On a worldwide scale, research groups working on vulnerability have varied interests and areas of expertise. Each research group will typically respond to the need for a standardised literature review on vulnerability data and functions by producing offline data repositories (i.e., spreadsheets) that are only used internally, infrequently updated (if not totally abandoned at the end of a project), and/or maybe recreated again on a different occasion using a different data organisation format. Typically, these repositories are not big and often limited to specific hazards or assets (i.e., the specific use case of a research project). The issue with this modus operandi is that the data on vulnerability, which is not per se' large in volume, especially for some countries and assets, is scattered across multiple, partially overlapping but overall incomplete, non-standardised, and not comprehensive offline databases that are not shared with the wider research community. These offline databases may also contain vulnerability data and functions that are collected locally and are not published in research journals (i.e., grey literature).
The data paucity and the importance of a correct estimation of vulnerability for loss modelling makes vulnerability data and functions high-value datasets. Local data are particularly valuable because they are hard to find and because they best represent local conditions of the exposed building stock. Unfortunately, the value of vulnerability datasets is diluted by the fragmentation deriving from the existence of multiple repositories, by the difficult of knowing the existence of the offline, unpublished ones, and by the inability to access the contained data.
In recognition of this, in 2018, UCL EPICentre developed MOVER, a “Multi-Hazard Open Vulnerability platform for Evaluating Risk” as part of the GFDRR Challenge 3 project. The MOVER data schema, provided a rational, peer-reviewed and tested data schema for the collection of physical and social vulnerability data and models and it was designed to accommodate both social and physical vulnerability data evaluated at different geographical scales and also supports a gridded system of data entry. In terms of physical vulnerability, it captured data and models pertaining to a range of different assets (people, crops, residential buildings, industrial warehouses, commercial properties, schools and hospitals, and key components of water, electricity, gas, telecommunications, and transportation networks) for a number of different natural hazard (strong winds, earthquakes, riverine floods, storm surge, landslides, tsunami, drought and volcanic ash). The MOVER database schema had a modular structure to favour future expansion (as new data and vulnerability models became available). MOVER consisted of 4 separate modules; (a) the Vulnerability, Fragility and Damage to Loss Functions module, (b) the Physical Indicators module, (c) the Social Indicators module, and (d) the Physical, Social and Hybrid Indices module. A consistent taxonomy, largely based on the GEM taxonomy, was used throughout .
In 2019, as a result of our continued commitment to keep up to date with vulnerability research, we modified MOVER making the taxononomy used to identify hazards and processes, as well as intensity measures and damage scales, consistent with Think Hazard! But we knew that our work was not finished.
Today, in 2021, We bring you MVDat. Happy browsing!
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