RDF and RDF Schema
As mentioned above, XML by itself is meaningless. RDF (Resource Description Framework) comes to cope with it. RDF is used to express the meaning of entity and its relationship through a statement. A statement is a form or structure containing 3 important elements, namely Subject, Predicate, and Object also known as Triple. With RDF on the document, machine can easily identify each entity and how they are related. For instance “Qillbel” as the first entity (Subject) has relation (Predicate) “is the owner of” a second entity (Object), “Luwak Coffee Shop”.
This structure is the basic and natural way to describe the huge amount of data processed by machine. Each element is identified by unique URI that makes a concept are not just a word, but are tied to a unique definition that everyone can find on the Internet (Berners-Lee, Hendler, & Lassila, 2001).
In order to define properties and data type, RDF needs particular vocabulary known as RDF Schema. RDF Schema is can be defined as a vocabulary description language for describing properties and classes of RDF resources, with a semantics for generalization hierarchies of such properties and classes (Antoniou & Van Harmelen, 2004). The presence of RDF Schema provides modeling primitives for organizing RDF vocabularies hierarchically. By using RDF Schema, we can define the vocabulary; specify which properties apply to which kinds of object and what values they can take; and describe the relationships between object. Thus, RDFS makes semantic information machine-accessible, in accordance with the Semantic Web vision (Antoniou & Van Harmelen, 2004).
Although the RDF and RDF Schema provide some benefits to the concept of Semantic Web, they are limited to some extends. They are not expressive enough to interpret the meaning of the content of the Web. Semantic Web needs something that much more expressiveness. One solution is by using Ontology.
Ontology is one of the important parts in Semantic Web technology. Its role is to provide a set of inference rules that can be used to perform automated reasoning. This is important for the concept of Semantic Web since logics needs to be attached to the web in order to discover the meaning of information on the web. As we know that the terms or the XML codes attached in the web page hold the hidden meaning, this meaning can be defined by pointers to ontology by using unique URI. Therefore, the hidden meaning can be understood by machine and ambiguity can be avoided.
Further, as every domain has its own jargon, the existence of ontology’s file defines the relations among terms. This means that ontology can be used as a platform to shared understanding of a certain domain and can support a meaningful. With this concept, web application can reason about different worlds and environments and make a connection between them (Hella, 2014).
As a Semantic Web background, the benefit of using ontology is for information management and exchange that allowed reasoning service analyzes the knowledge stored in the resources (Hella, 2014). It can also enhance the accuracy of result in search engine since the searching is based on the meaning of the concept, rather than the ambiguous keywords. As a result, we can improve the functioning of nowadays Web when ontology is implemented.