Proposal of a Multi-agent System for Indexing and Recovery applied to Learning Objects

There are a variety of specifications and metadata standards used to describe learning contents. A learning content, along with the file containing the descriptive metadata, constitutes the learning object. Learning objects can be stored in a repository and used in the process of teaching and learning. The heterogeneity of metadata standards used to describe learning objects creates difficulties to reuse of these objects. Applications that seek to recover learning objects cannot interoperate with different repositories, which contain objects described according to different metadata standards. This paper proposes a multi-agent system, wherein agents can index and retrieve learning objects that are contained in different repositories and described with different metadata standards. These agents use an ontology that is the result of the union of all the ontologies that contextualize the existing metadata standards.