OBAA-LEME: A Learning Object Metadata Content Editor supported by Application Profiles and Educational Metadata Ontologies

Abstract

This paper proposes an editor for Learning Object Metadata compatible with the Semantic Web. This tool uses two base ontologies, OBAA and VideoAula to provide the semantics to describe learning objects. These ontologies are the core for a tool to verify the consistency of the user-input data and realize inferences about the described information. Furthermore, this tool is mainly based on application profiles (derived from the base ontologies) that copes with the reasoning engine that verifies the description of the learning objects. The tool also serializes a learning object metadata ontology in an open server that can be reused in third-party applications.