Ontology-based Modelling and Reasoning for Forest Fire Emergencies in Resilient Societies

Every year, thousands of forest fires throughout the world cause disasters. One of the most critical challenges during a wildfire disaster is the effective management of heterogeneous information relative to the crisis to support human operators and authorities. Towards addressing this challenge, this paper presents an ontology-based framework for data representation and interlinking of wildfire events that are being used to foster advanced reasoning, situational awareness and interpretation for decision support. More specifically, we illustrate the capabilities of the ONTO-SAFE ontology to symbolically model contextual information in the domain, addressing application and user requirements promoting the creation of interoperable knowledge graphs. On top of the symbolic knowledge graphs, we define a rule-based framework for infusing expert knowledge in the form of constraints and rules to recognize patterns and situations of interest based on domain knowledge, assisting end-users in taking informed decisions and facilitating advanced decision-making.