Title: Teaching linked open data using open educational resources
Authors: Mikroyannidis, Alexander
Domingue, John
Maleshkova, Maria 
Norton, Barry
Simperl, Elena
Language: eng
Keywords: Big data;Data Science;Ebook;Linked open data;Massive open online course;Open educational resource
Issue Date: 19-Mar-2016
Publisher: Springer
Document Type: Book Part
Journal / Series / Working Paper (HSU): Lecture Notes in Computer Science
Volume: 9500
Page Start: 135
Page End: 152
Published in (Book): Open Data for Education
Publisher Place: Cham
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.
Organization Units (connected with the publication): Karlsruhe Institute of Technology
ISBN: 9783319304922
ISSN: 03029743
Publisher DOI: 10.1007/978-3-319-30493-9_7
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