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Teaching Linked Open Data Using Open Educational Resources

Mikroyannidis, Alexander; Domingue, John; Maleshkova, Maria; Norton, Barry and Simperl, Elena (2016). Teaching Linked Open Data Using Open Educational Resources. Open Data for Education: Linked, shared, and reusable data for teaching and learning, 9500 pp. 135–152.

DOI (Digital Object Identifier) Link: https://doi.org/10.1007/978-3-319-30493-9_7
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Abstract

Recent trends in online education have seen the emergence of Open Educational Resources (OERs) and Massive Open Online Courses (MOOCs) as an answer to the needs of learners and educators for open and reusable educational material, freely available on the web. At the same time, Big Data and the new analytics and business intelligence opportunities that they offer are creating a growing demand for data scientists possessing skills and detailed knowledge in this area. This chapter presents a methodology for the design and implementation of an educational curriculum about Linked Open Data, supported by multimodal OERs. These OERs have been implemented as a combination of living learning materials and activities (eBook, online courses, webinars, face-to-face training), produced via a rigorous process and validated by the data science community through continuous feedback.

Item Type: Journal Article
Copyright Holders: 2016 Springer International Publishing Switzerland
ISBN: 3-319-30493-3, 978-3-319-30493-9
ISSN: 1611-3349
Project Funding Details:
Funded Project NameProject IDFunding Body
EUCLID296229European Community’s Seventh Framework Programme
Extra Information: Series title: Lecture Notes in Computer Science, ISBN 978-3-319-30493-9
Academic Unit/Department: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi)
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 46808
Depositing User: Kay Dave
Date Deposited: 14 Jul 2016 16:07
Last Modified: 19 Oct 2016 15:45
URI: http://oro.open.ac.uk/id/eprint/46808
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