Using Linked Data in Learning AnalyticsLAK 2013 tutorial
Mathieu d’Aquin (@mdaquin, mdaquin.net)(Knowledge Media Institute, The Open University, UK)Stefan Dietze (L3S Research Center, DE)Hendrik Drachsler(CELSTEC, Open Universiteit Nederland, NL)Eelco Herder(L3S Research Center, DE)
Why a Linked Data Tutorial at LAK 2013?A Naïve view
Learning Analytics is an application of data analytics on educational data, in learning environment and for the purpose to improve the learning and teaching experience.
Linked Data is a set of technologies and principles to expose, publish and interconnect data on the Web. It is very popular nowadays for opendata, eGovernment, academia and the industry because of the flexibility and the global integration possibilities it provides.
So, Linked Data used to find, collect and process large amounts of interconnected data to be used in analytics. But It is not only the input! Can be used to complete local data, enrichment them, or for interpretation of the results.
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
The LAK Data Challenge (preview)
Soude Fazeli – Open Universiteit Nederland (Netherlands). Socio-semantic Networks of Research Publications in the Learning Analytics Community
Michael Derntl, Nikou Günnemann and Ralf Klamma – RWTH Aachen (Germany). A Dynamic Topic Model of Learning Analytics Research
Ricardo Alonso Maturana, María Elena Alvarado, Susana Lopez-Sola, María José Ibáñez and Lorena Ruiz Elósegui – GNOSS (Spain). Linked Data based applications for Learning Analytics Research: faceted searches, enriched contexts, graph browsing and geographic visualisation
Nikola Milikic, Uros Krcadinac, Jelena Jovanovic, Bojan Brankov and Srdjan Keca – University of Belgrade, UZROK Labs (Serbia).Paperista: Visual Exploration of Semantically Annotated Research Papers
Sadia Nawaz, Farshid Marbouti and Johannes Strobel – Purdue University (United States). Analysis of the Community of Learning Analytics
Bernardo Pereira Nunes and Besnik Fetahu – L3S Research Center (Germany). Cite4Me: Semantic Retrieval and Analysis of Scientific Publications
Davide Taibi, Ágnes Sándor, Duygu Simsek, Simon Buckingham Shum, Anna De Liddo and Rebecca Ferguson – Italian National Research Council, Xerox Research Center (France), The Open University (UK). Visualizing the LAK/EDM Literature Using Combined Concept and Rhetorical Sentence Extraction
Amal Zouaq, Srecko Joksimovic and Dragan Gasevic – Royal Military College of Canada, Simon Fraser University, Athabasca University (Canada). Ontology Learning to Analyze Research Trends in Learning Analytics Publications
Your guides to the wild world of linked data
Mathieu@mdaquin
Stefan@stefandietze
Hendrik@hdrachsler
Eelco@eelcoherder
(put he is not actually here)
Linked data and its potential in learning analytics scenarios
Linked Data
Open University Website
Open UniversityVLE
KMi Website
Mathieu’s Homepage
Mathieu’s List of
PublicationsMathieu’s
The Web
M366 Coursepage
Person: Mathieu
Publication: Pub1
Organisation:The Open University
Course: M366
Country: Belgium
Book: Mechatronics
author
workFor
availableIn
offers
setBook
The Web of Linked Data
From Linked Data to the Semantic Web
Gene Ontology
FMA OntologyLODE
BIBO
Geo Ontology
DBPedia Ontology
Dublin Core
FOAF
DOAP
SIOC
Music Ontology
Media Ontology
rNews
Example: data.open.ac.uk
Data.open.ac.uk
Course information: 580 modules/ description of the course, information about the levels and number of
credits associated with it, topics, and conditions of enrolment.
Research publications: 16,000 academic articles / information about authors, dates, abstract and venue of the
publication.
Podcasts: 2220 video podcasts and 1500 audio podcats / short description, topics, link to a
representative image and to a transscript if available, information about the course the podcast might relate to and license information regarding the content of the podcast.
Open Educational Resources: 640 OpenLearn Units / short description, topics, tags used to annotate the resource, its
language, the course it might relate to, and the license that applies to the content.
Youtube videos: 900 videos / short description of the video, tags that were used to annotate the video,
collection it might be part of and link to the related course if relevant.
University buildings: 100 buildings / address, a picture of the building and the sub-divisions of the building
into floors and spaces.
Library catalogue: 12,000 books/ topics, authors, publisher and ISBN, as well as the course related.
Others…
A global data space for education data
The Open University
University of Bristol
University of Southampton
mEducator
University of Muenster, DEOrganicEduNet
Data.gov.uk education
Orgs., Buidings, Locations
Learning resources
Research ouputs
8. April 2023LinkedUp – Mathieu d‘Aquin 12
http://data.linkededucation.org/linkedup/catalog
What’s the use in Learning Analytics
From Bienkowski, Feng, and Means areas of LA/EDM applications
• Modeling user knowledge, behavior, and experience… and connect them to information about the context of learning
• Creating profiles of users… that can be interlinked through common objects
• Modeling knowledge domains… through online knowledge sources that can be numerous and collectively built
• Trend analysis… that can be interpreted through related them to external sources of information
• Personalization and adaptation… using indirect connections to other reference entities
Original image from George Siemenshttp://www.elearnspace.org/blog/2010/08/25/what-are-learning-analytics/
Data
Integration
Understanding
Example of simple application: Map of OU buildings
Interactive map of Open University Buildings in the UK
Each dot is a location where buildings can be found. Going over the dot give information about the building there (floors, spaces, car-parks, etc.)
Spaces
Floors
ID Address Post-code
Buildings
bat1
bat1-address
Postcode-mk76aa
name “Berrill building”
data.open.ac.ukMilton Keynes
inDistrict
Buckinghamshire
inCounty
Mk76aa-location
location
lat long
52.024924 -0.709726
data.ordnancesurvey.co.uk
Simple recommendation: Study at the OU
Each topic as a linked data URI. Each course as a linked data URI. Each resource as a linked data URI. They are all connected. Use SPARQL to answer the question:
“What are the resources related to this topic or to courses on this topic”
Less simple recommendation: Talis Aspire
Lecturers from different universities put their reading lists online. Publishing using the principles of linked data means that all resources are globally identified, creating a network of resources and reading lists.Recommendations can then trivially exploit globally all these local contributions.
Even less simple recommendation:DiscOU
data.open.ac.uk
Semantic Indexing
Semantic Index
Named Entity
RecognitionPodcasts, OpenLearn Units and Articles
Semantic Entities (Dbpedia)
Indexes
BBC Programme or iPlayer page
Synopsis
Similarity-Based Search
Indexes
Interface
Resource descriptions
Resources URIs + common topics
Not one scenario: An infinite recombination of data and purposes
Complex analytics in a lightweight way
http://uciad.info
Analytics across datasets
Academics in “Arts and Humanities” most often involved with the media (in number of news items)
Topics most commonly mentioned by news outlets own by the BBC (in number of news items)
From the Open University From news clippings From DBpedia.org
Complex analytics with rich background information
Basics of manipulating linked data
Agenda
URIs – the basis
RDF – the representation language
Ontologies/Vocabularies – for schemas and models
SPARQL – for querying
SPARQL Update – for modifying (but we won’t say much about this)
URIs – three roles
Example:
http://data.aalto.fi/id/courses/noppa/dept_T3030
An anchor for linkingLet’s say you have worked
there. You – worked-at this URI
An identifier for a data entity
Here, the Department of Media Technology of the University of
Aalto, Finland
An access point to representation(s) of
the data entityIn possibly different formats…
URI resolving
http://data.aalto.fi/id/courses/noppa/dept_T3030
8. April 2023 29
In the browser(Accept: text/html)
curl -H "Accept: application/rdf+xml" -L http://data.aalto.fi/id/courses/noppa/dept_T3030
<rdf:Description rdf:about="http://data.aalto.fi/data/id/courses/noppa/dept_T3030"> <rdfs:label>RDF description of Department of Media Technology</rdfs:label> <foaf:primaryTopic> <aiiso:Department rdf:about="http://data.aalto.fi/id/courses/noppa/dept_T3030"> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5077"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.2211"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.3101"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5100"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5006"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.1300"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5600"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4950"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.1100"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.6596"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5300"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.1220"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.4360"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5701"/> <aiiso:code>T3030</aiiso:code> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4210"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5070"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4400"/> <foaf:name xml:lang="en">Department of Media Technology</foaf:name> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5310"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5020"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.1110"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.6595"/> <foaf:name xml:lang="sv">Institutionen för mediateknik</foaf:name> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.1202"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5700"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5600"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.1124"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4100"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4900"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.2300"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5360"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.4101"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5200"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.2400"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5030"/> <aiiso:part_of> <rdf:Description rdf:about="http://data.aalto.fi/id/courses/noppa/org_SCI"> <aiiso:organization rdf:resource="http://data.aalto.fi/id/courses/noppa/dept_T3030"/> </rdf:Description> </aiiso:part_of> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5700"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.4800"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5502"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5350"/>
RDF – graph data model for linked data and the Web
Basic idea: URIs and literals (String, integers) are nodes - connected by links labelled by properties (themselves identified as URIs)
http://data.aalto.fi/id/courses/noppa/dept_T3030
“Department of Media Technology”
foaf:name
aiiso:Departmentrdf:type
http://data.aalto.fi/id/courses/noppa/org_SCI
aiiso:part_ofaiiso:School
rdf:type
“School of Science”foaf:name
http://data.aalto.fi/id/courses/noppa/course_Inf-0.1202
aiiso:teaches
aiiso:Courserdf:typeteach:courseTitle
“Filosofia”
“fi”dc:language
RDF+XML
<aiiso:Department rdf:about="http://data.aalto.fi/id/courses/noppa/dept_T3030"> <aiiso:code>T3030</aiiso:code> <foaf:name xml:lang="en">Department of Media Technology</foaf:name> <foaf:name xml:lang="sv">Institutionen för mediateknik</foaf:name> <aiiso:part_of rdf:resource="http://data.aalto.fi/id/courses/noppa/org_SCI"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5077"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.2211"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.1100"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.6596"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5300"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.1220"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.4360"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5701"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4210"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5070"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.4400"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_Inf-0.4101"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-75.5200"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.2400"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5030"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.5700"/> <aiiso:teaches rdf:resource="http://data.aalto.fi/id/courses/noppa/course_T-111.4800"/>
Other syntaxes…
… Ntriple, Turtle and JSON-LD
Simpler to a certain extent, but same principles
Spaces
Floors
ID Address Post-code
Buildings
bat1
bat1-address
Postcode-mk76aa
name “Berrill building”
data.open.ac.ukMilton Keynes
inDistrict
Buckinghamshire
inCounty
Mk76aa-location
location
lat long
52.024924 -0.709726
data.ordnancesurvey.co.uk
Remember…
Ontologies and Vocabularies
Role: Provide common definitions for the types (classes) and properties (relations) used in the RDF representations, and their expected behaviour (meaning)
Vocabularies and ontologies we have already seen:• AIISO: Academic Institution Internal Structure Ontology• DC: Dublin Core• FOAF: Friend of a Friend (for people and their connections)• TEACH: For courses and academic programmes
Use the same mechanisms as Linked Data: • Classes and properties have URIs• They connect through special properties (rdf:type, rdfs:domain, rdfs:range,
rdfs:subClassOf, etc.)
Formal ontologies: define more precisely the intended meaning of types and properties based on logical constructs
8. April 2023LinkedUp – Author Name 35
Example: AIISO
foaf:Organization
aiiso:School
rdfs:subClassOf
aiiso:College
aiiso:Course
aiiso:Department
rdfs:subClassOf
rdfs:subClassOf
aiiso:Institution
rdfs:subClassOf
aiiso:Faculty
rdfs:subClassOf
aiiso:KnowledgeGrouping
rdfs:subClassOf
aiiso:Module
rdfs:subClassOf
aiiso:Programme
rdfs:subClassOf
aiiso:part_of
foaf:Agent
aiiso:responsibleFor
aiiso:responsibleFor
aiiso:teaches
Example: BIBO
bibo:Article
bibo:AcademicArticle
bibo:Document
bibo:Book
bibo:AudioVisualDocument
bibo:DocumentPart
bibo:BookSection
bibo:Chapter
bibo:EditedBook
bibo:Issue
bibo:Journal
rdfs:subClassOf
rdfs:subClassOfrdfs:subClassOf
rdfs:subClassOf
rdfs:subClassOf
rdfs:subClassOfrdfs:subClassOf
bibo:partOf
All bibo:partOf
<=1 bibo:partOf
<=1 bibo:partOf
Querying: SPARQL
ASK query: is this true?ask {<http://data.aalto.fi/id/courses/noppa/dept_T3030> a
aiiso:Department} (is it a department?)ask{<http://data.aalto.fi/id/courses/noppa/dept_T3030> dc:subject ?x}
(is there a subject to this department?)
Select query: Get me some dataselect ?org ?name where { ?x a aiiso:Department. ?x aisso:part_of ?org. ?org foaf:name ?name. filter( ?x != <http://data.aalto.fi/id/courses/noppa/dept_T3030> ) } order by ?name limit 100(get the organisations with names that have department, except T3030)
Construct query: Build a (sub) RDF graphconstruct {?agent1 foaf:knows ?agent2} where {?agent1 aiiso:responsibleFor ?x. ?agent2:responsibleFor ?x}(Construct of graph of people knowing each-other because of being responsible from the same thing)
Querying: SPARQL
SPARQL is also a protocol for Web-based data endpoints…
Example
select distinct ?course where {?course <http://data.open.ac.uk/saou/ontology#isAvailableIn> <http://sws.geonames.org/2328926/>.?course a <http://purl.org/vocab/aiiso/schema#Module>
}
Open University courses available in Nigeria (http://sws.geonames.org/2328926/) on http://data.open.ac.uk/query
Example
select distinct ?q (count(distinct ?t) as ?n) where { ?q a <http://purl.org/net/mlo/qualification>. ?q <http://data.open.ac.uk/saou/ontology#hasPathway> ?p. ?p <http://data.open.ac.uk/saou/ontology#hasStage> ?s. {{?s <http://data.open.ac.uk/saou/ontology#includesCompulsoryCourse> ?c} union {?s <http://data.open.ac.uk/saou/ontology#includesOptionalCourse> ?c}}. ?c <http://purl.org/dc/terms/subject> ?t. [] <http://www.w3.org/2004/02/skos/core#hasTopConcept> ?t.} group by ?q order by desc(?n)
How many top level subjects are represented in individual Open University qualifications on http://data.open.ac.uk/query
Example
select ?broader ?term ?narrowerwhere { graph npgg:subjects { ?subject skos:prefLabel ?term . ?subject skos:broader [ skos:prefLabel ?broader ] . ?_ skos:broader ?subject ; skos:prefLabel ?narrower . } filter(regex(?term, "^Stem cells$", "i"))}order by ?broader ?narrower
Broader and narrower terms for "Stem cells“ on http://data.nature.com/query
Example
select ?doi ?datawhere { ?doi a npg:Article ; npg:hasDataCitation [ npg:hasLink [ ?_ ?data ] ; npg:type ?type ] . filter(regex(?type, "pdb"))}limit 25
Data citations to the Protein Database on http://data.nature.com/query
SPARQL update
Delete querydelete {?x ?p ?y} where { ?x a aiiso:Course. ?x ?p ?y. ?a1 aiiso:responsibleFor ?x. ?a2 aiiso:responsibleFor ?x. filter ( ?a1 != ?a2 )}
Insert query insert {?x a onto:WeirdCourse} where{ ?x a aiiso:Course. ?a1 aiiso:responsibleFor ?x. ?a2 aiiso:responsibleFor ?x. filter ( ?a1 != ?a2 )}
Basic take away message
Linked data is about using the web architecture for sharing and connecting data, with some form of meaningful interpretation (semantic web)
Potential in Learning Analytics processes: as input data, for data integration, for enrichment, for interpretation
Based on simple technologies for web-based access to the data: URI, RDF, Web Schemas, SPARQL
Links and References
http://linkeddata.org - http://linkeddatabook.com http://data.open.ac.uk - http://lucero-project.info http://linkeduniversities.org - http://linkededucation.orghttp://linkedup-project.eu - http://linkedup-challenge.orghttp://data.linkededucation.org/linkedup/catalog/ http://talisaspire.com/ - http://discou.info - http://uciad.info http://http://www.w3.org/TR/rdf-sparql-query/ http://www.w3.org/TR/sparql11-update/
d'Aquin, M. and Jay, N. Interpreting Data Mining Results with Linked Data for Learning Analytics: Motivation, Case Study and Direction, LAK 2013, http://oro.open.ac.uk/36660/
Kessler C., d’Aquin M. and Dietze S. (eds) Semantic Web Journal Special Issue on Linked Data for Science and Education. http://iospress.metapress.com/content/m87017012802/
d’Aquin M. Linked Data for Open and Distance Learning. Commonwealth of Learnin report. http://www.col.org/resources/publications/Pages/detail.aspx?PID=420
d'Aquin, M., Allocca, C. and Collins, T. DiscOU: A Flexible Discovery Engine for Open Educational Resources Using Semantic Indexing and Relationship Summaries, Demo ISWC 2012. http://data.open.ac.uk/applications/iswc2012-demo.pdf
Bienkowski, M., Feng M. and Means, B. Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief. U.S. Department of Education, Office of Educational Technology http://www.ed.gov/edblogs/technology/files/2012/03/edm-la-brief.pdf