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This paper investigates basic research issues that need to be addressed for developing an architecture that enables repurposing of learning objects in a flexible way. Currently, there are a number of Learning Object Content Models (e.g. the SCORM Content Aggregation Model) that define learning objects and their components in a more or less precise way. However, these models do not allow repurposing of fine-grained components (sentences, images). We developed an ontology-based solution for content repurposing. The ontology is a solid basis for an architecture that will enable on-the-fly access to learning object components and that will facilitate repurposing these components.