The document outlines the agenda for a tutorial on using linked data in learning analytics. It discusses the current and potential uses of linked data in learning analytics, including as a data modeling approach, as a data source, and for ontological models and integration. It also summarizes results from the LAK Data Challenge, which involved using linked data for tasks like statistical analysis, network analysis, recommendation, and visualization. While linked data is not yet widely used in learning analytics, the document argues it will become more standard as the benefits become better understood and more education and resources are provided to the community.

1. State of Linked Data in Learning Analytics
And future…

2. Schedule
8.30 Intro to the tutorial
Linked data and its potential in learning analytics scenarios
Basics of manipulating linked data
10.30 Coffee break
11.00 Using Linked Data in Analytics Tools
Evaluation of the Linked Data applications
12.30 Lunch
13.30 Introduction to the LAK Data challenge
Presentations from the LAK Data Challenge particiants
15.30 Tea break
16.30 Current state of Linked Data in Learning Analytics
Results of the challenge
Wrap up
17.30 Finished

3. What is (sometimes) being done
Linked data as basic underlying data modelling
Linked data as data source
Semantic Web for ontological models and integration
Some use in recommendation
Some use in visualisation / social network analysis

4. Going further
Some
other tool
SPARQL endpoint
SPARQL SPARQL CSV
Results proxy
Open Refine Excel
RDF

5. Going further
Some
!
other tool
SPARQL endpoint
I
SPARQL SPARQL
N CSV G
Results
O R
proxy
B
Open Refine Excel
RDF

6. From the LAK Data Challenge
Statistical analysis, network analysis
Exploration, facet search and browsing
Recommendation
Visualisation / visual analytics
Search and retrieval
Rethorical / narrative analysis
Trend Analyis

7. From LAK
Linked data and semantic web in the CFP… but
LAK 2013
1 paper with a strong linked data component
1 tutorial (this one)
LAK 2012
1 workshop (LALD 2012)
LAK 2011
1 paper on semantic social analysis
7

8. Going further
data.ox.ac.uk mEducator
data.open.ac.uk
Lodum.de …
Gephi Tableau Weka …
Results / findings / insights / aggregates / …
Interpretation
Understanding

9. Challenges
Data: Technology:
Overview of what exist Data mining in linked data
Integration – can we jointly query all of Linked data quality specification
these things?
Heterogeneity, dealing with multiple
Provenance
sources
Coverage, adoption Skills:
Development with new technologies
Usage: Dealing with large, distributed data
Linked data for interpretation
Change with respect to usual data
Linked data for enrichment
management approaches
Linked data for re-purposing
Moving away from traditional
Linked data for result publication
cataloguing approaches

11. Collecting and cataloguing data
http://data.linkededucation.org/linkedup/catalog/

12. Architecture

13. Process

14. CKAN-based catalogue
http://datahub.io/group/linked-education

15. Data browsing interface
http://data.linkededucation.org/linkedup/catalog/

16. SPARQL endpoint
http://data.linkededucation.org/linkedup/catalog/sparql

17. Vocabularies in the datasets

18. Types in the datasets

19. Lightweight-Global integration
Simple manual mapping of the types
(classes) in the datasets to a set of
selected vocabularies

20. Supporting development
http://data.linkededucation.org/linkedup/devtalk/

21. Education/training events
LAK 2013 tutorial
Using Linked Data in Learning Analytics
WWW 2013 tutorial
Open learning and linked data
Rio de Janeiro, 14th May 2013
SSSW 2013 (http://sss.org/2013)
Summer School on Ontology
Engineering and the Semantic Web
Cercedilla (near Madrid), Spain
7-13 July 2013
Deadline to apply: 12th April 2013

22. And of course, the Challenge!
http://linkedup-challenge.org

23. Take home message
Linked Data is essential to Learning Analytics:
provides a flexible, reusable source of
information for all the steps of the analytics
process
Still some efforts to make for a complete
understanding by the Learning Analytics
community of the benefits of adopting (and
learning) linked data
But, through various channels, will soon become
standard practice
10. April 201323