Abstract
Throughout the last few years, the scale and diversity of datasets published according to Linked Data (LD) principles has increased and also led to the emergence of a wide range of data of educational relevance. However, sufficient insights into the state, coverage and scope of available educational Linked Data seem still missing. In this work, we analyse the scope and coverage of educational linked data on the Web, identifying the most significant resource types and topics and apparent gaps. As part of our findings, results indicate a prevalent bias towards data in areas such as the life sciences as well as computing-related topics. In addition, we investigate the strong correlation of resource types and topics, where specific types have a tendency to be associated with particular types of categories, i.e. topics. Given this correlation, we argue that a dataset is best understood when considering its topics, in the context of its specific resource types. Based on this finding, we also present a Web data exploration tool, which builds on these findings and allows users to navigate through educational linked datasets by considering specific type and topic combinations.
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These include, for instance, http://linkededucation.org, http://linkeduniversities.org or the recently established W3C Community Group on Open Linked Education (http://www.w3.org/community/opened/).
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source: http://lod-cloud.net/.
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Acknowledgments
This work has been partially supported by the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement No 317620– LinkedUp project (http://linkedup-project.eu/). The authors would like to acknowledge networking support by the COST Action IC1302 (KEYSTONE).
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Taibi, D., Fulantelli, G., Dietze, S., Fetahu, B. (2016). Educational Linked Data on the Web - Exploring and Analysing the Scope and Coverage. In: Mouromtsev, D., d’Aquin, M. (eds) Open Data for Education. Lecture Notes in Computer Science(), vol 9500. Springer, Cham. https://doi.org/10.1007/978-3-319-30493-9_2
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