The Semantic Web role for interoperability in e-learning

Since the use of Semantic Web is becoming more popular as a new research direction in AEH to address the issues of interoperability and semantic-exchange, this section is dedicated to the application of Semantic Web in AEHS. The Semantic Web (Berners-Lee

et al. 2001) is, according to the W3C, a Web of data which provides a common

framework that allows this data to be shared and reused across applications, enterprises, and communities. It adds:

“The Semantic Web is an evolving collection of knowledge, built to

allow anyone on the Internet to add what they know and find answers to their questions. Information on the Semantic Web, rather than being in natural language text, is maintained in a structured form which is fairly easy for both computers and people to work with.” (W3C 2002a).

The Semantic Web can be understood as a vision where formally-described data on the Web can be readable and comprehensible by the computer as a machine rather than by humans. The machine is able to consume such data and deduce or infer relationships, meanings, reasons and answers to proposed questions, automatically without human interferences. Since the focus is on the data and not the processes, new technologies and protocols are introduced to reach a common understanding of this shared data. These include but are not limited to RDF19 and OWL20.

A distinction between Semantic “Web Services” and “Semantic Web” services is given in (Millard et al. 2008 ), where the former refers to Web services that apply the Semantic

19 _{Resource Description Framework, from: http://www.w3.org/RDF/} 20_{Web Ontology Language, from: http://www.w3.org/TR/owl-features/}

Web technologies and the latter are services designed to use the information on the Semantic Web.

In the context of e-learning, the Semantic Web is used as a reference for e-learning semantics. It aims to allow collaboration and interoperability through semantic meta-data applied to the learning resources. The Semantic Web here is usually applied within a SOA. A common description is needed to share this data across multiple applications using ontology. Ontology is a description or specification of a given domain and what is permitted in this specific domain. This includes concepts as well as relationships in this particular domain. Advantages of the application of Semantic Web technologies include: metadata, interoperability and reasoning (Millard et al. 2008 ). However, interoperability (issue of concern) is often quoted but rarely demonstrated (Millard et al. 2008 ). Yet it is seen as one of the possible advantages that is still pushing Semantic Web and its applications forward.

A number of e-learning frameworks applied Semantic Web technologies such APeLS (Conlan 2002) (section 2.9.2) or Personalisation Services (Henze 2005) (section 2.9.3), which are both adaptive systems. Other general (non-adaptive) e-learning systems include Question Bank (Millard et al. 2008 ) which provides a combination of Web services and Semantic Web technologies in a SOA, and argues that “Semantic Web” service has a lot to offer in terms of e-learning: easy development and easier mark-up resources to allow for external access and manipulation of the learning services.

The main link between AEH and the Semantic Web is the Web services’ technologies (Dagger et al. 2007); they allow for remote systems to communicate with adaptive services to create complex systems built from atomic services. Those adaptive services

take the advantages of the service ontology provided by OWL-S. It supplies them with a rich meta-data description and highly expressive framework for interoperability at a semantic level as well as at a technical level. This is applicable in terms of user’s data as well as learning content materials and links within a learning system.

On the other hand, a number of researchers are doubtful about the real possibility of agreeing on a common ontology (Marshall and Shipman 2003) and hence having a true Semantic Web working in practice. There are many issues surrounding the Semantic Web, critics question the practical feasibility of a partial fulfilment of what it promotes. Hence, consider it as an unrealistic idea and some critics even argue that there a real need for a Semantic Web. However, others who might believe that the Semantic Web is capable of delivering what it promises have problems with issues such as censorship and privacy. They believe that machine readability would make it much easier for information to be understood by automated content-blocking programs, hence can be used by governments to control Web access. Moreover, the geo-location meta-data can reveal the user’s location and therefore violets his/her privacy. Other developers, who might not be concerned with these issues but worry that the Semantic Web would make it much more time-consuming to create and publish content on the Web because of the need for two formats for humans and machines.

Nevertheless, although a lot of debate surrounds the Semantic Web in general, there might be more possibility of it becoming a reality in specific controlled domains, such as in a specific organisation (intra-company project) if not in the Web as a whole.

As mentioned earlier, the Semantic Web and the standard approaches are both working towards a goal of having a Universal Language (section 2.5). However, another problem

of a common language is that it could expand and become unreasonably large as will be described further in chapter 9.