Semantic Web: Ontological Engineering for Knowledge Services

Ontology has been collecting a lot of attention recently. In fact, it has potential for resolving several key problems such as semantic tag design for semantic web, semantic integration, knowledge sharing/reuse, etc. However, it is also true that people have different understanding of ontology. This article is written to contribute to clarification of the understanding of ontology and ontological engineering and to promotion of its utility. Although the discussion is made in the context of Artificial Intelligence in Education domain, I believe the content is pretty general.

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Ontological Engineering and the Semantic Web

Advanced Techniques in Web Intelligence - I - Studies in Computational Intelligence ◽

10.1007/978-3-642-14461-5_8 ◽

2010 ◽

pp. 191-224 ◽

Cited By ~ 3

Author(s):

José Manuel Gómez-Pérez ◽

Carlos Ruiz

Keyword(s):

Semantic Web ◽

Ontological Engineering

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Semantic Web services

Agency and the Semantic Web ◽

10.1093/oso/9780199292486.003.0013 ◽

2006 ◽

Author(s):

Christopher Walton

Keyword(s):

Semantic Web ◽

Web Applications ◽

Automated Processing ◽

Common Goals ◽

Common Interests ◽

Definition Of ◽

Key Techniques ◽

Build Systems ◽

Knowledge Services

In this book we have been consistently directed by the vision of the Semantic Web. This vision can be summarized as the ability for computers to automatically use information on the Web in a similar way to humans. In particular, we want to be able to retrieve, comprehend, and exchange knowledge using automated techniques. At this point we have defined all of the main techniques that can be used to realize these goals. A summary of the four key techniques that we now have at our disposal is presented below: 1. We have the ability to represent knowledge in a form suitable for automated processing. This ability is provided by the definition of ontologies, which provide structure to knowledge. 2. We can construct entities, called agents, which act on behalf of humans and solve specific goals. We have presented many different techniques that can be used to construct these agents, dependent on the purpose for that the agents to be applied. 3. We can reason about the knowledge that we represent to answer specific questions. This can be accomplished by query answering techniques, or by complex inferences over the knowledge, guided by the ontology. 4. Our agents can communicate with other agents, and form societies based on common interests. Within these societies, agents can collaborate towards the resolution of common goals, which could not be accomplished by individual agents alone. The purpose of this penultimate chapter is to show how we can harness and combine these four key techniques to build systems and applications for the Semantic Web. As stated in Chapter 1, Semantic Web applications are not constructed statically in the traditional manner. Instead, these applications are constructed dynamically, at run-time, from combinations of services, termed knowledge services. Our presentation is designed to answer the two key questions below: 1. How can we construct knowledge services that encompass the various capabilities that we have available? 2. How do we compose knowledge services into applications that can accomplish specific tasks?

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