# A Semantic Framework for Decision Making in Forest Fire Emergencies
## 2 Background and Related Work
### Ontologies and Ontology-Based Systems for Emergencies
When a user reports an emergency, the program responds with the protocol to be followed along with the actions to be taken and the involved organizations and resources. In this approach, the EmergencyFire ontology's interoperability reduces the probability of false compliance while improving response times in emergency situations. Moreover, the BACAREX ontology [29] is a component of the SIADEX framework, which facilitates the development of strategies for combating forest fires in the Andalusian regional government. BACAREX is a heavy-weight ontology of objects and contains resources (people, squads, vehicles, facilities, etc. ), activities (transport, water spraying, refueling, etc.) and additional data (GIS information, weather forecasting, etc.) related to the forest fighting plan. The ontology provides the information needed for the planning process. It keeps track of both organizational (e.g., the location of the object) and informative data for each object it maintains, such as the responder's radio channel for a specific forest area that may be required by the decision makers during a forest fire incident. This ontology contains more than 130 classes and more than 2000 instances only for planning objects and without taking into account the representation of activities. Furthermore, geo-ontology [30] is presented as an ontology representation of the meteorological disaster system. By extending the ontology to encompass a spatial and temporal context, geo-ontology enables the definition of concepts pertaining to the geospatial environment. These relationships can then be incorporated into reasoning statements during decision-making processes. Through the utilization of a multi-level ontology model, semantic support is provided throughout the entire emergency management cycle, covering activities such as risk assessment, resource preparedness, and emergency response for the periods before, during, and after the event. As a result, geo-ontology is suggested as a solution for addressing the challenges posed by the meteorological disaster system because of its geographic characteristics. The primary objective of this ontology is to meet the informational requirements of the planning and response stages of meteorological disasters. Semantic integration is applied in another highly relevant approach. [PERSON] et al. [31] present a geo-portal system in the area of wildfires using OntoFire ontology. This ontology comprises numerous concepts such as topography, vegetation, weather, climate, and fire in order to represent the semantic context of wildfires and their associated dangers. The relationships between the data can be uncovered by the suggested navigation mechanisms, which is otherwise not achievable when utilizing traditional querying approaches alone. Via the use of a browser, the user engages with the system by navigating to relevant geo-informational resources and learning about the semantic relationships therein. Graduate students with a wide background in geoinformatics and environmental risk management and users from local fire authorities evaluated the ontology and the system's capabilities using related scenarios and provided their feedback on the system's functionality. In the area of crisis management, BeAWARE ontology [32] represents crisis management techniques for climate-related emergencies such as floods, earthquakes, forest fires, etc. The ontology is a component of the decision support system developed in the context of the beAWARE EU-funded project [33]. BeAWARE ontology reuses and combines features from existing ontologies, such as MOAC [34] and SoKNOS [22], and merges all pertinent aspects of crisis management. This ontology incorporates heterogeneous data from crisis incidents and related impacts, sensor analysis, social media, and first responde unit allocations. BeAWARE ontology contains 38 classes, 21 subclasses, 37 object properties, and 22 datatype properties, which indicates that the suggested ontology is a lightweight ontology that can be readily adapted by different applications.