State of Linked Data in Learning AnalyticsAnd future…
Schedule8.30 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
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
Going further
SPARQL endpointSPARQL
proxy
Open Refine
Some other tool
Excel
RDF
SPARQLResults
CSV
Going further
SPARQL endpointSPARQL
proxy
Open Refine
Some other tool
Excel
RDF
SPARQLResults
CSV
BORIN
G!
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
From LAK
Linked data and semantic web in the CFP… but
LAK 2013 1 paper with a strong linked data component1 tutorial (this one)
LAK 2012 1 workshop (LALD 2012)
LAK 20111 paper on semantic social analysis
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Going further
data.open.ac.uk
data.ox.ac.uk mEducator
Gephi Tableau Weka …
Lodum.de …
Results / findings / insights / aggregates / …
Interpretation
Understanding
Challenges
Data:Overview of what existIntegration – can we jointly query all of
these things?Heterogeneity, dealing with multiple
sourcesCoverage, adoption
Usage:Linked data for interpretationLinked data for enrichmentLinked data for re-purposingLinked data for result publication
Technology:Data mining in linked dataLinked data quality specificationProvenance
Skills:Development with new technologiesDealing with large, distributed dataChange with respect to usual data
management approachesMoving away from traditional
cataloguing approaches
Collecting and cataloguing data
http://data.linkededucation.org/linkedup/catalog/
Architecture
Process
CKAN-based catalogue
http://datahub.io/group/linked-education
Data browsing interface
http://data.linkededucation.org/linkedup/catalog/
SPARQL endpoint
http://data.linkededucation.org/linkedup/catalog/sparql
Vocabularies in the datasets
Types in the datasets
Lightweight-Global integration
Simple manual mapping of the types (classes) in the datasets to a set of selected vocabularies
Supporting development
http://data.linkededucation.org/linkedup/devtalk/
Education/training events
LAK 2013 tutorial Using Linked Data in Learning Analytics
WWW 2013 tutorialOpen learning and linked data Rio de Janeiro, 14th May 2013
SSSW 2013 (http://sss.org/2013) Summer School on Ontology Engineering
and the Semantic WebCercedilla (near Madrid), Spain 7-13 July 2013Deadline to apply: 12th April 2013
And of course, the Challenge!
http://linkedup-challenge.org
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
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