User profiles and Learning Objects as ontology individuals to allow reasoning and interoperability in recommender systems

This work presents an alternative model to traditional educational recommender systems techniques. The model proposes the description of Learning Objects (LO) and User Profiles as OWL ontology individuals. We propose that the use of ontologies can be very helpful when we seek to accomplish an overall domain interoperability and knowledge description. It is also fundamental for our proposal that a common vocabulary is used. For that, the core of the ontologies are described with the use of the OBAA metadata standard, an extension to IEEE LOM that provides interoperability among hardware platforms for the Brazilian context. Also is part of this work to present a set of practices to develop educational Recommender Systems supported by ontologies.