PurposeResearch in the area of technology‐enhanced learning (TEL) throughout the last decade has largely focused on sharing and reusing educational resources and data. This effort has led to a fragmented landscape of competing metadata schemas, or interface mechanisms. More recently, semantic technologies were taken into account to improve interoperability. The linked data approach has emerged as the de facto standard for sharing data on the web. To this end, it is obvious that the application of linked data principles offers a large potential to solve interoperability issues in the field of TEL. This paper aims to address this issue.Design/methodology/approachIn this paper, approaches are surveyed that are aimed towards a vision of linked education, i.e. education which exploits educational web data. It particularly considers the exploitation of the wealth of already existing TEL data on the web by allowing its exposure as linked data and by taking into account automated enrichment and interlinking techniques to provide rich and well‐interlinked data for the educational domain.FindingsSo far web‐scale integration of educational resources is not facilitated, mainly due to the lack of take‐up of shared principles, datasets and schemas. However, linked data principles increasingly are recognized by the TEL community. The paper provides a structured assessment and classification of existing challenges and approaches, serving as potential guideline for researchers and practitioners in the field.Originality/valueBeing one of the first comprehensive surveys on the topic of linked data for education, the paper has the potential to become a widely recognized reference publication in the area.

In addition to user-generated content, Open Educational Resources are increasingly made available on the Web by several institutions and organizations with the aim of being re-used. Nevertheless, it is still difficult for users to find appropriate resources for specific learning scenarios among the vast amount offered on the Web. Our goal is to give users the opportunity to search for authentic resources from the Web and reuse them in a learning context. The LearnWeb-OER platform enhances collaborative searching and sharing of educational resources providing specific means and facilities for education. In the following, we provide a description of the functionalities that support users in collaboratively collecting, selecting, annotating and discussing search results and learning resources. Track: Open Track

is currently an MBA student at the Indian Institute of Management-Ahmedabad. She has worked with new and emerging technologies like semantic web and linked data. Her current area of research is inclusive of these areas which falls under the umbrella of web science. Along with this, exploring new strategic and financial prospects tied up with digital media and technology also adds up to her research interests. Stefan Dietze is a research group leader at the L3S Research Center (Germany). His research interests are in the areas of Linked Data, Web Science and Artificial Intelligence, and their use in actual application domains. Stefan currently is co-ordinator of several European R&D projects and he is co-chair of several working groups in the Semantic Web area. His work has been published in numerous major conferences and journals, he is member of many organization and program committees and editorial boards and a frequent invited speaker. Ivana Marenzi, PhD, is senior researcher at the L3S Research Center in Hannover. Throughout her career she has specialised in the relationship between technology and communication; her main area of research in Technology Enhanced Learning includes the support of collaborative and lifelong learning. AbstractIn this paper, we present the TED Talks dataset which exposes all metadata and the actual transcripts of available TED talks as structured Linked Data. The TED talks collection is composed of more than 1800 talks, along with 35 000 transcripts in over 30 languages, related to a wide range of topics. In this regard, TED talks metadata available in structured, multilingual and HTTP-accessible form constitute a valuable resource, for instance, for schoolteachers, to explore controversial contemporary topics with their students in order to stimulate awareness and critical thinking or as a means for language learning. Moreover, being compliant with state-of-the-art Linked Data principles, our dataset facilitates the computation of links with related data and resources. The TED dataset is used by a number of educational applications, and it is included in the LinkedUp Data Catalog. The TED talks dataset• Location: Dataset described at: http://datahub.io/dataset/ted-talks SPARQL endpoint: http://data.linkededucation.org/linkedup/ted/sparql Dump: http://data-observatory.org/ted_talks/tedtalksdump.nt.gz • Creator:

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