Rathnasinghe, A.P. and Kulatunga, U., 2019. Potential of using big data for disaster resilience: The case of Sri Lanka. In: Sandanayake, Y.G., Gunatilake, S. and Waidyasekara, A. (eds). Proceedings of the 8 th World Construction Symposium, Colombo, Sri Lanka, 8-10 November 2019, pp. 493-501. DOI: doi.org/10.31705/WCS.2019.49. Available at: https://2019.ciobwcs.com/papers 493 POTENTIAL OF USING BIG DATA FOR DISASTER RESILIENCE: THE CASE OF SRI LANKA A.P. Rathnasinghe 1 and U. Kulatunga 2 ABSTRACT The epoch of big data is evolving new possibilities for Disaster Management (DM). The concept of Big Data has been constantly scrutinised in terms of data creation, storage, retrieval, and analysis where professionals have identified its significance upon the volume, velocity and variety. Big Data provides the opportunity to gather more information in less time. Hence, analysis of Big Data can substantially enhance various disaster resilience activities such as issuing early warnings for evacuations; help emergency response personnel to identify areas that need urgent attention; coordination of disaster management activities; and to identify the most effective response methods for various situations. Therefore, Big Data is identified as a great catalyst for disaster response and, for better understanding of the damage situation and decision-making. Moreover, Big Data has the potential to improve disaster resilience by connecting people, processes, data and technology. However, it is essential to understand the type of Big Data that needs to be generated, to develop the data analysis as in necessary to help with real time responses, decision making and tracking of disaster victim. In order to accomplish the aim, a qualitative research approach was followed. This topical study marked the importance of big data in predicting human behavioral patterns during a disaster. Accordingly, the effective management of human and physical resources in habitual disaster territories was appraised through existing case studies in developed countries. Further, the research has successfully identified the challenges in employing Big Data upon its legal and technological barriers. Keywords: Big Data (BD); Disaster Management (DM); Disaster Resilience. 1. INTRODUCTION Ample natural and human induced disasters strike across the world frequently while mislaying thousands of lives and several more from their habitats and destroying vast amounts of properties (Altay and Green 2006; Galindo and Batta 2013). According to the World Disaster Report of 2015, “more than eight hundred thousand people are killed, and about two billion people were affected by six thousand natural and technological disasters around the world during the last decade” (Hamza, 2015, p.05). Therefore, the effective management of disasters can result in saving an uncountable number of human lives. Accordingly, the concept of DM is comprised of three segments: vigilance, reaction, and retrieval (National Academies Press, 2006). Thus, the assembling, archiving and analysis of disaster related data in a proficient manner is vital for an effective DM. Upon that view, 1 Department of Building Economics, University of Moratuwa, Sri Lanka, akilapr1993@gmail.com 2 Department of Building Economics, University of Moratuwa, Sri Lanka, ukulatunga@uom.lk