The purpose of this chapter is to examine the requirements of Knowledge Management (KM) services deployment in a Semantic Grid environment. A wide range of literature on Grid Computing, Semantic Web, and KM have been reviewed, related, and interpreted. The benefits of the Semantic Web and the Grid Computing convergence have been investigated, enumerated and related to KM principles in a complete service model. Although the Grid Computing model significantly contributed to the shared resources, most of KM tools obstacles within the grid are to be resolved at the semantic and cultural levels more than at the physical or logical grid levels. The early results from academia, where grid computing still in testing phase, show a synergy and the potentiality of leveraging knowledge, especially from voluminous data, at a wider scale. However, the plethora of information produced in this environment will result in a serious information overload, unless proper standardization, automated relations, syndication, and validation techniques are developed.
Berners-Lee (2001) the pre-eminent thinker of the Internet world, state that Semantic Web is not a separate Web, but an extension of the current one, in which information is given well-defined meaning, better enabling computers, and people to work in cooperation. In view of that, Daconta et al. (2003) report that Tim Berners-Lee has a two-part vision for the future of the Web. The first part is to make the Web a more collaborative medium. The second part is to make the Web understandable, and thus processable, by machines. This futuristic thinking found its way to reality, where Semantic Web Services contribution through XML protocols has been enriching the Web with outstanding collaborative features. The Web Services has been defined by Daconta et al. (2003) as software applications that can be discovered, described, and accessed based on XML and standard Web protocols over intranets, extranets, and the Internet.