The Decision Support System (DSS) in forest fire management aims to extract information and knowledge to facilitate advanced decision-making. It supports human operators and authorities by mapping operational procedures, providing recommendations, and performing data analysis. The DSS integrates multiple data sets, provides advice to citizens, offers recommendations to decision-makers, and supports the prescribed burning process. It is useful in the prevention, preparation, detection, and response phases of forest fires, and can be used by various stakeholders identified by SAFERS according to established rules. In short, the DSS is an essential tool for effective forest fire management.
The main functionalities of the DSS are:
- Store data in the Knowledge Base Repository (RDF triplestore) following a standard ontology language (OWL2)
- Collect inputs from Intelligent Services
- Integration and interlinking of data from multiple heterogeneous sources (locations, weather, earth observations, etc.)
- Homogeneous representation of data in the form of Knowledge Graphs
- Semantic reasoning
- Ability to infer implicit knowledge from explicitly asserted facts residing in the ontology.
- Based on predefined rules and policies defined by the users, implemented as a set of queries over the interlinked Knowledge Graphs (KGs)
- Provide decision support.
- Generate automatically color coded bullettins according to user-selected rules.