@incollection{zouaq_linked_2017,
	address = {Alberta, Canada},
	edition = {1},
	title = {Linked {Data} for {Learning} {Analytics}: {Potentials} and {Challenges}},
	isbn = {978-0-9952408-0-3},
	url = {http://solaresearch.org/hla-17/hla17-chapter1},
	abstract = {Learning analytics (LA) is witnessing an explosion of data generation due to the multiplicity and diversity of learning environments, the emergence of scalable learning models such as massive open online courses (MOOCs), and the integration of social media platforms in the learning process. This diversity poses multiple challenges related to the interoperability of learning platforms, the integration of heterogeneous data from multiple knowledge sources, and the content analysis of learning resources and learning traces. This chapter discusses the use of linked data (LD) as a potential framework for data integration and analysis. It provides a literature review of LD initiatives in LA and educational data mining (EDM) and discusses some of the potentials and challenges related to the exploitation of LD in these  elds.},
	booktitle = {The {Handbook} of {Learning} {Analytics}},
	publisher = {Society for Learning Analytics Research (SoLAR)},
	author = {Zouaq, Amal and Jovanović, Jelena and Gašević, Dragan and Joksimović, Srećko},
	editor = {Lang, Charles and Siemens, George and Wise, Alyssa Friend and Gaševic, Dragan},
	year = {2017},
	pages = {347--355}
}