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Developing rich interactive eBooks to teach linked open data to professionals: principles and processes

This talk given at a seminar in St Petersburg describes work within the Euclid project which has focused on producing Open Educational Resources, in particular eBooks, to support the professionals learning about Linked Data

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Developing rich interactive eBooks to teach linked open data to professionals: principles and processes

  1. 1. Developing Rich Interactive eBooks to Teach Linked Open Data to Professionals: Principles and Processes John Domingue, Knowledge Media Institute, The Open University STI International St Petersburg, March 10, 2014 11/03/2014 1
  2. 2. Overview • Motivation • Design and delivery principles • Channels • Process • Results • Monitoring • Future Work • Summary 11.03.2014 2
  3. 3. Motivation (1/3) 11.03.2014 3 3
  4. 4. Motivation (2/3) 11.03.2014 4 http://www.mckinsey.com/mgi/publications/big_data/index.asp
  5. 5. Motivation (3/3) Percentage increase in staff over next 2 years Approach taken to increasing staff Big Data Analytics talent gap staff survey
  6. 6. PRINCIPLES 11.03.2014 6
  7. 7. 11.03.2014 7
  8. 8. ‘Right’ Topic? 11.03.2014 8
  9. 9. Design Principles Industrial relevance Team curriculum design External collaboration Explicit learning goals Use of realistic solutions Use of real data Use of real tools Show scalable solutions Eating our own dog food 11.03.2014 9
  10. 10. Delivery Principles Multiple Channels Open to format Addressability Integrated High quality Self-testing and reflection 11.03.2014 10
  11. 11. CHANNELS 11.03.2014 11
  12. 12. OU iTunes U Stats • Open University on iTunes U was launched on 3rd June 2008 • Now 58 iTunes U Courses • 65,138,000 downloads • Over 9,015,700 visitors downloaded files • Currently averaging 80,000-300,000 downloads a week • 449 collections containing 3,485 tracks (1,638 audio, 1,847 video) and 27 extras (PDF) • 423 OpenLearn study units as eBooks (ePub), representing over 5,000 hours of study • Currently delivering an average of 0.3-1 TB of data a week
  13. 13. ESWC Summer School 11.03.2014 14
  14. 14. PROCESS 11.03.2014 15
  15. 15. Expert Opinion Gathering 11.03.2014 16 Data science curriculum session
  16. 16. Process Model Collection of Raw Chapter Materials Learning Objectives Slides First Version Webinar – First Recording Slides – Final Version Webinar – Final Recording Initial Version of eBook Chapter Pre-final Version of eBook Chapter Final eBook Chapter and online course
  17. 17. RESULTS 11.03.2014 18
  18. 18. Modules 11.03.2014 19 • Introduction and application scenarios • Querying Linked Data • Provisioning Linked Data • Interaction with Linked Data • Building Linked Data applications • Scaling up
  19. 19. Module Formats 11.03.2014 20
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  24. 24. 11.03.2014 25
  25. 25. 11.03.2014 26
  26. 26. iTunes U Course 11.03.2014 27
  27. 27. MONITORING 11.03.2014 28
  28. 28. Dataflow
  29. 29. Data Harvesting • Twitter – keywords-based search & monitoring • LinkedIn groups – Linked Data Web, Semantic Web, ‘Ontologies, OWL-S, SPARQL interest group’, Semantic Technologies Group, Semantic Technologies, OWL/RDF • W3C mailing lists – SemanticWeb, LOD, Government Linked Data, Public-idp, Public-ldp-wg, LifeScience, RDF Stream processing, Semantic Open Data, Semantic Web Activity • SlideShare - not monitored yet (RSS feed is useless) #30Social Media Monitoring Platform v.2 Dec 2013
  30. 30. Monitoring Numbers • 185,000 tweets • 773 linkedIn posts • 898 messages from the W3 mail lists 11.03.2014 31
  31. 31. Monitoring Forums (1/2) 11.03.2014 32
  32. 32. Monitoring Forums (2/2) 11.03.2014 33
  33. 33. Monitoring Topics (1/2) 11.03.2014 34
  34. 34. Monitoring Topics (2/2) 11.03.2014 35
  35. 35. Monitoring People 11.03.2014 36
  36. 36. FUTURE WORK 11.03.2014 37
  37. 37. www.ict-forge.eu @ICT_FORGE FORGE is bringing the FIRE and eLearning worlds together FIRE (Future Internet Research and Experimentation) high-performance test-beds Forging Online Education through FIRE
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  39. 39. 11.03.2014 40
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  41. 41. Summary • Need to fill skilled data scientists gap • Successful development and deployment of open educational resources – Multi-skilled course team – Strong links to industrial requirements – Rich multimedia interactive eBooks – Explicit learning goals – Real data and tools – Multi channel delivery • Linked data based monitoring • Future work to deploy in new contexts – EU job skills dashboard 11.03.2014 42
  42. 42. The team Thanks to all contributors! Alexander Mikroyannidis, OU Alice Carpentier, STI-R Andreas Harth, KIT Andreas Wagner, KIT Andriy Nikolov, fluidOps Barry Norton, Ontotext Alex Simov, Ontotext Marin Dimitrov, Ontotext Daniel M. Herzig, KIT Elena Simperl, STI-R/Univ. of Southampton Günter Ladwig, KIT Inga Shamkhalov, KIT Jacek Kopecky, OU John Domingue, OU Juan Sequeda, Capsenta/University of Texa Kalina Bontcheva, University of Sheffield Lyndon Nixon, STI-R Maria Maleshkova, KIT Maria-Esther Vidal, Univers. Simon Bolivar Maribel Acosta, KIT Michael Meier, fluidOps Ning Li, OU Paul Mulholland, OU Peter Haase, fluidOps Richard Power, OU Steffen Stadtmüller, KIT 11.03.2014 43
  43. 43. 44 @euclid_project euclidproject euclidproject http://www.euclid-project.eu Other channels eBook Course

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