Política de cookies

GNOSS usa cookies, propias y de terceros, con finalidad principalmente técnica y necesaria para la prestación de nuestros servicios.Más información sobre nuestra política de cookies. 

 

ACEPTA para confirmar que has leído la información y aceptado su instalación.Puedes modificar la configuración de tu navegador. 

mEducator: A Linked Dataset of Medical Educational Resources

Equipo GNOSS

01/09/2012

visibility 267

La red mEducator utiliza la tecnología semántica y los datos enlazados para ofrecer un servicio que permite acceder, evolucionar y reutilizar recursos educativos médicos en entornos de Educación Superior en Europa:

"The mEducator Best Practice Network (BPN) aims to implement and critically evaluate existing standards and reference models in the field of e-learning in order to enable specialized state-of-the-art medical educational content to be discovered, retrieved, shared and re-used across European higher academic institution".

mEducator ofrece su dataset en The Data Hub.

El recurso incluye la descripción de uso de la tecnología semántica en el proyecto :

 

"With sharing and reusing, educational resources become increasingly important for enhancing learning and teaching  experiences, particularly in medical educational domain since these resources are expensive to re-produce. In respect to this, many  efforts have been applied to federate the resources to achieve the sharing and reusing goals, which led to a fragmented landscape of  competing metadata schemas, such as IEEE LOM or OAI-DC, and interface mechanisms, such as OAI-PMH or SQI. However, the  major issue of educational resource federating is the heterogeneity challenge of metadata and data. In this paper, we illustrate a  medical educational dataset (mEducator Linked Educational Resources dataset) that is published as part of the Linked Open Data  cloud following Linked Data principles. The dataset contains educational resource metadata federated from ten different (medical)  educational institutes together with enriched links to related information by using Linked Data techniques and datasets. We introduce a Semantic Web Service based data extracting mechanism that is exploited for services and data integration to address  heterogeneous metadata problems. The paper also discusses the dataset accessing APIs, statistics and existing applications of using  the mEducator dataset".

mode_comment comentarios (0)

¿Quieres comentar? Regístrate o inicia sesión