Interlinking educational data to Web of Data (Thesis presentation)

International doctorate thesis

I li ki Ed i l d Interlinking Educational data to Web of Data

Presented by: Enayat RajabiSupervisors: Salvador Sanchez-Alonso

Miguel-Ángel Sicilia

May 2015

Agendag

1 Research context1. Research context2. Motivation3 State of the art3. State of the art4. General objective & approach5. Specific objectives6. Studies & experimentationsp7. Conclusion & future work

2 out of 54

Research contextResearch context Linked Data An approach for e posing structured data An approach for exposing structured data

(triples) on the Web Currently, the LOD cloud includes ~10,000 y, ,

datasets (88 Billion triples) in different domains Datasets include metadata about objects

I li ki l h l bli h li k Interlinking tools help publishers to link datasets

12 datasets!May 2007

1. Research context3 out of 54

Research contextResearch context eLearning eLearning repositories (including educational data) eLearning repositories (including educational data) eLearning metadata schema (Dublin Core, IEEE

LOM,…) Analysis on largest educational repository with

around one million metadata (GLOBE)

1. Research context4 out of 54

MotivationMotivation

An increasing number of educational resourcesare published on the Webare published on the Web.

Some of these resources are implicitly orsemantically related to each other.semantically related to each other.

The Linked Data approach allows resources to bereusable, and accessible for learners.

There exist a number of tools for exposing dataand semi-automatic linking between datasets.

2. Motivation5 out of 54

State of the art (background)State of the art (background)

• Is there any mapping • Is the (meta)data

Practical steps for exposing data as Linked Data

y pp gtool to convert data?

( )structure flat or hierarchical?

Selecting a proper

Converting d t i t proper

schema orontology

data into a structured

format

Mapping data

according to the

Importing the RDF

dump to a triple store

• Creating a dump file• Selecting a proper

triple store• Setting up a SPARQL

ontologytriple store

Setting up a SPARQL endpoint

3. State of the art6 out of 54

Linked Data exposure infrastructurep


State of the artState of the art

Interlinking educational data Studying the importance of interlinking on an

educational context (Stefan Dietz, 2012)

Exposing IEEE LOM as RDF RDF binding of some IEEE LOM elements

(Nil & P l é 2002)(Nilson & Palmér, 2002)

Interlinking tools Theoretical comparison of interlinking tools

(Wolger et al., 2011)


General objectiveGeneral objective

Investigating an interlinking approachInvestigating an interlinking approacheducational contexton an

4. General objective and approach9 out of 54

General approachGeneral approach

4. General objective and approach10 out of 54

Specific objectivesSpecific objectives

1 Analyzing an eLearning metadata schema 1. Analyzing an eLearning metadata schema for exposing it as Linked Open Data

2. Examining the datasets in the Linked 2. Examining the datasets in the Linked Open Data cloud

3. Investigating existing interlinking tools in g g g gan educational context

4. Assessing the interlinking results and g gtheir advantages

5. Specific objectives11 out of 54

Objective 1:Analyzing a metadata schema for

exposing it as Linked Open Data

6. Studies and experimentations12 out of 54

Exposing a flat schemaExposing a flat schema

DCT titlDCTerms:title

DCTerms:date

DCTerms:publisher

Mapping an RDB to Dublin Core


Exposing a complex schema (IEEE LOM)Exposing a complex schema (IEEE LOM)


IEEE LOM ontologyIEEE LOM ontologyIEEE LOM schema has a hierarchical structure and it supports different kinds of data types, so pp yp ,we had to:

Map the data types Specif a correct element for identifier (URI) Specify a correct element for identifier (URI) Choose a strategy for exposing aggregated elements (e.g., keyword) Reuse existing vocabularies Test the ontology in an implementationimplementation


A case study based on the ontologyy gy


Remarks of this investigationRemarks of this investigation

Analyzing the IEEE LOM schema for the sake of: exposing its elements as Linked Open Data creating an complete ontology identifying the appropriate elements for interlinking identifying the appropriate elements for interlinking

The exposing approach was applied for other schemas as well.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “I li ki Ed i l R W b f D h h “Interlinking Educational Resources to Web of Data through IEEE LOM”. Computer Science and Information Systems,vol. 12, No. 1, pp. 233–255, 2015.


Objective 2:Examining the datasets in the

Linked Open Data cloud

The LOD datasets analysisThe LOD datasets analysis

We analyzed the Linked Open Data cloud to realize:

1. what datasets are more important in the cloud to be linked in an educational domain?to be linked in an educational domain?

Examining the LOD cloud using Social Network Analysis (SNA)

2. what educational datasets are appropriate for interlinking?

Selecting a set of educational datasets in Selecting a set of educational datasets in datahub using some metrics



We considered the LOD cloud as a directed graph and analyzed them according the following SNA metrics:analyzed them according the following SNA metrics: Betweenness Centrality (BC): If a dataset has a high BC value, then

many datasets are connected through it to others. In-Degree: the number of datasets point to the current dataset

D I D O D B C li

g p Out-Degree: the number of datasets that to the current dataset

point to

Dataset In-Degree Out-Degree Betweenness Centrality

DBpedia 181 30 82,664

Geonames 55 0 10,958

DrugBank 8 12 7,446

Bio2rdf-goa 11 8 3,751

Ordance-survey 16 0 3 272Ordance survey 16 0 3,272



High BCHigh BC


Selecting educational datasetsSelecting educational datasets

Exploring the LOD cloud to find educational d t t i th f ll i tdataset using the following steps:

Finding the datasets in datahub tagged as educational subjectseducational subjects

Checking their SPARQL endpoints or RDF dumps’ availability

Retrieving their specification (size, metadata schema, language…) from an interlinking point of view using SPARQLpoint of view using SPARQL


Datahub endpointDatahub endpoint

Exploring datahub endpoint to find educational datasets


Educational datasets bubble graphEducational datasets bubble graphSelecting 20 available educational datasets


Getting datasets specification using SPARQLGetting datasets specification using SPARQLDatasets Size (triple) SPARQL EndpointCharles University in Prague 93,233,661 http://linked.opendata.cz/sparqlUNISTAT-KIS 8,026,637 http://data.linkedu.eu/kis/query

h d d k ( ) 7 h // l d / lAchievement Standards Network (ASN) 7,494,201 http://sparql.jesandco.org:8890/sparqlData.gov.uk 6,619,847 http://services.data.gov.uk/education/sparqlUniversity of Southampton 5,726,668 http://sparql.data.southampton.ac.uk/Yovisto - academic video search 4,932,352 http://sparql.yovisto.com/University of Muenster(LODUM) 4,179,372 http://data.uni-muenster.de/sparql/O U i it i UK 3 588 626 htt //d t k/ lOpen University in UK 3,588,626 http://data.open.ac.uk/sparqlUniversity of Huddersfield 3,553,343 http://data.linkedu.eu/hud/querySemantic ISVU (Kent) 2,421,268 http://kent.zpr.fer.hr:8080/educationalProgram

/sparqlUniversity of Bristol 1,885,124 http://resrev.ilrt.bris.ac.uk/data-server-

workshop/sparqlAalto University 1 589 122 http://data aalto fi/sparqlAalto University 1,589,122 http://data.aalto.fi/sparqlOpen Courseware Consortium metadata 636,453 http://data.linkedu.eu/ocw/queryOxPoints (University of Oxford) 318,392 https://data.ox.ac.uk/sparql/TheSoz Thesaurus for the Social Sciences (GESIS) 305,329 http://lod.gesis.org/thesoz/sparqlPROD 62,375 http://data.linkedu.eu/prod/query

h // d d i 2 i /LMF/ l/Open Data @ Tor Vergata 54,968 http://opendata.ccd.uniroma2.it/LMF/sparql/select

Vytautas Magnus University, Kaunas 39,279 http://kaunas.rkbexplorer.com/sparql/MoreLab 3,906 http://www.morelab.deusto.es/joseki/articlesForge project 132 http://data.linkedu.eu/forge/query


Getting entities from the datasetsGetting entities from the datasets

Open University of UK endpoint


Remarks of this investigation

Selecting the DBpedia dataset as the LOD hub for i t li ki d ti l d t t


interlinking educational datasets Identifying a set of well-formed educational

datasets for interlinkingdatasets for interlinking

E. Rajabi, S. Sanchez-Alonso, and M.-A. Sicilia, “Analyzing Broken Links on the Web of Data: an Experiment with DBpedia,” Journal of the Association for Information Science and Technology (JASIST), vol. 65, no. 8, pp. 1721–1727, 2014.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Discovering Duplicate and Related Resources using Interlinking Approach: The case of Educational Datasets,” Journal of Information Science, first published on March 10 2015published on March 10, 2015


Objective 3:Investigating existing interlinking

tools in an educational context

6. Studies and experimentations

Interlinking tools (comparison)Interlinking tools (comparison)

Tool DomainSPARQL/ RDF

DumpManual/

AutomaticWell-

documentedCustomization

flexibility

GWAP Multimedia No Manual No Unknown

LIMES LOD Y A i Y YLIMES LOD Yes Automatic Yes Yes

LOD Refine General Yes Automatic Yes Partially

RDF-IA LOD RDF Dump Automatic No Unknown

SAI Multimedia No Automatic No Unknown

Silk LOD Yes Automatic Yes Yes

UCI LOD Y M l N U kUCI LOD Yes Manual No Unknown


Interlinking tools (general idea)Interlinking tools (general idea)

Source• Source data type: RDF dump• Source data type: RDF dump• Source entity: dcterms:title• Filtering: English titles Target

• Target data type. SPARQL Endpoint• Target entity: dcterms:title• Filtering: English titles

Setting• Matching algorithm: Trigrams• Matching algorithm: Trigrams• Threshold of acceptance: 95%• Output file format: N-TRIPLE• ...


Interlinking processInterlinking process


The interlinking tools (SILK)The interlinking tools (SILK)


The interlinking tools (LIMES)The interlinking tools (LIMES)

Source & Target datasets

Condition


The interlinking tools (LOD Refine)The interlinking tools (LOD Refine)


Sample interlinking results (exact matched)Sample interlinking results (exact matched)

Title in both datasets Globe resource Target URI Dataset name

lhttp://www.globe-i f / t/l 2

http://schools.nyc.gov/NR/rdonlyres/6C64098F-0C24-4B27-A22F-F542A2F97DA0/130926/TTS_G11_LiteracySSandScience_NuclearEnergy.pdf

ASN

Nuclear Energy info.org/ont/lom2owl# 108450 http://resrev.ilrt.bris.ac.uk/research-revealed-

hub/publications/118933#pub Bristol

http://data.linkedu.eu/hud/book/118555 Huddersfield

Bibliographyhttp://www.globe-info.org/ont/lom2owl#178214

http://resrev.ilrt.bris.ac.uk/research-revealed-hub/publications/15140#pub OpenUK

http://data.uni-muenster de/context/istg/allegro/6/210/T0024 Muenstermuenster.de/context/istg/allegro/6/210/T00244773

Muenster


Evaluating the interlinking toolsEvaluating the interlinking tools

We used three tools to interlink GLOBE to DBpedia

GLOBE and DBpedia on title


Evaluating the interlinking toolsEvaluating the interlinking tools

Does the result change if we use more than one tool?

Common results among the tools



Applying the interlinking tools for linking datasets i li bl th d


is a reliable method. Silk and LIMES were the efficient tools for

similarity discovery among the LOD datasets.similarity discovery among the LOD datasets.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “An empirical study on the evaluation of interlinking tools on the Web of Data,” Journal of Information Science, vol 40, pp.637–648 2014 fi t bli h d J 11 2014648 2014, first published on June 11, 2014.


Objective 4:Assessing the interlinking results

and their advantages

6. Studies and experimentations

Evaluating the interlinking resultsEvaluating the interlinking results

Interlinking tools perform an interlinking d i t t th t h d process and print out the matched resources.

The question under this discussion is to what The question under this discussion is to what extent are the results reliable?

An important step after doing the interlinking is evaluating the interlinking results by human and domain expertsand domain experts.


The interlinking approachThe interlinking approach


GLOBE metadata analysisGLOBE metadata analysis

Creating a criteria under which we can findappropriate elements for interlinking (datatype, completeness, content)pp p g ( yp , p , )


GLOBE metadata analysisGLOBE metadata analysis


Interlinking resultsInterlinking results

Title Keyword Taxon Coverage

GLOBE 8,260 228,352 134,791 12,941

Percentage 2% 74% 76% 78%

Interlinking through the Keyword element


Evaluating the interlinking resultsEvaluating the interlinking resultsWe evaluated the interlinking results from

the following perspectives:the following perspectives: Reliability Level of agreement between the ratersg

Relationship among results (e.g., threshold 75%)

Is parent of, Is related to, Is part of Enrichment of content

Li ki d Linking one resource to many datasets on the Web


Remarks of this investigationg Human experts (the results raters) agreed that the

interlinking results are reliable. Interlinking a learning repository to several

educational datasets in the LOD cloud leads to the enrichment of content.

Interlinking results can lead to duplicate metadata finding.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Discovering Duplicate and Related Resources using Interlinking Approach: The case of Educational Datasets,” Journal of Information Science, first

bli h d M h 10 2015

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Interlinking Educational Data: an Experiment with Engineering-related

published on March 10, 2015

Resources in GLOBE,” International Journal of Engineering and Education, Vol 31-3, 2015.


Conclusions

1. Exposing eLearning metadata as Linked O D t Open Data

A complete analysis was done on exposing the IEEE LOM schema as RDFIEEE LOM schema as RDF.

A new ontology was designed for RDF binding of IEEE LOM.

Keyword, Coverage, Classification, and Title were appropriate elements for interlinking.

7. Conclusion & Future work47 out of 54

Conclusions (cont.)

2. Evaluating Linked Data tools & datasets

( )

Silk and LIMES were the efficient frameworks in terms of discovering similarities between two ddatasets.

DBpedia was identified as the hub of the LOD cloud. cloud.

Twenty educational dataset were identified as the most proper targets for interlinking.

The Open University of UK includes rich metadata schema and reliable endpoint.


Conclusions (cont.)

3. Enriching the educational datasets

( )

g Interlinking results were reviewed and

verified by human experts. Several educational resources were linked to

more than one resources in the LOD cloud. A duplicate identification was proposed after

the analysis of the interlinking results.


Additional contributions

Implementing several platform for exposing data as Linked DataLinked Data Organic.Edunet (http://data.organic-edunet.eu) ARIADNE (http://ariadne.grnet.gr) Open Discovery Space (http://data opendiscoveryspace eu) Open Discovery Space (http://data.opendiscoveryspace.eu) Agrega (http://agrega2.red.es/ )

Submitting the IEEE LOM ontology to Linked Open Vocabularies (LOV) at Vocabularies (LOV) at http://lov.okfn.org/dataset/lov/vocabs/lom

Developing an online Mashup to interlinking eLearning objects to Web of Data (research stay in eLearning objects to Web of Data (research stay in Agroknow)

Writing a book chapter about “Optimizing Big Data using the Linked Data approach”


Additional contributions (cont.)( )


Future work

Content Applying the interlinking approach to other

educational repositories Tools and software Tools and software

Extending the tools to link one datasets to several datasets at the same time

Adding some semantic similarity services to tools to improve the interlinking results

Linking educational resources by datasets crawling


Publications (journal papers)(j p p ) E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Interlinking Educational Resources to Web of Data

through IEEE LOM”. Computer Science and Information Systems, vol. 12, No. 1, pp. 233–255, 2015.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Discovering Duplicate and Related Resources using Interlinking Approach: The case of Educational Datasets,” Journal of Information Science, first published on March 10, 2015 doi:10.1177/0165551515575922.

E. Rajabi, S. Sanchez-Alonso, and M.-A. Sicilia, “Analyzing Broken Links on the Web of Data: an Experiment with DBpedia,” Journal of the Association for Information Science and Technology (JASIST), vol. 65, no. 8, pp. 1721–1727, 2014 doi: 10.1002/asi.23109.gy ( ) pp /

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “An empirical study on the evaluation of interlinking tools on the Web of Data,” Journal of Information Science, vol 40, pp.637–648 2014, first published on June 11, 2014 doi:10.1177/0165551514538151.

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Interlinking Educational Data: an Experiment with Engineering related Resources in GLOBE ” International Journal of Engineering and Education Engineering-related Resources in GLOBE, International Journal of Engineering and Education, 2015. In press.

E. Rajabi, W Greller, K Niemann, K Kastrantas, S Sanchez-Alonso, Social data interoperability in educational repositories and federations , International Journal of Metadata, Semantics and Ontologies 8 (2), 169 - 178, 2013.

E. Rajabi, S. Sanchez-Alonso, M.-A. Sicilia, and N. Mouneselis, “A linked and open dataset from a network of learning repositories on organic agriculture”, British Journal of Educational Technology, submitted (under second review).

M-C Valiente, M.-A. Sicilia, E. Garcia-Barriocanal, E. Rajabi, "Adopting the metadata approach to improve the search and analysis of educational resources for online learning", Computers in Human


p y g , pBehavior. 2015. In press.

Publications (conference papers)( p p ) E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, “Interlinking Educational Data: an

Experiment with GLOBE Resources,” presented at the First International Conference on Technological Ecosystem for Enhancing Multiculturality, Salamanca, Spain, 2013. g y g y, , p ,

E. Rajabi, M.-A. Sicilia, and S. Sanchez-Alonso, "Research Objects Interlinking: The Case of Dryad Repository”, presented at Metadata and Semantics Research, Karlsruhe, Germany, 2014.

E. Rajabi, and S. Sanchez-Alonso, "Enriching the e-learning contents using j , , g g ginterlinking”, presented at 5th eLearning conference, Belgrade, Serbia, 2014. Link: https://scholar.google.es/scholar?oi=bibs&cluster=16249634834288673991&btnI=1&hl=en

E. Rajabi, M.-A. Sicilia, S. Sanchez-Alonso, A Simple Approach towards SKOSificationof Digital Repositories , Metadata and Semantics Research, 67-74, 2013.

M-A. Sicilia, S. Sanchez-Alonso, E. Garcia-Barriocanal, J. Minguillón and E. Rajabi, Exploring the keyword space in large learning resource aggregations: the case of GLOBE, Lacro workshop, April 2013.


Interlinking educational data to Web of Data (Thesis presentation)

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