This document outlines the goals and tangible outcomes of the LinkedUp project. The project aims to demonstrate success stories of open web data applications, establish an evaluation framework for such applications, and facilitate technology transfer in the education sector. It will run a multi-stage challenge and establish a large-scale data testbed. The challenge aims to produce highly innovative and evaluated applications using web-scale data to address educational scenarios. The project expects to increase collaboration, disseminate best practices, and raise awareness of open web data through technology transfer activities.

1. Stefan Dietze 06/11/12 1

2. Motivation
Data on the Web
Some eyecatching opener illustrating growth and or diversity of web data
LinkedUp: Linking Web Data for Education Project
– Open Challenge in Web-scale Data Integration
Stefan Dietze
(L3S Research Center, DE)
Stefan Dietze 06/11/12 2

3. Web-scale exploration of (educational)
resources and data ?
RecSys (Linked) Web Data
TEL

4. TEL data vs Linked Open Data
TEL data on the Web
 Open Educational Resource (OER) metadata & MOOC
collections
(e.g. OpenCourseware, OpenLearn, Merlot, Coursera)
 Competing Web interfaces (e.g. OAI-PMH, SOAP, REST)
 Competing metadata standards (e.g. IEEE LOM, ADL
SCORM, DC…) & taxonomies & exchange formats (JSON,
RDF, XML)
 Issues: heterogeneity & lack of interoperability
Stefan Dietze 06/11/12 4

5. TEL data vs Linked Open Data
TEL data on the Web Linked Open Data
 Open Educational Resource (OER) metadata & MOOC  Vision: well connected graph of open Web data
collections
(e.g. OpenCourseware, OpenLearn, Merlot, Coursera)  W3C standards (RDF, SPARQL) to expose data, URIs
to interlink datasets
 Competing Web interfaces (e.g. OAI-PMH, SOAP, REST)
 => vast cloud of interconnected datasets
 Competing metadata standards (e.g. IEEE LOM, ADL
SCORM, DC…) & taxonomies & exchange formats (JSON,  Crossing all sorts of domains
RDF, XML)
 32 billion triples (September 2011)
 Issues: heterogeneity & lack of interoperability
Stefan Dietze 06/11/12 5

6. TEL data vs Linked Open Data
Linked Data for Education Linked Open Data
Relevant knowledge and data  Vision: well connected graph of open Web data
 Publications: ACM, PubMed, DBLP (L3S), OpenLibrary  W3C standards (RDF, SPARQL) to expose data, URIs
 (Cross-)domain knowledge & resources: Bioportal for Life to interlink datasets
Sciences, historic artefacts in Europeana, Geonames,  => vast cloud of interconnected datasets
DBpedia, Freebase, …
 Crossing all sorts of domains
 Media resource metadata: BBC, Flickr, …
 32 billion triples (September 2011)
Explicit educational data
 University Linked Data: eg The Open University UK,
http://data.open.ac.uk, Southampton University, …
 OER Linked Data: mEducator Linked ER (
http://ckan.net/package/meducator), Open Learn LD
 Schemas: Learning Resource Metadata Initiative (LRMI,
http://www.lrmi.net/), mEducator OER schema (
http://purl.org/meducator/ns)
=> http://linkededucation.org; http://linkeduniversities.org
Stefan Dietze 06/11/12 6

7. Slow take-up => crucial
challenges:
Scalability, performance &
robustness
(in large-scale data
environments)
Licensing & legal issues
Web data quality and
consistency
Benchmarking & evaluation
…
RecSys (Linked) Web Data
TEL

8. LinkedUp in a nutshell
Challenge and evaluation framework aimed at:
LinkedUp
 Leap in robustness/scalability of (Big) data integration technologies
Web
data
submissi
on data
(data analytics, mining, storage, analysis)
 Real-world use case: Web-based education facilitated by open Web data
Personal
data
What? Stage 1-
Initialisation
Initialisation
When? 3 stages of the LinkedUp competition
LinkedUp Challenge Environment
How? • Lowest requirements level for participation
• LinkedUp Evaluation Framework
• Inital prototypes and mockups, use of data
…
n
o
i
t
a
p
i
c
i
t
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P
testbed required • Methods and Test Cases
Stage 2 • 10 to 20 projects are expected • LinkedUp Data Testbed
• Competitor ranking list
• Medium requirements level for participation …provides:
• Working prototypes, minimum amount of
LinkedUp Support Actions  Legal & technical
data sources, clear target user group
Stage 3 • 5 to 10 projects are expected • Dissemination (events, training) guidance
a
i
r
e
t
i
r
c • Data sharing initiatives  Data & use cases
• Deployment in real-world use cases • Community building & clustering
• Sustainable technologies, reaching out • Technology transfer  Evaluation
to critical amount of users,
Stage 4 • 3 to 5 projects are expected
• Cashprice awards & consulting results
! 2 years !  Financial awards
E
P S
P F  …
Network of supporting organisations T
I
(see 3.2 Spreading excellence, exploiting results, disseminating knowledge) S E
C B
C O
Stefan Dietze 06/11/12 8

9. LinkedUp consortium
(Scientific) expertise in three strategic areas
 Data integration, Web
technologies & evaluation
 Educational technologies,
(meta)data and resources
 Dissemination and exploitation
of open Web data
Stefan Dietze 25/05/12 9

10. LinkedUp consortium
(Scientific) expertise in three strategic areas
L3S Research Center, Leibniz University, DE
Elsevier, NL
 Leading institute in Web science &
 Leading scientific & educational publisher
data technologies as well as
 Innovative research on the future of publishing &
technology-enhanced learning
extensive experience in data competitions
 Strong experience in coordinating EC R&D
CELSTEC, The Open University, NL projects
 R&D institute in educational technologies and part of the
largest distance university in the netherlands
The Open Knowledge Foundation, UK
 Not-for profit organisation to promote open
knowledge and data; global network
 Host of key events (OKCon) and platforms (eg CKAN)
KMI, The Open University, UK
 Leading R&D institute in areas related to LinkedUp
 World’s largest distance university (over 200.000
students)
Exact Learning Solutions, IT
 SME in educational technologies and services with
long-standing experience in (EC-funded) R&D projects

11. LinkedUp network/associated partners
Persistent “LinkedUp Network”(community of industrial and academic institutions)
Commonwealth of Learning, COL (CA)
Athabasca University (CA)
International
Talis Group (UK) (outside Europe)
SURF NL (NL)
Université Fribourg, eXascale Infolab Group (CH)
Democritus University of Thrace (GR)
AKSW, Universität Leipzig (DE)
Aristotele University of Thessaloniki (GR)
CNR Institute for Educational Technologies (IT)
Clam Messina Service and Research Centre (IT)
Eurix (IT)
Ontology Engineering Group (OEG), UPM, (ESP)
11 18/09/12
Stefan Dietze

12. Advisory Board
Dan Brickley
 Google, UK & W3C
 Schema.org / Learning Resource
Metadata Initiative
 FOAF project
Sören Auer
Venkataraman Balaji
 Agile Knowledge Engi-
 Director, Technology &
neering and Semantic
Knowledge Management
Web (AKSW) group leader, University
 Commonwealth of Learning – of Leipzig
http://col.org  DBpedia, Coordinator of LOD2 project
Philippe Cudré-Mauroux
 Head of eXascale Infolab
 University of Fribourg,
Switzerland
Stefan Dietze 06/11/12 12

13. Previous collaborations
R&D projects & events/initiatives
R&D Projects
Events & Initiatives
EC IP OKKAM: Web entity LILE: Linked Learning (Linked Data for
identification & discovery Education) workshop series
EC BPN mEducator:
Integration of educational LALD: Learning Analytics and Linked
resources based on LOD Data workshop (series)
EC STREP LUISA: Semantic LinkedEducation
Web technologies for http://linkededucation.org
sharing of OER
EC NoE STELLAR: LinkedUniversities
educational Web http://linkeduniversities.org
technologies network
Joint special issues related to LinkedUp
OpenScout: promotion of (Semantic Web Journal and ILE)
use of open educational
content European Association for Technology-
enhanced Learning (EATEL)
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14. Other related initiatives from LinkedUp partners
Large-scale challenges & competitions Web data dissemination and events
 Open Data Challenge  The Open Knowledge Conference (OKCon):
(http://opendatachallenge.org/): Europe‘s annual open knowledge conference run by
largest open data competition, 430 OKFN
submissions from 24 member states  DataTEL theme team: gathering of open
 Elsevier Grand Challenge data within education (OUNL)
(http://www.elseviergrandchallenge.com):  Open Government Data Camp:
communication of scientific information. http://ogdcamp.org/
 Semantic Web Challenge  Open Data Handboook
(http://challenge.semanticweb.org/) large- http://opendatahandbook.org/: living online
scale Semantic Web data applications manual for basic concepts of ‘open data’
 Semantic Web Service Challenge  Topical working groups and hackdays, eg
(http://sws-challenge.org) : evaluation of http://okfn.org/wg/
semantic web service technologies
Data catalogues & (educational) datasets
 CKAN: The Data Hub, the most important registry of open
knowledge datasets (hosted and managed by OKFN).
 LUCERO, http://data.open.ac.uk: first extensive Linked Data
university dataset, approach adopted by many universities
 mEducator Linked Educational resources: one of first OER
datasets in Linked Data cloud (LUH, OUUK)
Stefan Dietze 06/11/12 14

15. ?

16. Goals
Objective 1
Open Web
Data Success
Stories
evaluate create
support
demonstrate create support
support demonstrate
Educational Web data &
technologies
Objective 2
support Objective 3
Evaluation evaluate create Technology
Framework for
demonstrate / support Transfer in the
Open Web
Education
Data
Sector
Applications evaluate
Stefan Dietze 06/11/12 16

17. Goals & tangible outcomes Web
data
LinkedUp
submissi
on data
Personal
data
Stage 1-
Initialisation
Initialisation
 Competition framework & community 3 stages of the LinkedUp competition
LinkedUp Challenge Environment
• Lowest requirements level for participation
• LinkedUp Evaluation Framework
 Evaluation framework for large-scale • Inital prototypes and mockups, use of data
n
o
p
c
i
t
r
a
P
testbed required • Methods and Test Cases
Stage 2 • LinkedUp Data Testbed
Web data applications and data • 10 to 20 projects are expected
• Competitor ranking list
Objective 1• Medium requirements level for participation
(metrics, methods, benchmarks)
Open Web • Working prototypes, minimumgroup of
data sources, clear target user
amount
LinkedUp Support Actions
Stage 3 • 5 to 10 projects are expected
 Large-scale data testbed of quality- Data Success • Dissemination (events, training)
a
e
t
i
r
c
• Data sharing initiatives
Stories • Deployment in real-world use cases
assessed datasets • Sustainable technologies, reaching out
• Community building & clustering
• Technology transfer
to critical amount of users,
Stage 4 • 3 to 5 projects are expected
• Cashprice awards & consulting
evaluate create P S
E
T P F
Network of supporting organisations I
support
(see 3.2 Spreading excellence, exploiting results, disseminating knowledge) S B
E
demonstrate create support C
O
C
support demonstrate
Periodic/continuous challenge
Educational Web data &
technologies
Objective 2
support Objective 3
Evaluation evaluate create Technology
Framework for
demonstrate / support Transfer in the
Open Web
Education
Data
Sector
Applications evaluate
Stefan Dietze 06/11/12 17

18. Goals & tangible outcomes
Challenge & evaluation framework (WP1, WP2)
LinkedUp in a nutshell
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19. Goals & tangible outcomes
Data curation & “testbed” (WP3): initial ideas
Educational data gathering - community-approach: Linked Education cloud
 “LinkedUp/Linked Education cloud” as subset of LOD cloud
 CKAN – “The DataHub” (ckan.net) for data collection (analogous to LOD approach)
 Dedicated group (“linked-education”) for cataloging educational datasets
Educational Data
Educational data integration & infrastructure: Linked Education graph
 Linked Education cloud => Linked Education graph
 Integration of (selected) datasets into coherent (RDF) dataset
 Infrastructure and unified (SPARQL) endpoint for LinkedUp challenge
Stefan Dietze 06/11/12 19

20. Goals & tangible outcomes
LinkedUp in a nutshell  Highly innovative, evaluated applications
of large-scale Web data
 “LinkedUp Challenge” offers incentive and
support to steer submissions
Objective 1
Open Web  Educational scenario: (a) challenging vision
Data Success and (b) real-world scenario and
Stories requirements
evaluate create
support
demonstrate create support
support demonstrate
Educational Web data &
technologies
Objective 2
support Objective 3
Evaluation evaluate create Technology
Framework for
demonstrate / support Transfer in the
Open Web
Education
Data
Sector
Applications evaluate
Stefan Dietze 06/11/12 20

21. Goals & tangible outcomes
Success stories: in both research & practice
Technical achievements & progress in, e.g. End-user applications facilitated by Open Data & resources
 Information Retrieval tasks (performance, scalability)  Tutoring systems (course/resource development) &
 Data integration (eg schema mapping, data interlinking, educational resource sharing and discovery solutions
entity co-reference resolution)  Certificate-level Web education offerings
Characteristics
 Specific & constrained challenge tasks & datasets Characteristics
 Evaluation with traditional quantitative measures  Open & less constrained challenge tasks (eg use cases) and
(precision, recall, response times, … ) data
 Impact primarily scientific (at least in short-term)  Evaluation via qualitative and quantitative criteria
 Impact on academia, industry, society
Stefan Dietze 06/11/12 21

22. Goals & tangible outcomes
in a nutshell
 Technology transfer, increase in
collaboration and awareness
(best practices, clusters/communities,
Objective 1 events)
Open Web  Transfer of innovative R&D results
Data Success
Stories  Increase in awareness about open Web
data and scalable data integration
evaluate create
methods
support
demonstrate create support
support demonstrate
Educational Web data &
technologies
Objective 2
support Objective 3
Evaluation evaluate create Technology
Framework for
demonstrate / support Transfer in the
Open Web
Education
Data
Sector
Applications evaluate
Stefan Dietze 06/11/12 22

23. Exploitation, dissemination, sustainability
Dissemination events & platforms Clustering
 Joint clustering activities with
Viral dissemination channels
 Showcases & tutorials collocated with
relevant conferences related organisations (“LinkedUp  Sharing of publications via Mendeley,
(WWW, ISWC, ESWC, ICDE, LAK etc) Network”) … Research Gate, CiteULike,
 System demonstrations  …and EC-funded R&D projects, Academia.edu
 Topical hackdays such as  Advertisement of slides, showcases
 LILE, LALD, DataTEL workshop series  LOD2 and demo videos on Slideshare,
 ARCOMEM Youtube, Videolectures.net, Vimeo
(established, persistent and growing
communities)  SEALS, etc.  Social network channels such as
 Open Knowledge Conference OKCON Twitter, LinkedIn
 LinkedEducation.org,  Source code sharing via Source Forge
LinkedUniversities.org  Use of open licensing schemes (CC)
Standardisation
 Participation/support of standardisation of
schemas and technologies through working
groups (eg W3C or http://okfn.org/wg/)
 Data catalogues (eg CKAN) and community data
portals (eg http://bibsoup.net/)
 Standardisation initiatives and working groups
(eg Creative Commons LRMI)
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24. Thank you!
http://purl.org/dietze / dietze@l3s.de
http://linkededucation.org
http://linkedup-project.eu
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