# A Semantic Framework for Decision Making in Forest Fire Emergencies
## 6 Evaluation
### Structural Ontology Evaluation  
An important area of study in ontology engineering is ontology evaluation [50]. For evaluating the structure of ONTO-SAFE ontology with OntoMetrics [51] framework, the ontology was populated with data related to anomalies, weather forecasts, and prescribed burns. The OntoMetrics framework includes five types of ontology quality metrics: base, schema, knowledge base, class, and graph metrics. These metrics serve as indicators of ontology quality and are associated with various factors including accuracy, understandability, cohesion, computational efficiency, and conciseness [52]. Table 4 presents the results derived from the analysis by the OntoMetrics tool. According to the OntoMetrics tool, base metrics are simple metrics that display the number of ontology elements, such as counting classes, axioms, objects, etc. Based on the total number of classes and characteristics, the suggested ontology can be characterized as a lightweight ontology that could be easily adopted by diverse applications where the full expressive power of a more complex ontology is not necessary or practical. In addition, _DL expressivity_ is designed to describe and reason about structured knowledge in a formal and logical manner and indicates the Description Logic type of ontology. ONTO-SAFE ontology is under the expressivity of the \(AL(D)\) Description Logic, which indicates that it can be suitable for various applications, as AL is the base language and the smallest DL language that can be detected by reasoners (e.g., Pellet) [53]. Regarding the schema metrics, they are concerned with the design of the ontology. Metrics in this category show an ontology schema design's richness, width, depth, and inheritance. _Attribute richness_ refers to the average number of attributes per class and can be used as a metric for evaluating both the efficacy of an ontology's design and the volume of information that is pertinent to instance data. The greater the number of qualities defined, the more knowledge the ontology provides. The _inheritance richness_ metric describes how information is distributed across different levels of the ontology's inheritance tree. This is a reliable indication of how well the ontology organizes knowledge into various categories and subcategories. This value for ONTO-SAFE ontology is above the middle levels, which indicates that the conception level is sufficient. _Relationship richness_ is determined by dividing the count of non-inheritance relationships (such as object properties, equivalent classes, and disjoint classes) by the total number of relationships specified in the schema. This measure indicates how diverse the ontology's relation types are. For instance, in the case that ontology includes only inheritance relationships, it represents less information compared with an ontology with diverse relationships. \begin{table}
\begin{tabular}{c l l} \hline \hline
**Category** & **Description** & **Results** \\ \hline Base Metrics & Class count & 80 \\  & Object property count & 54 \\  & Data property count & 24 \\  & DL expressivity & AL(D) \\  & SubClassOf axioms count & 40 \\  & Object property domain axioms count & 45 \\  & Data property domain axioms & 27 \\  & count & 0.358209 \\  & Inheritance richness & 0.597015 \\  & Relationship richness & 0.52381 \\  & Average population & 70.089552 \\  & Class richness & 0.044776 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: Ontology metrics produced by the OntoMetrics tool. In addition, the knowledgebase metrics are based on the instance metrics, which are used to calculate the quantity of real-world knowledge represented by the ontology. The _average population_ metric indicates the number of instances in relation to the number of classes. The result shows how successfully the data extraction procedure was carried out in order to populate the knowledge base. The respective value of this metric in the proposed ontology is high which indicates that the knowledge represented is more than satisfactory.