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Towards integration of web data into a coherent educational data graph

Personalisation, adaptation and recommendation are central aims of Technology Enhanced Learning (TEL) environments. In this context, information retrieval and clustering techniques are more and more often applied to filter and deliver learning resources according to user preferences and requirements. However, the suitability and scope of possible recommendations is fundamentally dependent on the available data, such as metadata about learning resources as well as users. However, quantity and quality of both is still limited. On the other hand, throughout the last years, the Linked Data (LD) movement has succeeded to provide a vast body of well-interlinked and publicly accessible Web data. This in particular includes Linked Data of explicit or implicit educational nature. In this paper, we propose a large-scale educational dataset which has been generated by exploiting Linked Data methods together with clustering and interlinking techniques to extract import and interlink a wide range of educationally relevant data. We also introduce a set of reusable techniques which were developed to realise scalable integration and alignment of Web data in educational settings.