The increasing frequency and intensity of wildfires require an extensive plan for efficient management and response to crises. The SILVANUS project is focused on creating an integrated platform that addresses the difficulties of managing wildfires by leveraging an ontology and knowledge base (KB). The construction of the ontology and the KB’s infrastructure are described in this study. They set the groundwork for a knowledge-driven strategy to handle ongoing wildfire threats. The background discusses the goals of the SILVANUS project and semantic technologies, highlighting the use of ontologies as management tools for forest fires. A thorough wildfire management ontology was created by utilizing domain-specific sources and ontologies to cover topics such as causes, climate, sensors, and tools. A methodical approach to ontology engineering was used in the technique, which included creating competency questions, gathering data, and classifying classes. The ontology evaluation met the requirements of the Ontology Summit 2013 and was thus of high quality and relevance. SILVANUS’s semantic data fusion used the CASPAR framework to merge data from several sources, including social media sensing and IoT sensors. Through the use of a semantic repository, data fusion, and semantic mapping, heterogeneous data could be efficiently integrated into a Knowledge Graph (KG). By combining several data sources, the KG, which is driven by SPARQL queries, facilitates the extraction of deep insights and improves decision-making abilities. With interdisciplinary cooperation and creative technological integration, this study provides a strong ontology and knowledge base architecture that are essential for tackling the complex problems of managing wildfires.