The document discusses opportunities and challenges of using linked data in education. It begins by outlining how linked data principles can be useful for sharing educational data by providing background knowledge and common standards and vocabularies. However, it notes that currently only a few datasets are actually reused or linked, in part due to heterogeneity in datasets, unreliable metadata, and a lack of links between datasets. The LinkedUp project aims to address these issues by collecting and profiling open educational datasets, generating links between them, and building applications and tools to help utilize the data. Key activities include developing a dataset catalog, generating topic profiles of datasets, running challenges to identify innovative applications, and engaging stakeholders.

1. Motivation
Data on the Web
Some eyecatching opener illustrating growth and or diversity of web data
Linked Data and Education – Opportunities,
Challenges & the case of LinkedUp
Stefan Dietze
(L3S Research Center, DE,
@stefandietze,
http://purl.org/dietze)
Stefan Dietze
18/11/13

2. Once upon a time (just a short while ago in fact)
?
„blurb…
„blurb…
Berlin ...main
Tiergarten …
station…
Bahnhof…“
„blurb…
Berlin
central…“
HTML pages
Stefan Dietze
„…waiting @
#berlinhbf“
Social Data
„…Lehrter
Bahnhof…“
PDFs
18/11/13

3. “A little semantics goes a long way” (J.
1)
Hendler
Semantic Web
dbp:populatedPlace
 Adding meaning through
shared vocabularies and
schemas (eg DBpedia)
typeOf
dbp:Berlin
typeOf
city
 W3C standards RDF &
SPARQL for data &
knowledge representation
and querying
 Persistent URIs to reference
& interlink data on the Web
dbp:Tiergarten
location
dbp:Berlin_Hauptbahnhof
redirectOf
dbp:Berlin_Central_Station
„blurb…
„blurb…
Berlin ...main
Tiergarten …
station…
Bahnhof…“
„blurb…
Berlin
central…“
HTML pages
1 Hendler,
redirectOf
dbp:Lehrter_Bahnhof
„…waiting @
#berlinhbf“
Social Data
J., The Dark Side of the Semantic Web, IEEE Intelligent Systems, Jan/Feb 2007
„…Lehrter
Bahnhof…“
PDFs

4. Semantic Web / Linked Data
 Use of URIs, RDF and SPARQL for exposing data
 De-facto standard for sharing data on the Web
rNews
 Vision: well connected graph of open Web data
 350+ datasets and 32 billion triples in LOD Cloud
alone
Media
Ontology
Geo
Ontology
 Other „incarnations“:
 Google
Knowledge Graph
 Facebook Open Graph
Dublin
Core
DBpedia
Ontology
 http://schema.org
FOAF
FMA
Ontology
BIBO
Gene
Ontology
Source: http://lod-cloud.net/state, September 2011

5. Linked Data for Education – How is it useful?
1. Linked Data as body of knowledge for education

vast amount of publicly available resources and data (300+ datasets, 32 billion statements LOD alone)

Dedicated OER and university data + „knowledge resources“ (from DBpedia to Slideshare)
2. Linked Data as set of principles and W3C standards for data sharing

RDF, SPARQL & shared vocabularies to improve interoperability of educational data

Supports Open Education Resources (OER) vision: reuse across isolated platforms
 „HTTP-accessibility“
(SPARQL, URI-dereferencing)
http://linkeduniversities.org
 „Structure“ & „Semantics“
(=> shared/linked vocabularies)
http://linkededucation.org
 „Interlinked“
 „Persistent“
 Interlinking educational Resources and the Web of Data – a
Survey of Challenges and Approaches
Stefan Dietze, Salvador Sanchez-Alonso, Hannes Ebner, Hong Qing
Yu, Daniela Giordano, Ivana Marenzi, Bernardo Pereira Nunes,
Emerald Program: electronic Library and Information Systems,
Volume 47, Issue 1 (2013).
 Linked Data for Open and Distance Learning
Mathieu d’Aquin, report for the Common Wealth18/11/13
of Learning,
Stefan Dietze

6. How LD principles can be useful for data sharing
LD as background knowledge
http://dbpedia.org/resources/Berlin
 „HTTP-accessibility“
(SPARQL, URI-dereferencing)
 „Structure“ & „Semantics“
(=> shared/linked vocabularies)
 „Interlinked“
 „Persistent“
 Trusted knowledge,
exposed via
established standards
 Shared semantics
(enrichment,
disambiguation)
Stefan Dietze
18/11/13

7. How LD principles can be useful for data sharing
LD as background knowledge
Combining a co-occurrence-based and a semantic measure
for entity linking, B. P. Nunes, S. Dietze, M.A. Casanova, R.
Kawase, B. Fetahu, and W. Nejdl., ESWC 2013 - 10th Extended
Semantic Web Conference, (May 2013).
Slideset
<sioc:Item 2139393292>
<title>Planetary motion
& gravity</title>
…
</sioc:Item 2139393292>
Semantics of terms?
Topics/categories addressed?
Relatedness of resources/entities?
(types, semantics)
Programme
Video
<po:Programme519215>
<po:Series>Wonders of the Solar
System</po:Series>
<po:Episode>Emp. of the Sun</po:Episode>
<po:Actor>Brian Cox</po:Actor>
</po:Programme519215 >
<yo:Video 8748720>
<dc:title>Pluto & the
Dwarf Planets</dc:title>
…
</yo:Video 8748720>
Stefan Dietze
18/11/13

8. How LD principles can be useful for data sharing
LD as background knowledge
Pluto?
Brian Cox?
Sun?
Programme
Video
<po:Programme519215>
<po:Series>Wonders of the Solar
System</po:Series>
<po:Episode>Emp. of the Sun</po:Episode>
<po:Actor>Brian Cox</po:Actor>
</po:Programme519215 >
<yo:Video 8748720>
<dc:title>Pluto & the
Dwarf Planets</dc:title>
…
</yo:Video 8748720>
Stefan Dietze
18/11/13

9. How LD principles can be useful for data sharing
LD as background knowledge
Slideset
db:Astronomy
<sioc:Item 2139393292>
<title>Planetary motion
& gravity</title>
…
</sioc:Item 2139393292>
db:Astronomical Objects
db:Pluto
(Dwarf Planet)
db:Sun
Programme
Video
<po:Programme519215>
<po:Series>Wonders of the Solar
System</po:Series>
<po:Episode>Emp. of the Sun</po:Episode>
<po:Actor>Brian Cox</po:Actor>
</po:Programme519215 >
<yo:Video 8748720>
<dc:title>Pluto & the
Dwarf Planets</dc:title>
…
</yo:Video 8748720>
Stefan Dietze
18/11/13

10. That’s awesome, but...
…why are there so few datasets actually used?
Hm,
really?
 LD reuse and links very much focused on trusted „reference
graphs“ such as DBpedia
 Long tail of LD datasets which are neither reused nor linked
to (LOD Cloud alone consists of 300+ datasets)
 „HTTP-accessibility“
(SPARQL, URI-dereferencing)
 Explanations?
 „Structure“ & „Semantics“
(=> shared/linked vocabularies)
 „Interlinked“
 „Persistent“
Stefan Dietze
18/11/13

11. LD is more heterogeneous than we think
SPARQL Web-Querying Infrastructure:
Ready for Action?, Carlos Buil-Aranda, Aidan Hogan, Jürgen
Umbrich Pierre-Yves Vandenbussch, International Semantic Web
Conference 2013, (ISWC2013).
“Availability” & “Standards” ?
 Less than 50% of all SPARQL endpoints actually responsive
at given point of time (“high reliability”)
 “THE” SPARQL protocol? No, but many subsets/variants
 Huge differences in response times
SPARQL endpoint availability over time [Buil-Aranda et al 2013]
Shared vocabularies & schemas, but:
 …still very heterogeneous [d’Aquin, WebSci13]
 …data partially messy an not conformant
(RDFS, schemas) [HoganJWS2012]
 …even widely used reference datasets such as
DBpedia noisy [Fürber2010]
Co-occurence graph of data
types in 146 datasets: 144
Vocabularies, 588 highly
overlapping types, 719
Properties
Assessing the Educational Linked Data Landscape, D’Aquin, M.,
Adamou, A., Dietze, S., ACM Web Science 2013 (WebSci2013), Paris,
France, May 2013.
Using semantic web resources for data quality management. Fürber,
C., Hepp, M..2010,. In Proceedings of the 17th international conference on
Knowledge engineering and management by the masses (EKAW'10),
Springer-Verlag, Berlin, Heidelberg, 211-225.
An empirical survey of Linked Data conformance. Hogan, A., Umbrich,
J., Harth, A., Cyganiak, R., Polleres, A., Decker., S., In the Journal of Web
Semantics 14: pp. 14–44, 2012

12. (Linked) Open Data for Educationnutshell Using/exploiting Linked Data in Education ?
(Open) Educational Resources
 Lack of reliable dataset metadata about
 Resource types
 Topics & disciplines
 Quality, currentness & availability
 Provenance
 Lack of links
Distance Universities and cross-dataset references
 Lack of federated query approaches
 ….
World
Wide
Web
Linked Open Data
MOOCs
 http://linkededucation.org &
Stefan Dietze
 http://linkeduniversities.org
18/11/13

13. “LinkedUp” – Linking Web Data for Education
L
European project aimed at
advancing take-up of open data
and related technologies
http://linkedup-project.eu
Success models:
data & applications
http://data.linkededucation.org
Data curation
 Collecting & exposing open
data of educational relevance
=> LinkedUp Data Catalog
 Profiling and linking of Web
Data for education
=> educational data graph
 LinkedUp Challenge
to identify innovative
tools & applications
 Evaluation methods
and approaches
http://www.linkedup-challenge.org/
Technology transfer
& community-building
 Disseminating knowledge &
building communities
(educators, computer
scientists, data engineers)
 Gathering stakeholder
feedback: use cases, and
requirements
http://linkedup-project.eu/events
Stefan Dietze
http://linkedup-challenge.org/#usecases
18/11/13
13

14. Who we areL
LinkedUp Advisory Board
LinkedUp Network
LinkedUp Consortium
17/09/2013
Stefan Dietze
18/11/13
14

15. “LinkedUp” – Linking Web Data for Education
L
European project aimed at
advancing take-up of open data
and related technologies
http://linkedup-project.eu
Success models:
data & applications
http://data.linkededucation.org
Data curation
 Collecting & exposing open
data of educational relevance
=> LinkedUp Data Catalog
 Profiling and linking of Web
Data for education
=> educational data graph
 LinkedUp Challenge
to identify innovative
tools & applications
 Evaluation methods
and approaches
http://www.linkedup-challenge.org/
Technology transfer
& community-building
 Disseminating knowledge &
building communities
(educators, computer
scientists, data engineers)
 Gathering stakeholder
feedback: use cases, and
requirements
http://linkedup-project.eu/events
Stefan Dietze
http://linkedup-challenge.org/#usecases
18/11/13

16. Data curation and dataset profiling
LinkedUp approach
 Goal: helping data consumers to discover and use suitable datasets
 Dataset selection: “LinkedUp/Linked Education cloud”
(http://datahub.io/groups/linked-education)
 RDF (VoID) catalog of datasets (LinkedUp Catalog): classification of datasets
according to, eg, represented types, disciplines/topics, data quality,
accessability
 Links and coreferences => unified view on data => Linked Education Graph
 Infrastructure, unified (SPARQL) endpoint & APIs for federated querying
Automated processing to generate:
 Descriptive VoID/RDF Dataset Catalog
 Data links
LinkedUp
Catalog
Educational Datasets
Stefan Dietze
18/11/13

17. LinkedUp Data Catalog
in VoIDnutshell browse, explore and query for
 a dataset catalog:
http://data.linkededucation.org/linkedup/catalog/
http://datahub.io/group/linked-education
datasets/types
 Federated queries using type mappings
Stefan Dietze
18/11/13

18. What‘s all the data about: dataset profiling
Issue:
 Considering LOD as knowledge graph, most
nodes are connected
Slideset
db:Astronomy
<sioc:Item 2139393292>
<title>Planetary motion
& gravity</title>
…
</sioc:Item 2139393292>
 Relevance of topics (DBpedia entities &
categories) for particular resources and
datasets?
 „Topic profile“ of a given dataset?
db:Astronomical Objects
db:Sun
Programme
db:Pluto
(Dwarf
Planet)
Video
<po:Programme519215>
<po:Series>Wonders of the Solar
System</po:Series>
<po:Episode>Emp. of the Sun</po:Episode>
<po:Actor>Brian Cox</po:Actor>
</po:Programme519215 >
<yo:Video 8748720>
<dc:title>Pluto & the
Dwarf Planets</dc:title>
…
</yo:Video 8748720>
Stefan Dietze
18/11/13

19. What‘s all the data about: dataset profiling
Generating structured Profiles of Linked Data
Graphs, Fetahu, B; Adamou, A., Dietze, S., d’Aquin,
M., Nunes, B.P., ISWC2013 – 12th International
Semantic Web Conference;
 Goal: extracting representative „topic profile“ for datasets
 How: computing of normalised (DBpedia) category relevance scores from sample resource sets
(scalability vs representativeness)
 Applied to entire LOD cloud
db:Astronomy
DBpedia category graph
db:Astronomical Objects
db:Sun
Programme
<po:Programme519215>
<po:Series>Wonders of the Solar
System</po:Series>
<po:Episode>Emp. of the Sun</po:Episode>
<po:Actor>Brian Cox</po:Actor>
</po:Programme519215 >
Stefan Dietze
18/11/13

20. Dataset profile explorer
http://data.linkededucation.org/linkedup/categories-explorer
http://data.linkededucation.org/request/pipeline/sparql
http://data.linkededucation.org/

21. “LinkedUp” – Linking Web Data for Education
L
European project aimed at
advancing take-up of open data
and related technologies
http://linkedup-project.eu
Success models:
data & applications
Data curation
 Collecting & exposing open
data of educational relevance
=> LinkedUp Data Catalog
 Profiling and linking of Web
Data for education
=> educational data graph
 LinkedUp Challenge
to identify innovative
tools & applications
 Evaluation methods
and approaches
http://www.linkedup-challenge.org/
 Series of 3 competitions („Veni“, „Vidi“,
„Vici“) running until end of 2014
 Disseminating knowledge &
 Open & focused tracks
building communities
 Total prize budget of almost 40.000 EUR
(educators, computer
Technology engineers)
scientists, data transfer
 LinkedUp support activities
& community-building
http://www.linkedup-challenge.org/
 Gathering stakeholder
feedback: use cases, and
requirements
Stefan Dietze
18/11/13

22. Veni Competition
 Tools and demos that analyse or integrate open web data
(deadline: 27 June, 1 Open Track, 10.000 EUR awards)
 22 submissions, shortlist of 8, from which:
 3 winners
 People's Choice Award
 Final ceremony on 17 September at OKCon, Geneva
17 September 2013, Geneva
Stefan Dietze
18/11/13

23. The Shortlist incl. 2nd/3rd/People’s Choice
DataConf.
http://www.globe-town.org/
ReCredible
KnowNodes
GlobeTown - 2nd price
http://seek.cloud.gsic.tel.uva.es/weshare/
18/11/13
YourHistory
WeShare - 3rd price / people‘s choice
Mismuseos

24. st
1
Place: PoliMedia
Exploring political debates & events
 Cross-media analysis of political events.
 Browsing parliament debates & related media
coverage
http://www.polimedia.nl/
 Automatically generated links between transcripts
debates, newspaper articles, including their
original lay-out on the page, and radio bulletins.
 Generated data available as Linked Data
(http://data.polimedia.nl)
 Data sources: 1) newspapers in their original layout
of the historical newspaper archive, and 2) radio
bulletins of the Dutch National Press Agency (ANP)
 9000+ debates (1945 – 1995)
 Over 3000 media links
Martijn Kleppe, Max Kemman, Henri Beunders (Erasmus Universiteit
Rotterdam), Laura Hollink Damir Juric (Vrije Universiteit Amsterdam), Johan
Oomen Jaap Dietze (Nederlands Instituut voor Beeld en Geluid)
Stefan Blom
09/04/13

25. Outlook
LinkedUp Veni Competition

Wanted: tools and demos that analyse or integrate open web data (for education)

Anyone can participate - researchers, students, developers, industry

“Open track” & “focused tracks”

20.000+ EUR worth of awards

Final awards ceremony at 11th Extended
Semantic Web Conference (ESWC2014)

http://linkedup-challenge.org/
Submission: 14 February 2014
Learning Analytics & Knowledge (LAK) Data Challenge

Analyse, apply, use, exploit the „LAK Dataset“

Finals at Learning Analytics & Knowledge Conference 2014, Indianapolis, US

http://lak.linkededucation.org/
Submission: 20th January
18/11/13
25

26. Thank you!
Contact
 http://purl.org/dietze | @stefandietze
See also (data)
 http://datahub.io/group/linked-education
 http://data.linkededucation.org
 http://data.linkededucation.org/linkedup/catalog/
 http://lak.linkededucation.org
See also (general)
 http://linkedup-project.eu
 http://linkedup-challenge.org
 http://linkededucation.org
 http://linkeduniversities.org
Stefan Dietze
18/11/13