Exposing Social Data as Linked Data in Education

Enayat Rajabi and Wolfgang Greller
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Enayat Rajabi: REDSpace Co., Bedford, Canada
Wolfgang Greller: University of Teacher Education, Vienna, Austria

International Journal on Semantic Web and Information Systems (IJSWIS), 2019, vol. 15, issue 2, 92-106

Abstract: According to recent studies, the social interactions of users such as sharing, rating, and reviewing can improve the value of digital learning objects and resources on the web. Linked data techniques, on the other hand, make different kinds of data available and reusable for other applications on the web. Exposing (meta)data, especially with a complex structure, as resource description framework (RDF) requires an ontology to bring all the data types under one umbrella. In this article, the authors propose an ontology in which social activities of users are exposed as linked data by reusing existing vocabularies. The proposed ontology has been implemented in a federated open educational resources (OER) portal, in which they published ratings, shares, comments, and other social activities assigned to around 1,000 OERs. This exposure allows other datasets, including harvested repositories, to explore the exposed social data related to e-learning objects according to the users' social engagement.

Date: 2019
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Persistent link: https://EconPapers.repec.org/RePEc:igg:jswis0:v:15:y:2019:i:2:p:92-106

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