# Towards Collaborative and Dynamic Spectrum Sharing via Interpretation of Spectrum Access Policies
## 4 Ontology
### A DSA Ontology  
Since our approach heavily relies on an ontology, we first provide a brief overview of the overall structure of the ontology. Ontologies, similarly to other engineering artifacts, such as hardware or software, are built in a modular and hierarchical fashion. The structure of our Dynamic Spectrum Access (DSA) ontology (here, termed OntoDSA) is shown in Figure 6. The arrows in this figure represent the \"import\" relationships. OntoDSA imports SpectralSPARQL [13], which, in turn, imports GeoSPARQL [14], as well as ontologies to describe Lists and Uncertainty (both of them import the Nuvio foundational ontology [15]). The structure of SpectralSPARQL is patterned upon GeoSPARQL [14]--an Open Geospatial Consortium (OGC) standard extension of SPARQL. GeoSPARQL provides a common representation of geospatial data in RDF [12] and facilitates querying and filtering of such data based on relationships between geospatial entities. The standard consists of an ontology of geospatial concepts, a set of SPARQL [16] functions and query transformation rules. With GeoSPARQL, one can express high-level queries that ask about specific geographic objects of features, their attributes and relations between them. SpectralSPARQL is built on top of the base ontology, Nuvio [15], and thus includes its top-level classes: Attribute, InformationEntity, Object, Process, Situation, UnitOfMeasure and Value; all mutually exclusive. Each of the classes in SpectralSPARQL are subclasses of at least one of these concepts. The two top-level concepts in Nuvio are Object and Process--entities that are either wholly represented or that can only be partially represented at any given snapshot of time, respectively. The three fundamental objects in SpectralSPARQL are Signal, Receiver and Emitter. The process subclasses are used to model different activities that the objects can participate in. For instance, an emitter can participate in a frequency hopping transmission. Figure 6: The Architecture of the DSA Ontology. The subclasses of the Attribute class model properties for describing both objects and processes. Some of them are simple quantities with associated units of measure, e.g., Frequency with FrequencyUnit, while others are more complex and require special-purpose properties to fully define them, e.g., FrequencyRange with object properties referring to the minimum and maximum values of the range. There are three major Attribute categories (subclasses): Spectral, Temporal and Signal. The first one is the central focus of the SpectralSPARQL functions. The SpectralAttribute class was modeled in a similar fashion as Feature in GeoSPARQL. It is used to define SpectralSPARQL functions that calculate relationships between two different spectral attributes, e.g., the intersection, regardless whether they are single frequencies, frequency sets or ranges, very similar to the _Intersects_ query function in GeoSPARQL. The OntoDSA ontology imports all of the above by simply importing SpectralSPARQL. The most significant classes in this ontology include Policy, Rule and the SAPHyperspace classes. These classes relate directly to the following Spectrum Access Policy (SAP) use cases implemented by the CRE:  
* Each instance of the Policy class can be related to many instances of the Rule class by the property _hasRule_. It may also have several data property assertions, such as _hasID_ or _hasRevision_. * Instances of the Rule class can be related to instances of the SAPHyperspace by the property _governs_, denoting a relationship between a SAP rule and the spatio-spectr-temporal region that it applies to. Properties of each rule, such as its _ID_, _revision_, _type_ (with the value of either _allow_ or _deny_), or _maximum transmit power_, are asserted directly on the instance of the Rule class. * Instances of the SAPHyperspace class represent spatio-spectro-temporal regions that are governed by some SAP rules. The term _spatial_ is interpreted here in a more abstract sense, more than just the physical space.