## 4 Use Case Evaluation
### Building the Scenario RDF Knowledge Graph  
The RDF knowledge graph (KG) is designed to identify an environmentally friendly route using environmental sensor data from IoT entities and open data entities. Each entity in the scenario, such as _IoTEntity_, has sensors that measure values for temperature, humidity, and air quality. These entities have relationships with other entities, which are represented using properties such as _hasCoSemanticsRelationshipWith_ and _hasCoworkRelationshipWith_. These relationships are used to determine the most environmentally friendly route to take.  
In the RDF KG for this scenario, there are three IoT entities with different types of measurements, and two open data entities that provide different types of data. There are also three types of relationships between these entities, including _co-location_, _co-work_ and _co-semantics_ relationships with different proximity and similarity values.  
Specifically, we have the following:  
* _Co-location_ relationships between _IoTEntity1_ and _IoTEntity2_, and between _IoTEntity2_ and _IoTEntity3_, with different proximity values;
* _Co-semantics_ relationships between _IoTEntity1_ and _OpenDataEntity1_, and between _IoTEntity2_ and _OpenDataEntity1_, with different similarity values;
* A _Co-work_ relationship between _OpenDataEntity1_ and _OpenDataEntity2_, with a proximity value.  
The _GreenRoute_ resource in the KG is of type _s2 netm:Route_, and has properties describing its start and end locations, as well as whether it is optimal or not. The graph also includes information about the green route passing through three IoT entities (_IoTEntity1_, _IoTEntity2_, _IoTEntity3_), as well as two open data entities (_OpenDataEntity1_, _OpenDataEntity2_). Appendix A provides the RDF code for the Green Route scenario, utilizing the S2 NeTM Ontology.  
Figure 6: End-user application for Green Route.  
Figure 7 presents a visual representation of the RDF KG for the Green Route use case scenario, which uses the S2 NeTM ontology. The use of color coding and clear labeling of the classes, instances, and properties helps to make the relationships between the entities in the scenario easily understandable. The yellow boxes in the figure represent the classes defined in the ontology, such as _User_, _Location_, _Sensor_, _IoTEntity_, _OpenDataEntity_ and others. The green boxes represent the instances of these classes, such as [PERSON] (an instance of _User_) and PiraeusPort (an instance of _Location_). The white boxes represent the instances of properties, such as _hasName_, _hasLat_, and _hasLong_. The visualization in Figure 7 provides a clear and concise representation of the relationships between the different entities in the scenario RDF KG. For example, it shows that [PERSON] is an instance of the _User_ class, and that she has a name (_hasName_) and a location (_hasLat_ and _hasLong_). It also shows that the PiraeusPort of is an instance of the _Location_ class, and that it has a location with latitude and longitude values.  
Furthermore, Figure 7, shows the relationships between the instances of the different classes. For example, it shows that _IoTEntity1_ is an instance of _IoTEntity_, and has a sensor (_hasSensor_) named _Sensor1_ that has a sensor type (_hasSensorType_) called _TemperatureSensor_. It also shows that _IoTEntity1_ has a _co-location_ relationship with _IoTEntity2_, and that _IoTEntity2_ has a _co-location_ relationship with _IoTEntity3_ with proximity values (_hasLocationProximity_) of 50 and 10, respectively.  
Figure 7: RDF knowledge graph for Green Route scenario.