An Assistant for Loading Learning Object Metadata: An Ontology Based Approach

In the last years, the development of different Repositories of Learning Objects has been in-creased. Users can retrieve these resources for reuse and personalization through searches in web repositories. The importance of high quality metadata is key for a successful retrieval. Learning Objects are described with metadata usually in the standard IEEE LOM. We have designed and implemented a Learning Object Metadata ontology (LOM ontology) that establishes an interme-diate layer offering a shared vocabulary that allows specifying restrictions and gives a common semantics for any application which uses Learning Objects metadata. Thus, every change in the LOM ontology will be reflected in the different applications that use this ontology with no need to modify their code. In this work, as a proof of concept, we present an assistant prototype to help users to load these Objects in repositories. This prototype automatically extracts, restricts and validates the Learning Objects metadata using the LOM ontology.