Towards a Repository for Datasets of Mass Casualty Incidents

Abstract

Many mathematical models and algorithms addressing logistics around mass casualty incidents (MCI) have been proposed in the literature. However, hardly any data sets exist that can be used to analyse, validate, and evaluate approaches and solutions. As MCI are comparably rare, real-world data is scarce and often extremely sensitive, making it difficult for researchers to get access and build test datasets. In this paper, we therefore present the first
steps towards a repository for the exchange of datasets to facilitate validation and comparison. We first provide an overview of potential stakeholders such as working groups, review disaster-related databases and existing repositories for other fields followed by a preliminary taxonomy to identify and structure the relevant entities and their characteristics within models for disaster management.