A Linked Dataset of medical educational resources.

• Autores: Stefan Dietze, Davide Taibi, Hong Qing Yu, Nikolas Dovrolis
• Localización: British journal of educational technology, ISSN 0007-1013, Vol. 46, Nº. 5, 2015, págs. 1123-1129
• Idioma: inglés
• Texto completo no disponible (Saber más ...)
• Resumen

  • Reusable educational resources became increasingly important for enhancing learning and teaching experiences, particularly in the medical domain where resources are particularly expensive to produce. While interoperability across educational resources metadata repositories is yet limited to the heterogeneity of metadata standards and interface mechanisms with a lack of shared or aligned controlled vocabularies, Linked Data ( LD) principles, based on W3 C standards and supported through a wide range of tools, open up opportunities to alleviate such problems. We introduce the 'm Educator Linked Educational Resources' dataset, which offers a range of open educational resources for the medical domain, exposed through LD principles. Data have been generated through a combination of manual curation and semi-automated harvesting techniques, and state-of-the-art enrichment and clustering techniques were deployed in order to classify and categorize data, toward improved reusability and access. Data are currently used by a range of educational applications and is accessible for third parties and developers, for instance through the Linked Up Catalog and other registries, to facilitate further take-up and applications. [ABSTRACT FROM AUTHOR]