Abstract (EN):
There is a growing interest in the systematic and consistent collection of disaster
loss data for different applications. Therefore, the collected data must follow a set of
technical requirements to guarantee its usefulness. One of those requirements is the
availability of a measure of the uncertainty in the collected data to express its quality for a
given purpose. Many of the existing disaster loss databases do not provide such uncertainty/quality
measures due to the lack of a simple and consistent approach to express
uncertainty. After reviewing existing literature on the subject, a framework to express the
uncertainty in disaster loss data is proposed. This framework builds on an existing
uncertainty classification that was updated and combined with an existing method for data
characterization. The proposed approach is able to establish a global score that reflects the
overall uncertainty in a certain loss indicator and provides a measure of its quality.
Language:
English
Type (Professor's evaluation):
Scientific
No. of pages:
26
License type: