A review of linked data proposals in the learning domain

This study critically reviews the recently published scientific literature on Linked Data proposals in the educational field. After systematically searching online bibliographic databases,33 original works satisfied the scope and quality criteria,and thus were included in this review. Studies were classified with respect to TEL research areas; interoperability,personalization and contextualized learning were the main areas addressed. Many studies have a foundation on learning object and repository research,where Linked Data practices are applied to simplify the integration of educational datasets. As learning institutions are gradually exposing their key datasets as Linked Data,an emergent educational data web is being constituted. A number of the reviewed works consume these data for different purposes,reporting reusability and enrichment benefits. Nevertheless,upcoming proposals should be aware of existing challenges,derived from the Linked Data model,such as the lack of control of data sources or varying degrees of data quality. We also give some recommendations for delivering Linked Databased proposals in education,including a classification of vocabularies,datasets and technological products. Future research directions include the release of new datasets as Linked Data,federation and interlinking practices to improve the cohesion of the emergent educational Web of Data,generation of learning artifacts,curation and enrichment of educational data,novel educational applications consuming Linked Data,and performance improvements.