A Conceptual Model for Grid Learning Services Automatic Composition

This work proposes an initial model for the automatic composition of Grid based learning services based on the semantic capabilities and metadata of e-learning frameworks. There are three principal motivations for Learning Grid Services Composition: build a more powerful service using basic existing services, fulfill service requester’s requirement better, and enhance resource reuse while reducing the cost and time of a new service development. Let us consider a learning Grid as a set of resources and services distributed in a network with the service model based on the IMS abstract framework [1], where learning services can be composed by others allocated in different repositories inside the network. The model we propose for the automatic composition of learning services is based on the use of the defined syntactic and semantic characteristics of the different levels of services involved in the Learning Abstract Framework. The design of the model is presented in the Fig. 1 and is described below.