Online Learning and
Linked Data
An Introduction
John Domingue with Mathieu d‘Aquin,
Stefan Dietze and Alexander Mikroyannidis
Tutorial at WWW 2013
Overall Agenda
• Introduction
– John Domingue
• Best Practices for Linked Data Education
– Alexander Mikroyannidis
• Using Linked Data in Education – Opportunities,
Challenges, Examples
– Stefan Dietze
• Interactive Session
2
Agenda
• Linked Data
• Massive Open Online Courses (MOOCs)
• iBooks and SocialLearn
• Summary
3
LINKED DATA
4
“unHogging Data”
5
TheWeb: Evolution
6
Web of Documents Web of Data
"Documents"
Hyperlinks Typed Links
"Things"
Linked Data Principles
1. Use URIs as names for things.
2. Use HTTP URIs so that people can look up
those names.
3. When someone looks up a URI, provide useful
RDF information.
4. Include RDF statements that link to other URIs
so that they can discover related things.
Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2006
Slide curtesy of Chris Bizer
Set of best practices for publishing structured
data on the Web in accordance with the general
architecture of the Web.
Semantics on theWeb
8
Semantic Web Stack
Berners-Lee (2006)
Semantics on theWeb
9
Semantic Web Stack
Berners-Lee (2006)
RDF – Resource Description Framework
Semantics on theWeb
10
RDF – Resource Description Framework
• RDF is the basis layer of the Semantic Web stack
‘layer cake’.
• Basic building block: RDF triple.
• Subject – a resource, which may be identified with a URI.
• Predicate – a URI-identified reused specification of the
relationship.
• Object – a resource or literal to which the subject is related.
Semantics on theWeb
11
RDF Graphs
• Every set of RDF assertions can then be drawn and
manipulated as a (labelled directed) graph:
• Resources – the subjects and objects are nodes of the
graph.
• Predicates – each predicate use becomes a label for an arc,
connecting the subject to the object.
Subject Object
Predicate
Describing Data
12
Vocabularies
• Collections of defined relationships and classes of
resources.
• Classes group together similar resources.
• Terms from well-known vocabularies should be
reused wherever possible.
• New terms should be define only if you can not find
required terms in existing vocabularies.
Describing Data
13
Vocabularies
A set of well-known vocabularies has evolved in the
Semantic Web community. Some of them are:
Vocabulary Description Classes and Relationships
Friend-of-a-Friend (FOAF) Vocabulary for describing
people.
foaf:Person, foaf:Agent, foaf:name,
foaf:knows, foaf:member
Dublin Core (DC) Defines general metadata
attributes.
dc:FileFormat, dc:MediaType,
dc:creator, dc:description
Semantically-Interlinked
Online Communities (SIOC)
Vocabulary for representing
online communities.
sioc:Community, sioc:Forum,
sioc:Post, sioc:follows, sioc:topic
Music Ontology (MO) Provides terms for describing
artists, albums and tracks.
mo:MusicArtist, mo:MusicGroup,
mo:Signal, mo:member, mo:record
Simple Knowledge
Organization System (SKOS)
Vocabulary for representing
taxonomies and loosely
structured knowledge.
skos:Concept, skos:inScheme,
skos:definition, skos:example
Linked Data Cloud
14
MASSIVE OPEN ONLINE COURSES
(MOOCS) AND OPEN EDUCATIONAL
RESOURCES (OERS)
15
MOOC
• Large scale participation
• Open access
– Resources and tuition are freely available
16
Coursera Course Clip
17
Coursera
18
• Started in Stanford in April 2012
• Now has 69 partner universities
• 3.2 Million Users
• Courses in: engineering, humanities,
medicine, biology, social sciences,
mathematics, business, computer science
• Assignments are peer-graded
edX
19
• Founded by MIT and Harvard in April 2012
• Developing an open source learning platform
• Offers 15 courses from MIT, Harvard and Berkely
• Additional universities to be added in 2014
Udacity
20
• Started in 2011 as an offshoot of Stanford
Courses
– 160,000 enrolled in Introduction to Artificial
Intelligence course
• Announced in 2012
• Now has 24 Courses
• Partnership with San Jose State University
announced in January 2013
• Certificate at end for free
• Exam from Pearson VUE for $89
FutureLearn
• Started in January 2013 by The Open
University
• Developing a MOOC platform
• Currently has British Library, British Council,
British Museum and 17 UK Universities as
partners
21
22
23
IBOOKS AND SOCIALLEARN
24
OU iTunes U Stats
• Open University on iTunes U was launched on
3rd June 2008
• Now 79 iTunes U Courses
• 61,974,200 downloads
• Over 8,402,400 visitors downloaded files
• Currently averaging 303,000 downloads a week
• 434 collections containing 3,422 tracks (1,630
audio, 1,792 video)
• 423 OpenLearn study units as eBooks (ePub),
representing over 5,000 hours of study
• Currently delivering an average of 6 TB of data
a week
SocialLearn
Learning Paths
Summary
• Linked Data
– Web of Data
– 5 principles
– Subject, Relation, Object
• Massive Open Online Courses (MOOCs)
– Possible re-configuration of higher education
• iBooks and SocialLearn
– Use of new media and Web 2.0 to support learning
29
THANKS
30

Online Learning and Linked Data: An Introduction

  • 1.
    Online Learning and LinkedData An Introduction John Domingue with Mathieu d‘Aquin, Stefan Dietze and Alexander Mikroyannidis Tutorial at WWW 2013
  • 2.
    Overall Agenda • Introduction –John Domingue • Best Practices for Linked Data Education – Alexander Mikroyannidis • Using Linked Data in Education – Opportunities, Challenges, Examples – Stefan Dietze • Interactive Session 2
  • 3.
    Agenda • Linked Data •Massive Open Online Courses (MOOCs) • iBooks and SocialLearn • Summary 3
  • 4.
  • 5.
  • 6.
    TheWeb: Evolution 6 Web ofDocuments Web of Data "Documents" Hyperlinks Typed Links "Things"
  • 7.
    Linked Data Principles 1.Use URIs as names for things. 2. Use HTTP URIs so that people can look up those names. 3. When someone looks up a URI, provide useful RDF information. 4. Include RDF statements that link to other URIs so that they can discover related things. Tim Berners-Lee, http://www.w3.org/DesignIssues/LinkedData.html, 2006 Slide curtesy of Chris Bizer Set of best practices for publishing structured data on the Web in accordance with the general architecture of the Web.
  • 8.
    Semantics on theWeb 8 SemanticWeb Stack Berners-Lee (2006)
  • 9.
    Semantics on theWeb 9 SemanticWeb Stack Berners-Lee (2006) RDF – Resource Description Framework
  • 10.
    Semantics on theWeb 10 RDF– Resource Description Framework • RDF is the basis layer of the Semantic Web stack ‘layer cake’. • Basic building block: RDF triple. • Subject – a resource, which may be identified with a URI. • Predicate – a URI-identified reused specification of the relationship. • Object – a resource or literal to which the subject is related.
  • 11.
    Semantics on theWeb 11 RDFGraphs • Every set of RDF assertions can then be drawn and manipulated as a (labelled directed) graph: • Resources – the subjects and objects are nodes of the graph. • Predicates – each predicate use becomes a label for an arc, connecting the subject to the object. Subject Object Predicate
  • 12.
    Describing Data 12 Vocabularies • Collectionsof defined relationships and classes of resources. • Classes group together similar resources. • Terms from well-known vocabularies should be reused wherever possible. • New terms should be define only if you can not find required terms in existing vocabularies.
  • 13.
    Describing Data 13 Vocabularies A setof well-known vocabularies has evolved in the Semantic Web community. Some of them are: Vocabulary Description Classes and Relationships Friend-of-a-Friend (FOAF) Vocabulary for describing people. foaf:Person, foaf:Agent, foaf:name, foaf:knows, foaf:member Dublin Core (DC) Defines general metadata attributes. dc:FileFormat, dc:MediaType, dc:creator, dc:description Semantically-Interlinked Online Communities (SIOC) Vocabulary for representing online communities. sioc:Community, sioc:Forum, sioc:Post, sioc:follows, sioc:topic Music Ontology (MO) Provides terms for describing artists, albums and tracks. mo:MusicArtist, mo:MusicGroup, mo:Signal, mo:member, mo:record Simple Knowledge Organization System (SKOS) Vocabulary for representing taxonomies and loosely structured knowledge. skos:Concept, skos:inScheme, skos:definition, skos:example
  • 14.
  • 15.
    MASSIVE OPEN ONLINECOURSES (MOOCS) AND OPEN EDUCATIONAL RESOURCES (OERS) 15
  • 16.
    MOOC • Large scaleparticipation • Open access – Resources and tuition are freely available 16
  • 17.
  • 18.
    Coursera 18 • Started inStanford in April 2012 • Now has 69 partner universities • 3.2 Million Users • Courses in: engineering, humanities, medicine, biology, social sciences, mathematics, business, computer science • Assignments are peer-graded
  • 19.
    edX 19 • Founded byMIT and Harvard in April 2012 • Developing an open source learning platform • Offers 15 courses from MIT, Harvard and Berkely • Additional universities to be added in 2014
  • 20.
    Udacity 20 • Started in2011 as an offshoot of Stanford Courses – 160,000 enrolled in Introduction to Artificial Intelligence course • Announced in 2012 • Now has 24 Courses • Partnership with San Jose State University announced in January 2013 • Certificate at end for free • Exam from Pearson VUE for $89
  • 21.
    FutureLearn • Started inJanuary 2013 by The Open University • Developing a MOOC platform • Currently has British Library, British Council, British Museum and 17 UK Universities as partners 21
  • 22.
  • 23.
  • 24.
  • 26.
    OU iTunes UStats • Open University on iTunes U was launched on 3rd June 2008 • Now 79 iTunes U Courses • 61,974,200 downloads • Over 8,402,400 visitors downloaded files • Currently averaging 303,000 downloads a week • 434 collections containing 3,422 tracks (1,630 audio, 1,792 video) • 423 OpenLearn study units as eBooks (ePub), representing over 5,000 hours of study • Currently delivering an average of 6 TB of data a week
  • 27.
  • 28.
  • 29.
    Summary • Linked Data –Web of Data – 5 principles – Subject, Relation, Object • Massive Open Online Courses (MOOCs) – Possible re-configuration of higher education • iBooks and SocialLearn – Use of new media and Web 2.0 to support learning 29
  • 30.