Since 2015, the Global Earthquake Model (GEM) Foundation and its partners have been supporting regional programs and bilateral collaborations to develop an open global earthquake risk model. These efforts led to the development of a repository of probabilistic seismic hazard models, a global exposure dataset comprising structural and occupancy information regarding the residential, commercial and industrial buildings, and a comprehensive set of fragility and vulnerability functions for the most common building classes. These components were used to estimate probabilistic earthquake risk globally using the OpenQuake‐engine, an open‐source software for seismic hazard and risk analysis. This model allows estimating a number of risk metrics such as annualized average losses or aggregated losses for particular return periods, which are fundamental to the development and implementation of earthquake risk mitigation measures.
8 April 2021 in Bulletin of Earthquake Engineering
Purpose: Using risk-related data often require a significant amount of upfront work to collect, extract and transform data. In addition, the lack of a consistent data structure hinders the development of tools that can be used with more than one set of data. The purpose of this paper is to report on an effort to solve these problems through the development of extensible, internally consistent schemas for risk-related data. Design/methodology/approach: The consortia coordinated their efforts so the hazard, exposure and vulnerability schemas are compatible. Hazard data can be provided as either event footprints or stochastic catalogs. Exposure classes include buildings, infrastructure, agriculture, livestock, forestry and socio-economic data. The vulnerability component includes fragility and vulnerability functions and indicators for physical and social vulnerability. The schemas also provide the ability to define uncertainties and allow the scoring of vulnerability data for relevance and quality. Findings: As a proof of concept, the schemas were populated with data for Tanzania and with exposure data for several other countries. Research limitations/implications: The data schema and data exploration tool are open source and, if widely accepted, could become widely used by practitioners. Practical implications: A single set of hazard, exposure and vulnerability schemas will not fit all purposes. Tools will be needed to transform the data into other formats. Originality/value: This paper describes extensible, internally consistent, multi-hazard, exposure and vulnerability schemas that can be used to store disaster risk-related data and a data exploration tool that promotes data discovery and use.