined function of the adaptive, absorptive and transformative capacity of an individual or society to withstand and cope with the adverse effects of the disaster. This study explores the potential of big data in various stages of disaster management which can ensure the resilience capacity of a social unit. This chapter also highlights the major principles of big data for effective use for disaster management like open source tools, strong infrastructure, developing local skills, context -specific data sources, data sharing with ethics, awareness about the right of data and learning from experience. It also argues that big data is a potential tool for policymakers, administrators and related stakeholders to take necessary actions during and after disasters like early warning system, weather forecasting, emergency evacuation, immediate responses, relief distribution, training need assessment and increasing trained individuals. For getting maximum benefit from big data approach for disaster resilience, this study suggests to solve the related problems such as challenges in data collection, analytics, infrastructure, gaps between human and technological capacity, ethical and political anomaly, poor coordination, privacy and accuracy. This study recommends implementing proper infrastructure, technologies, tools and expertise for ensuring proper utilization of big data for disaster resilience. This study also focuses on further research on big data approaches for enhancing disaster resilience in context -specific cases by collecting primary data which can help to extend the use of it over the world.