Exploring Semantic Description and Matching Technologies for Enhancing the Automatic Composition of Grid based Learning Services

Abstract

In the implementation of e-learning frameworks, a problem still unsolved is how to use and integrate low-level learning services to compose more complex high-level services or tools that make sense to both tutors and learners. In that sense semantic description of Grid learning Services appears like a powerful tool to be used for discovering and matching learning services depending of a set of parameters inside the learning framework. These parameters must represent significant functional characteristics of a learning Grid environment formed by a set of distributed e-learning resources and services. The main objective of this article is to present a review of existing technologies related with semantic description and matching and some techniques used at present to provide Grid Learning Tools and Services automatic composition.