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A linked dataset of medical educational resources

  • Stefan Dietze
    ,
  • Davide Taibi
    ,
  • Hong Qing Yu
    ,
  • Nikolas Dovrolis
  • Leibniz University Hannover
    ,
  • National Research Council of Italy
    ,
  • Democritus University of Thrace
Research Output: Contribution to journal Article Peer-review

Open access

Abstract

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 W3C standards and supported through a wide range of tools, open up opportunities to alleviate such problems. We introduce the “mEducator 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 LinkedUp Catalog and other registries, to facilitate further take‐up and applications.

Publication Information

Output type

Research Output: Contribution to journal Article Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 899-1129

Journal (Volume, Issue Number)

British Journal of Educational Technology (Volume 46, Issue 5)

Publication milestones

  • Published - 06/04/2015

Publication status

Published - 06/04/2015

ISSN

0007-1013

External Publication IDs

  • handle.net: 10547/623028
  • Scopus: 84939571941