Context Ontology for Humanitarian Assistance in Crisis Response

Massive crisis open data is not fully utilized to identify humanitarian needs because most of it is not in a structured format, thus hindering machines to interpret it automatically and process it in a short time into useful information for decision makers. To address these problems, the paper presents a method which merges ontologies and logic rules to represent the humanitarian needs and recommend appropriate humanitarian responses. The main advantage of the method is to identify humanitarian needs and to prioritize humanitarian responses automatically so that the decision makers are not overwhelmed with massive and unrelated information and can focus more on implementing the solutions. The method is implemented on real data from the Hurricane Wilma crisis. The use of the method in the hurricane Wilma crisis shows the potential abilities to identify the humanitarian needs in specific places and to prioritize humanitarian responses in real time