News Story

WWW Gangnam style!

John Domingue, Thursday 10 Apr 2014

KMi-ers Harith Alani, Carlos Pedrinaci and Alexander Mikroyannidis are in Seoul for the 23rd World Wide Web conference. This year, the WWW conference is hosted in the prestigious COEX hub in Korea’s Gangnam district. So far, it has featured a panel of renowned internet experts, including Tim Berners-Lee, discussing the challenges and opportunities of the previous 25 years and the next 25 years of the internet.

On Monday, Alexander Mikroyannidis chaired the tutorial: "Online Learning and Linked Data – Lessons Learned and Best Practices", which he co-organised with Stefan Dietze from the L3S Research Center in Germany, and John Domingue. Following the latest developments in online learning and Linked Data, the scope of this tutorial was two-fold. First, ways in which Linked Data principles and technologies can be used to support online learning and create innovative educational services were explained, based on the development of existing Linked Data applications for online learning, and particularly on the data catalogue, use cases and applications considered by the LinkedUp project. Secondly, new online learning methods were 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 were discussed.

The session was well attended and featured invited talks from Marin Dimitrov (Ontotext, UK) and Besnik Fetahu (L3S Research Center, Germany). All the presentations are available in the tutorial’s web page.

The conference continues today and tomorrow. Stay tuned for more updates from the KMi delegation!

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The KMi delegation in Seoul
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Alexander Mikroyannidis talks about the EUCLID project
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Stefan Dietze introduces the LinkedUp project
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Marin Dimitrov presents the Ontotext training experiences
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Besnik Fetahu introduces the LinkedUp Data Catalog
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Discussions with the tutorial audience


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EdUcational Curriculum for the usage of LInked Data

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