Towards Educational Metadata Interoperability on Semantic Web

André Behr, Tiago Primo, Rosa Viccari


Metadata is broadly used to describe learning objects and its standards have been developed to improve interoperability. With the current Web extension by the Semantic Web, learning object metadata has been migrating from XML-based metadata standards to semantic metadata standards. This work explores XSLT to provide a solution for this transition of descriptions to educational metadata. The approach consists of retrieve, convert, and store metadata in Semantic Web context. In this work, we converted OBAA metadata in XML to OWL format. The OWL format aims to give more semantic and improve the reasoners inference capabilities. The converted metadata can be managed by different applications and systems. In addition, we have been working in OWL to OWL mappings through aligned ontologies.

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