A framework to assess quality and uncertainty in disaster loss data

Abstract

There is a growing interest in the systematic and consistent collection of disasterloss data for different applications. Therefore, the collected data must follow a set oftechnical requirements to guarantee its usefulness. One of those requirements is theavailability of a measure of the uncertainty in the collected data to express its quality for agiven purpose. Many of the existing disaster loss databases do not provide such uncertainty/qualitymeasures due to the lack of a simple and consistent approach to expressuncertainty. After reviewing existing literature on the subject, a framework to express theuncertainty in disaster loss data is proposed. This framework builds on an existinguncertainty classification that was updated and combined with an existing method for datacharacterization. The proposed approach is able to establish a global score that reflects theoverall uncertainty in a certain loss indicator and provides a measure of its quality.