Online Learning and Linked Data - Lessons Learned and Best Practices
Tutorial at the 23rd International World Wide Web Conference WWW 2014
Co-organised by the EUCLID and LinkedUp projects
Scope of the tutorial
- New online learning methods will be taught for supporting the teaching of Linked Data. Additionally, the lessons learned and the best practices derived from designing and delivering a Linked Data curriculum by the EUCLID project will be discussed.
- Ways in which Linked Data principles and technologies can be used to support online learning and create innovative educational services will be explained, based on the experience developed in the development of existing Linked Data applications for online learning. We will in particular rely on the data catalogue, use cases and applications considered by the LinkedUp project.
Programme & slides
- Introduction (5 mins) - Alexander Mikroyannidis & Stefan Dietze
Part I: Supporting Online Education with Linked Data
- Using Linked Data for Learning & Education (30-40 mins) - Stefan Dietze
- Practical session: The LinkedUp catalog, dataset explorer, applications (20-30 mins) - Besnik Fetahu
- Q&A
- Coffee break
Part II: Development of a curriculum for Linked Data
- Development of a Linked Data curriculum (20 mins) - Alexander Mikroyannidis
- Delivering Linked Data training to data science practitioners (20 mins) - Marin Dimitrov
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Practical session: Evaluation of a EUCLID online course (30 mins) - Alexander Mikroyannidis
- Access the course at the EUCLID web site: www.euclid-project.eu/modules/course1 or in iTunes U (in an iPad): http://bit.ly/course1-itunesu
- Complete this questionnaire: http://bit.ly/euclid-www2014
- Q&A and wrap-up (20 mins)
Learning outcomes
- An awareness of the different approaches in producing and delivering online learning resources about Linked Data.
- A good overview of the range of technologies that can be employed to produce and deliver online learning resources about Linked Data.
- An insight into best practices for designing and delivering online learning resources about Linked Data.
- An insight into the current tools, datasets, approaches and initiatives aiming at exploiting the Web of Data for online learning, as well as the current research trends in this area (including learning analytics and educational data mining).
Organisers
Prof. John Domingue is the Deputy Director of the Knowledge Media Institute (KMi) at the Open University (OU). Since its inception in 1995 KMi has been at the forefront of enhancing OU teaching activities through the use of new media and semantic technologies and Prof. Domingue has played a leading role in this. Prof. Domingue has spent over a decade serving as a tutor and later as a director of leading summer schools in the semantic technologies area.
Dr. Alexander Mikroyannidis is a Research Associate at the Knowledge Media Institute of the Open University. His research areas of interest are related with knowledge management and applications of Semantic and Social Web technologies in Technology-Enhanced Learning (TEL). Recently, he has been working on the production of online courses and Open Educational Resources (OERs), delivered through various educational platforms, such as interactive eBooks.
Dr. Stefan Dietze is a research group leader at the L3S Research Center of the Leibniz University Hannover (Germany). Stefan is interested in Semantic Web and Linked Data technologies and their application to Web data integration problems in particular in Technology-Enhanced Learning (TEL). Stefan currently is coordinator of the EU-funded projects LinkedUp and DuraArK and he has been active in the organisation of a range of tutorials, workshops and conferences.
Guest speakers
Marin Dimitrov, Ontotext, UK
Marin Dimitrov is the CTO of Ontotext AD, with more than 12 years of experience in the company. His work experience includes research and development in areas related to enterprise integration systems, text mining, ontology management and Linked Data. Marin has a MSc degree in Artificial Intelligence from the University of Sofia (Bulgaria), and he is currently involved in projects related to Big Data, Cloud Computing and scalable many-core systems.
Besnik Fetahu, L3S Research Center, Germany
Besnik Fetahu is a PhD student at L3S Research Center, Leibniz University Hannover. He was part of the Graduate School of Computer Science at the Saarland University, and holds a M.Sc. in Computer Science from Sofia University. Main research interest lie on a combination of fields like Information Extraction and Retrieval, Semantic Web, and Natural Language Processing, with particular interest on bridging the gap between unstructured and structured content.
Previous editions
A previous edition of this tutorial was delivered in WWW 2013. More details and the presentations are available here.
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