Enabling Knowledge through Structured Disaster Damage & Loss Data Management System

Abstract

Effective and efficient management of post-disaster damage and loss data is a key component of disaster risk reduction and climate change adaptation policies to fulfil the requirements of the Sendai Framework, Sustainable Development Goals, and more recently, the European Climate Law. However, the reality of organized and structured damage and loss data collection is still in its infancy. In the era of rapid technological improvements, with overwhelming volumes and channels of data, we still record a lack of basic figures of disaster losses at the scale, granularity and level of detail needed for most applications. First, a theoretical overview of data science applied to disaster risk management and the description of collection procedures and use of damage data for buildings in the case of earthquakes for Italy and Greece are provided. Second, the Information System (IS) which is intended to enhance damage and loss data collection and management proposed by the LODE (Loss Data Enhancement for Disaster Risk Reduction and Climate Change Adaptation) project is illustrated. The IS is described in detail, starting from the stakeholder consultation to elicit the requirements, to the system’s architecture, design and implementation. The IS provides a comprehensive tool to input and query multisectoral post-disaster damage and loss data at relevant spatial and temporal scales. The part of the IS devoted to building damage is described in depth showing how obstacles and difficulties highlighted in the collection and use of data in the Greek and the Italian case have been approached and solved. Finally, further developments of the IS and its background philosophy are discussed, including the need for institutionalized damage data collection, engineering of the developed software and re-engineering of current damage and loss data practices.