## 4 Designing an Ontology Framework: A Case Study on Asthma
### Design General Contextual Ontology  
An ontology is a formal framework that provides a structured and shared understanding of concepts, properties and their relationships within a particular domain. Ontologies consist of three core components:  
* Classes that represent entities or concepts in the domain (e.g., \"Disease\" or \"Symptom\");
* Properties that describe relationships between these entities (e.g., \"hasSymptom\");
* Individuals that serve as specific instances of these classes (e.g., \"Asthma\" as an individual of the class \"Disease\"; [PERSON], 2005) [61].  
We created an ontology using OWL-DL, a specialized language for describing ontologies, and developed it using the Protege editor from Stanford University, supported by the Pellet reasoner. A general contextual ontology was built to represent chronic diseases, comprising 10 main categories, as illustrated in Figure 3. These categories encompass key elements such as patient data, social factors, environmental conditions, and disease-related information. This flexible structure is designed to be adaptable to various chronic diseases by illustrating how these elements are interrelated.  
In the general contextual ontology (see Figure 3), \"Patient\" is the central category. It acts as a key point that separates the ontology into nine categories, including individual data, social factors, temporal context, organization and the environmental factors that affect the patient's context. Additionally, it covers information about physical activity, disease information, health events, relevant organizational contexts and service-level agreements that support healthcare services.  
Each of these categories can be further subdivided into subcategories. For example, \"Individual Data\" can be divided into subcategories addressing the patient's personal information. Similarly, all other categories can be subdivided based on the \"Patient,\" creating subcategories that focus on specific aspects of the chronic disease ontology, such as symptoms and treatments. These subdivisions help better organize and represent the interrelations within chronic disease management.  
Figure 2: Designing a general contextual ontology framework for the extended asthma ontology.  
The social and individual data ontology illustrates the factors influencing a patient's well-being, as shown in Figure 4. It captures the relationship between patients; their individual data, including attributes like age, gender, body mass index (BMI), nationality and location; and the social factors impacting their health, such as education level, income, quality of life and social relations. Temporal factors, including seasons and specific dates, are also represented as events associated with the patient.  
Figure 5 represents the environmental and allergy factors. Ontology demonstrates the interconnected factors influencing a patient's health. The environmental category includes elements such as air quality, pollution, temperature and humidity, as well as temporal factors like seasons and specific dates. Patients are further linked to healthcare organizations, such as hospitals and clinics, where care is provided. According to studies, these factors play a significant role in chronic diseases and allergies, affecting disease severity and requiring tailored medical attention.  
Figure 4: Patient ontology.  
Figure 3: General contextual chronic disease ontology.  
We then extended this general contextual ontology to asthma based on the related dataset by adding specific classes and properties related to asthma, such as pulmonary function test results (FEV1, FVC), depending on the dataset features.