SlideShare a Scribd company logo
Online Learning and Linked Data
Lessons Learned and Best Practices
Dataset Profiling
3. April 2014 1Besnik Fetahu
LinkedUp: Data Catalog Features
 34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)
 VoID representations of datasets include the following information:
 Manual dataset schema alignments
 Accessibility information, i.e. SPARQL endpoint URL
3. April 2014 2Besnik Fetahu
http://purl.org/ontology/bibo/Thesis owl:equivalentClass http://purl.org/ontology/bibo/Thesis
http://swrc.ontoware.org/ontology#Article owl:equivalentClass http://purl.org/ontology/bibo/AcademicArticle
http://data.linkededucation.org/linkedup/dataset/data-open-ac-uk void:sparqlEndpoint http://data.open.ac.uk/queryCo-occurence graph of data
types in 146 datasets: 144
Vocabularies, 588 highly
overlapping types, 719
Properties
Assessing the Educational Linked Data Landscape, D’Aquin, M.,
Adamou, A., Dietze, S., ACM Web Science 2013 (WebSci2013), Paris,
France, May 2013.
LinkedUp: Data Catalog Features
 34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)
 VoID representations of datasets include the following information:
 Datasets’ resources type graph
 Datasets’ Topic Extraction (Dataset Profiling)
3. April 2014 3Besnik Fetahu
morelab
OpenCourseWare
LinkedUp: Data Catalog Features
 34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)
 VoID representations of datasets include the following information:
 Federated query interface:
3. April 2014 4Besnik Fetahu
PREFIX void: <http://rdfs.org/ns/void#>
PREFIX aiiso: <http://purl.org/vocab/aiiso/schema#>
SELECT DISTINCT ?endpoint WHERE{
?ds void:sparqlEndpoint ?endpoint.
{{ ?ds void:classPartition [void:class
aiiso:School] }
UNION
{?ds void:subset [void:classPartition [void:class
aiiso:School]] }}
}
LinkedUp: Why dataset profiling?
3. April 2014 5Besnik Fetahu
 Few linked dataset characteristics (from Linked Open Data Cloud).
Growing number of datasets: 227 datasets
Data represented as triples: 31 billion triples
Multi-lingual content: 18 languages
Broad set of topics covered
Inter-dataset links
Domain
Number of
datasets
Triples % (Out-)Links %
Media 25 1,841,852,061 5.82 % 50,440,705 10.01 %
Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 %
Government 49 13,315,009,400 42.09 % 19,343,519 3.84 %
Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 %
Cross-domain 41 4,184,635,715 13.23 % 63,183,065 12.54 %
Life sciences 41 3,036,336,004 9.60 % 191,844,090 38.06 %
User-generated
content
20 134,127,413 0.42 % 3,449,143 0.68 %
295 31,634,213,770 503,998,829
Domains covered by “lod-cloud” datasets
LinkedUp: Why dataset profiling?
3. April 2014 6Besnik Fetahu
Domain
Number of
datasets
Triples % (Out-)Links %
Media 25 1,841,852,061 5.82 % 50,440,705 10.01 %
Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 %
Government 49 13,315,009,400 42.09 % 19,343,519 3.84 %
Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 %
Cross-domain 41 4,184,635,715 13.23 % 63,183,065 12.54 %
Life sciences 41 3,036,336,004 9.60 % 191,844,090 38.06 %
User-generated
content
20 134,127,413 0.42 % 3,449,143 0.68 %
295 31,634,213,770 503,998,829
How do I find
information about
“renewable energy”?
31 billion
resources
18 languages 180 organisations
 How can we do that?
Check datasets that cover such topic?
Use SPARQL filter clause?
What are all possible forms of renewable energy?
38 out of 228 datasets
contain topic coverage
information
regex(*) filter clause
needs to check all
triples that contain a
specific keyword
renewable energy:
solar energy, wind
energy, geothermal…...
LinkedUp: How to profile Linked Data?
3. April 2014 7Besnik Fetahu
 What is a linked data profile?
Linked Dataset profiles consist of structured information describing their topic coverage. A profile
is represented as a graph. The vertices in the profile graph consist of datasets, resources, and
topics. The edges of the profile graph are constructed between the tuples ‹dataset, resources›
and ‹resources, topics›. Finally, edges between resources and topics are weighted conveying the
relevance of a topic for a dataset.
Profile Definition
<resource_uri_1> ?predicate_x value
<resource_uri_1> ?predicate_y value
<resource_uri_1> ?predicate_z value
A dataset consists of a
set of resource instances.
A resource is represented
by a set of triples.
A topic is equivalent to a DBpedia
category, associated to one of the
resource values.
<resource_uri_1>
<resource_uri_2>
……
<resource_uri_n>
Linked-Up: Profiling Linked Data
3. April 2014 8Besnik Fetahu
i. Metadata extraction
ii. Sampling of resource instances
iii. Entity and topic extraction
iv. Topic ranking (PageRank with Priors, HITS
with Priors and K-Step Markov)
v. Weighted dataset-topic profile graphs
vi. Profiles representation
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles. Besnik Fetahu,
Stefan Dietze, Bernardo Pereira Nunes, Marco Antonio Casanova, Davide Taibi, and Wolfgang Nejdl. In
Proceedings of the 11th Extended Semantic Web Conference, Springer, 2014 (to appear).
Profiling Linked Data – (I)
3. April 2014 9Besnik Fetahu
i. Metadata extraction:
 DataHub’s CKAN API
i. Sampling of resource instances
 weighted, random, centrality
i. Entity and topic extraction
 Consider only the textual values assigned to a resource
 NER: Disambiguate and extract named entities (DBpedia Spotlight)
Profiling Linked Data – (II)
3. April 2014 10Besnik Fetahu
i. Topic ranking (PageRank with Priors, HITS with Priors and K-Step Markov)
 Rank topics for each dataset, and compute their relevance w.r.t the
associated resources
i. Weighted dataset-topic profile graph
 The computed topic weights for each dataset, represent the weights for the
edges <dataset, topic>
i. Profiles representation (Vocabulary of Interlinked Datasets (VoID) and
Vocabulary of Links (VoL))
 VoID: Captures information about a Linked Dataset as a set of links
 VoL : Defines a link (of entity or topic type), along with the provenance
information and the relevance score of such link
Profiling Linked Data: Representation Example
3. April 2014Besnik Fetahu 11
Dataset Profile Metadata
Dataset’s Profile and Index
Entity Type Link
extracted entity
extracted topic
Provenance information
(resources) for the entity link
Provenance information (entities)
for the topic link
Topic Type Link
topic relevance score
SELECT ?dataset ?link ?score ?link_1 ?entity ?resource WHERE {
?dataset a void:Linkset.
?dataset vol:hasLink ?link.
?link vol:linksResource
<http://dbpedia.org/resource/Category:Renewable_energy>.
?link vol:derivedFrom ?entity.
?link vol:hasScore ?score.
?link_1 vol:linksResource ?entity.
?dataset vol:hasLink ?link_1.
?link_1 vol:derivedFrom ?resource }
ORDER BY DESC(?score)
3. April 2014Besnik Fetahu 12
How are the profiles useful?
• “Renewable Energy” is in different forms:
• Solar Energy
• Wind-farms
• Biogas
• Hydroelectricity etc.
http://enipedia.tudelft.nl/wiki/Windmar_Renewable_Energy
http://enipedia.tudelft.nl/data/page/eGRID/Plant/57050
http://enipedia.tudelft.nl/wiki/Us_Energy_Biogas_Corp
http://www.reegle.info/profiles/JP
How do I find
information about
“renewable energy”?
Profiling Linked Data: Evaluation
3. April 2014Stefan Dietze 13
Profiling accuracy for the different ranking approaches
using the full sample of analysed resource instances,
and with NDCG score averaged over all datasets.
The correlation between ranking accuracy (averaged
over all datasets and for ∆NDCG ) and ranking time.
Profiling Linked Data: Example use cases
3. April 2014Besnik Fetahu 14
 Type specific views on datasets/
categories
 “Document” (foaf:document)
 “Person “ (foaf:person)
 “Course” (aaiso:course)
 LinkedUp Catalog only (as schema mappings
already available here)
 Exploratory functionalities over
the dataset profiles
 Available for LinkedUp catalog
and the LOD-Cloud.
Online Learning and Linked Data
Lessons Learned and Best Practices
Cite4Me and Linked Challenge
3. April 2014Besnik Fetahu 15
Semantic Search and Retrieval of Publications
3. April 2014Besnik Fetahu 16
Semantic Search
Graph Search
Paper Recommendation
In-depth Analysis
Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications. Bernardo
Pereira Nunes, Besnik Fetahu, Stefan Dietze, and Marco Antonio Casanova. Proceedings of the 12th
International Semantic Web Conference, Sydney, Australia, (2013)
LinkedUp: Veni Challenge
3. April 2014Besnik Fetahu 17
DataConf.
KnowNodes
Mismuseos
ReCredible
YourHistory
3. April 2014
http://www.globe-town.org/
WeShare - 3rd
price / people‘s choice
GlobeTown - 2nd
price
http://seek.cloud.gsic.tel.uva.es/weshare/
http://www.polimedia.nl/
PoliMedia – 1st
price
Demos and Other Resources
3. April 2014Besnik Fetahu 18
Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications. Bernardo
Pereira Nunes, Besnik Fetahu, Stefan Dietze, and Marco Antonio Casanova. Proceedings of the 12th
International Semantic Web Conference, Sydney, Australia, (2013)
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles. Besnik Fetahu,
Stefan Dietze, Bernardo Pereira Nunes, Marco Antonio Casanova, Davide Taibi, and Wolfgang Nejdl. In
Proceedings of the 11th Extended Semantic Web Conference, Springer, 2014 (to appear).
Assessing the Educational Linked Data Landscape, D’Aquin, M., Adamou, A., Dietze, S., ACM Web
Science 2013 (WebSci2013), Paris, France, May 2013.
 LinkedUp Catalog: http://data.linkededucation.org/linkedup/catalog/
 DevTalk LinkedUp: http://data.linkededucation.org/linkedup/devtalk/
 LOD Profile Data: http://data-observatory.org/lod-profiles/sparql
 LOD Profile Explorer: http://data-observatory.org/lod-profiles/profile-explorer
 Cite4Me Application: http://www.cite4me.com/
 LinkedUp Challenge: http://linkedup-challenge.org/

More Related Content

What's hot

Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joinedKeystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
Joel Azzopardi
 
Documents, services, and data on the web
Documents, services, and data on the webDocuments, services, and data on the web
Documents, services, and data on the web
Chiara Del Vescovo
 
NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider Wor...
NISO/NFAIS Joint Virtual Conference:  Connecting the Library to the Wider Wor...NISO/NFAIS Joint Virtual Conference:  Connecting the Library to the Wider Wor...
NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider Wor...
National Information Standards Organization (NISO)
 
An introduction to Linked (Open) Data
An introduction to Linked (Open) DataAn introduction to Linked (Open) Data
An introduction to Linked (Open) Data
Ali Khalili
 
Introduction to RDF & SPARQL
Introduction to RDF & SPARQLIntroduction to RDF & SPARQL
Introduction to RDF & SPARQL
Open Data Support
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Ontotext
 
Linked library data
Linked library dataLinked library data
Linked library data
Jindřich Mynarz
 
Linking Open Government Data at Scale
Linking Open Government Data at Scale Linking Open Government Data at Scale
Linking Open Government Data at Scale
Bernadette Hyland-Wood
 
Linked Data in Libraries
Linked Data in LibrariesLinked Data in Libraries
Linked Data in Libraries
Carl Hess
 
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
National Information Standards Organization (NISO)
 
Resilient Linked Data
Resilient Linked DataResilient Linked Data
Resilient Linked Data
Dave Reynolds
 
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early AdoptersApril 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
National Information Standards Organization (NISO)
 
Linked Data Implementations—Who, What and Why?
Linked Data Implementations—Who, What and Why?Linked Data Implementations—Who, What and Why?
Linked Data Implementations—Who, What and Why?
OCLC
 
Role of Cataloger in the 21st Century Academic Library
Role of Cataloger in the 21st Century Academic LibraryRole of Cataloger in the 21st Century Academic Library
Role of Cataloger in the 21st Century Academic Library
New York University
 
NISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector AdministrationNISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector Administration
National Information Standards Organization (NISO)
 
Linked data as a library data platform
Linked data as a library data platformLinked data as a library data platform
Linked data as a library data platform
Jindřich Mynarz
 
Linked Open Data
Linked Open DataLinked Open Data
Linked Open Data
Lars Marius Garshol
 
Wed roman tut_open_datapub
Wed roman tut_open_datapubWed roman tut_open_datapub
Wed roman tut_open_datapub
eswcsummerschool
 
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
National Information Standards Organization (NISO)
 
Mending the Gap between Library's Electronic and Print Collections in ILS and...
Mending the Gap between Library's Electronic and Print Collections in ILS and...Mending the Gap between Library's Electronic and Print Collections in ILS and...
Mending the Gap between Library's Electronic and Print Collections in ILS and...
New York University
 

What's hot (20)

Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joinedKeystone summer school_2015_miguel_antonio_ldcompression_4-joined
Keystone summer school_2015_miguel_antonio_ldcompression_4-joined
 
Documents, services, and data on the web
Documents, services, and data on the webDocuments, services, and data on the web
Documents, services, and data on the web
 
NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider Wor...
NISO/NFAIS Joint Virtual Conference:  Connecting the Library to the Wider Wor...NISO/NFAIS Joint Virtual Conference:  Connecting the Library to the Wider Wor...
NISO/NFAIS Joint Virtual Conference: Connecting the Library to the Wider Wor...
 
An introduction to Linked (Open) Data
An introduction to Linked (Open) DataAn introduction to Linked (Open) Data
An introduction to Linked (Open) Data
 
Introduction to RDF & SPARQL
Introduction to RDF & SPARQLIntroduction to RDF & SPARQL
Introduction to RDF & SPARQL
 
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural HeritageBuild Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
Build Narratives, Connect Artifacts: Linked Open Data for Cultural Heritage
 
Linked library data
Linked library dataLinked library data
Linked library data
 
Linking Open Government Data at Scale
Linking Open Government Data at Scale Linking Open Government Data at Scale
Linking Open Government Data at Scale
 
Linked Data in Libraries
Linked Data in LibrariesLinked Data in Libraries
Linked Data in Libraries
 
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
April 24, 2013 NISO/DCMI Webinar: Deployment of RDA (Resource Description and...
 
Resilient Linked Data
Resilient Linked DataResilient Linked Data
Resilient Linked Data
 
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early AdoptersApril 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
April 8 NISO Webinar: Experimenting with BIBFRAME: Reports from Early Adopters
 
Linked Data Implementations—Who, What and Why?
Linked Data Implementations—Who, What and Why?Linked Data Implementations—Who, What and Why?
Linked Data Implementations—Who, What and Why?
 
Role of Cataloger in the 21st Century Academic Library
Role of Cataloger in the 21st Century Academic LibraryRole of Cataloger in the 21st Century Academic Library
Role of Cataloger in the 21st Century Academic Library
 
NISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector AdministrationNISO/DCMI Webinar: Metadata for Public Sector Administration
NISO/DCMI Webinar: Metadata for Public Sector Administration
 
Linked data as a library data platform
Linked data as a library data platformLinked data as a library data platform
Linked data as a library data platform
 
Linked Open Data
Linked Open DataLinked Open Data
Linked Open Data
 
Wed roman tut_open_datapub
Wed roman tut_open_datapubWed roman tut_open_datapub
Wed roman tut_open_datapub
 
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
NISO/DCMI Webinar: Schema.org and Linked Data: Complementary Approaches to Pu...
 
Mending the Gap between Library's Electronic and Print Collections in ILS and...
Mending the Gap between Library's Electronic and Print Collections in ILS and...Mending the Gap between Library's Electronic and Print Collections in ILS and...
Mending the Gap between Library's Electronic and Print Collections in ILS and...
 

Viewers also liked

Complex Matching of RDF Datatype Properties
Complex Matching of RDF Datatype PropertiesComplex Matching of RDF Datatype Properties
Complex Matching of RDF Datatype Properties
Besnik Fetahu
 
Combining a co-occurrence-based and a semantic measure for entity linking
Combining a co-occurrence-based and a semantic measure for entity linkingCombining a co-occurrence-based and a semantic measure for entity linking
Combining a co-occurrence-based and a semantic measure for entity linking
Besnik Fetahu
 
Automated News Suggestions for Populating Wikipedia Entity Pages
Automated News Suggestions for Populating Wikipedia Entity PagesAutomated News Suggestions for Populating Wikipedia Entity Pages
Automated News Suggestions for Populating Wikipedia Entity Pages
Besnik Fetahu
 
Towards Integration of Web Data into a coherent Educational Data Graph
Towards Integration of Web Data into a coherent Educational Data GraphTowards Integration of Web Data into a coherent Educational Data Graph
Towards Integration of Web Data into a coherent Educational Data Graph
Besnik Fetahu
 
How much is Wikipedia lagging behind News?
How much is Wikipedia lagging behind News?How much is Wikipedia lagging behind News?
How much is Wikipedia lagging behind News?
Besnik Fetahu
 
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
Besnik Fetahu
 
Improving Entity Retrieval on Structured Data
Improving Entity Retrieval on Structured DataImproving Entity Retrieval on Structured Data
Improving Entity Retrieval on Structured Data
Besnik Fetahu
 
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
A Scalable Approach for Efficiently Generating Structured Dataset Topic ProfilesA Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
Besnik Fetahu
 
Finding News Citations For Wikipedia
Finding News Citations For WikipediaFinding News Citations For Wikipedia
Finding News Citations For Wikipedia
Besnik Fetahu
 

Viewers also liked (9)

Complex Matching of RDF Datatype Properties
Complex Matching of RDF Datatype PropertiesComplex Matching of RDF Datatype Properties
Complex Matching of RDF Datatype Properties
 
Combining a co-occurrence-based and a semantic measure for entity linking
Combining a co-occurrence-based and a semantic measure for entity linkingCombining a co-occurrence-based and a semantic measure for entity linking
Combining a co-occurrence-based and a semantic measure for entity linking
 
Automated News Suggestions for Populating Wikipedia Entity Pages
Automated News Suggestions for Populating Wikipedia Entity PagesAutomated News Suggestions for Populating Wikipedia Entity Pages
Automated News Suggestions for Populating Wikipedia Entity Pages
 
Towards Integration of Web Data into a coherent Educational Data Graph
Towards Integration of Web Data into a coherent Educational Data GraphTowards Integration of Web Data into a coherent Educational Data Graph
Towards Integration of Web Data into a coherent Educational Data Graph
 
How much is Wikipedia lagging behind News?
How much is Wikipedia lagging behind News?How much is Wikipedia lagging behind News?
How much is Wikipedia lagging behind News?
 
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
Summaries on the fly: Query-based Extraction of Structured Knowledge from Web...
 
Improving Entity Retrieval on Structured Data
Improving Entity Retrieval on Structured DataImproving Entity Retrieval on Structured Data
Improving Entity Retrieval on Structured Data
 
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
A Scalable Approach for Efficiently Generating Structured Dataset Topic ProfilesA Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles
 
Finding News Citations For Wikipedia
Finding News Citations For WikipediaFinding News Citations For Wikipedia
Finding News Citations For Wikipedia
 

Similar to euclid_linkedup WWW tutorial (Besnik Fetahu)

Semantic Linking & Retrieval for Digital Libraries
Semantic Linking & Retrieval for Digital LibrariesSemantic Linking & Retrieval for Digital Libraries
Semantic Linking & Retrieval for Digital Libraries
Stefan Dietze
 
Interlinking educational data to Web of Data (Thesis presentation)
Interlinking educational data to Web of Data (Thesis presentation)Interlinking educational data to Web of Data (Thesis presentation)
Interlinking educational data to Web of Data (Thesis presentation)
Enayat Rajabi
 
WWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & EducationWWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & Education
Stefan Dietze
 
Retrieval, Crawling and Fusion of Entity-centric Data on the Web
Retrieval, Crawling and Fusion of Entity-centric Data on the WebRetrieval, Crawling and Fusion of Entity-centric Data on the Web
Retrieval, Crawling and Fusion of Entity-centric Data on the Web
Stefan Dietze
 
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the WebBeyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
Stefan Dietze
 
Open library data and embrace the world library linked data
Open library data and embrace the world library linked dataOpen library data and embrace the world library linked data
Open library data and embrace the world library linked data
皓仁 柯
 
LUCERO - Building the Open University Web of Linked Data
LUCERO - Building the Open University Web of Linked DataLUCERO - Building the Open University Web of Linked Data
LUCERO - Building the Open University Web of Linked Data
Mathieu d'Aquin
 
Integration of research literature and data (InFoLiS)
Integration of research literature and data (InFoLiS)Integration of research literature and data (InFoLiS)
Integration of research literature and data (InFoLiS)
Philipp Zumstein
 
A Generic Scientific Data Model and Ontology for Representation of Chemical Data
A Generic Scientific Data Model and Ontology for Representation of Chemical DataA Generic Scientific Data Model and Ontology for Representation of Chemical Data
A Generic Scientific Data Model and Ontology for Representation of Chemical Data
Stuart Chalk
 
Poster RDAP13: Research Data in eCommons @ Cornell: Present and Future
Poster RDAP13: Research Data in eCommons @ Cornell: Present and FuturePoster RDAP13: Research Data in eCommons @ Cornell: Present and Future
Poster RDAP13: Research Data in eCommons @ Cornell: Present and Future
ASIS&T
 
The Electronic Notebook Ontology
The Electronic Notebook OntologyThe Electronic Notebook Ontology
The Electronic Notebook Ontology
Stuart Chalk
 
Presentation of LUCERO at EURECOM
Presentation of LUCERO at EURECOMPresentation of LUCERO at EURECOM
Presentation of LUCERO at EURECOM
Mathieu d'Aquin
 
What's all the data about? - Linking and Profiling of Linked Datasets
What's all the data about? - Linking and Profiling of Linked DatasetsWhat's all the data about? - Linking and Profiling of Linked Datasets
What's all the data about? - Linking and Profiling of Linked Datasets
Stefan Dietze
 
Reuse of Structured Data: Semantics, Linkage, and Realization
Reuse of Structured Data: Semantics, Linkage, and RealizationReuse of Structured Data: Semantics, Linkage, and Realization
Reuse of Structured Data: Semantics, Linkage, and Realization
andrea huang
 
Open Data Dialog 2013 - Linked Data in Education
Open Data Dialog 2013 - Linked Data in EducationOpen Data Dialog 2013 - Linked Data in Education
Open Data Dialog 2013 - Linked Data in Education
Stefan Dietze
 
Turning Data into Knowledge (KESW2014 Keynote)
Turning Data into Knowledge (KESW2014 Keynote)Turning Data into Knowledge (KESW2014 Keynote)
Turning Data into Knowledge (KESW2014 Keynote)
Stefan Dietze
 
LinkedUp - Linked Data Europe Workshop 2014
LinkedUp - Linked Data Europe Workshop 2014LinkedUp - Linked Data Europe Workshop 2014
LinkedUp - Linked Data Europe Workshop 2014
Stefan Dietze
 
Bioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future PerspectivesBioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future Perspectives
University of Malaya
 
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
Carole Goble
 
2011linked science4mccuskermcguinnessfinal
2011linked science4mccuskermcguinnessfinal2011linked science4mccuskermcguinnessfinal
2011linked science4mccuskermcguinnessfinal
Deborah McGuinness
 

Similar to euclid_linkedup WWW tutorial (Besnik Fetahu) (20)

Semantic Linking & Retrieval for Digital Libraries
Semantic Linking & Retrieval for Digital LibrariesSemantic Linking & Retrieval for Digital Libraries
Semantic Linking & Retrieval for Digital Libraries
 
Interlinking educational data to Web of Data (Thesis presentation)
Interlinking educational data to Web of Data (Thesis presentation)Interlinking educational data to Web of Data (Thesis presentation)
Interlinking educational data to Web of Data (Thesis presentation)
 
WWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & EducationWWW2013 Tutorial: Linked Data & Education
WWW2013 Tutorial: Linked Data & Education
 
Retrieval, Crawling and Fusion of Entity-centric Data on the Web
Retrieval, Crawling and Fusion of Entity-centric Data on the WebRetrieval, Crawling and Fusion of Entity-centric Data on the Web
Retrieval, Crawling and Fusion of Entity-centric Data on the Web
 
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the WebBeyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
Beyond Linked Data - Exploiting Entity-Centric Knowledge on the Web
 
Open library data and embrace the world library linked data
Open library data and embrace the world library linked dataOpen library data and embrace the world library linked data
Open library data and embrace the world library linked data
 
LUCERO - Building the Open University Web of Linked Data
LUCERO - Building the Open University Web of Linked DataLUCERO - Building the Open University Web of Linked Data
LUCERO - Building the Open University Web of Linked Data
 
Integration of research literature and data (InFoLiS)
Integration of research literature and data (InFoLiS)Integration of research literature and data (InFoLiS)
Integration of research literature and data (InFoLiS)
 
A Generic Scientific Data Model and Ontology for Representation of Chemical Data
A Generic Scientific Data Model and Ontology for Representation of Chemical DataA Generic Scientific Data Model and Ontology for Representation of Chemical Data
A Generic Scientific Data Model and Ontology for Representation of Chemical Data
 
Poster RDAP13: Research Data in eCommons @ Cornell: Present and Future
Poster RDAP13: Research Data in eCommons @ Cornell: Present and FuturePoster RDAP13: Research Data in eCommons @ Cornell: Present and Future
Poster RDAP13: Research Data in eCommons @ Cornell: Present and Future
 
The Electronic Notebook Ontology
The Electronic Notebook OntologyThe Electronic Notebook Ontology
The Electronic Notebook Ontology
 
Presentation of LUCERO at EURECOM
Presentation of LUCERO at EURECOMPresentation of LUCERO at EURECOM
Presentation of LUCERO at EURECOM
 
What's all the data about? - Linking and Profiling of Linked Datasets
What's all the data about? - Linking and Profiling of Linked DatasetsWhat's all the data about? - Linking and Profiling of Linked Datasets
What's all the data about? - Linking and Profiling of Linked Datasets
 
Reuse of Structured Data: Semantics, Linkage, and Realization
Reuse of Structured Data: Semantics, Linkage, and RealizationReuse of Structured Data: Semantics, Linkage, and Realization
Reuse of Structured Data: Semantics, Linkage, and Realization
 
Open Data Dialog 2013 - Linked Data in Education
Open Data Dialog 2013 - Linked Data in EducationOpen Data Dialog 2013 - Linked Data in Education
Open Data Dialog 2013 - Linked Data in Education
 
Turning Data into Knowledge (KESW2014 Keynote)
Turning Data into Knowledge (KESW2014 Keynote)Turning Data into Knowledge (KESW2014 Keynote)
Turning Data into Knowledge (KESW2014 Keynote)
 
LinkedUp - Linked Data Europe Workshop 2014
LinkedUp - Linked Data Europe Workshop 2014LinkedUp - Linked Data Europe Workshop 2014
LinkedUp - Linked Data Europe Workshop 2014
 
Bioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future PerspectivesBioinformatics databases: Current Trends and Future Perspectives
Bioinformatics databases: Current Trends and Future Perspectives
 
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
The ELIXIR FAIR Knowledge Ecosystem for practical know-how: RDMkit and FAIRCo...
 
2011linked science4mccuskermcguinnessfinal
2011linked science4mccuskermcguinnessfinal2011linked science4mccuskermcguinnessfinal
2011linked science4mccuskermcguinnessfinal
 

Recently uploaded

一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
lzdvtmy8
 
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
uevausa
 
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
Vietnam Cotton & Spinning Association
 
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
actyx
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
osoyvvf
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
jitskeb
 
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Kaxil Naik
 
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
eudsoh
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Kiwi Creative
 
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
1tyxnjpia
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
bmucuha
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
Timothy Spann
 
Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024
ElizabethGarrettChri
 
Build applications with generative AI on Google Cloud
Build applications with generative AI on Google CloudBuild applications with generative AI on Google Cloud
Build applications with generative AI on Google Cloud
Márton Kodok
 
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
nyvan3
 
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
ytypuem
 
Drownings spike from May to August in children
Drownings spike from May to August in childrenDrownings spike from May to August in children
Drownings spike from May to August in children
Bisnar Chase Personal Injury Attorneys
 
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理 原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
tzu5xla
 
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
eoxhsaa
 
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
z6osjkqvd
 

Recently uploaded (20)

一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
一比一原版格里菲斯大学毕业证(Griffith毕业证书)学历如何办理
 
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
一比一原版加拿大渥太华大学毕业证(uottawa毕业证书)如何办理
 
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
[VCOSA] Monthly Report - Cotton & Yarn Statistics March 2024
 
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
一比一原版斯威本理工大学毕业证(swinburne毕业证)如何办理
 
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
一比一原版(uom毕业证书)曼彻斯特大学毕业证如何办理
 
Experts live - Improving user adoption with AI
Experts live - Improving user adoption with AIExperts live - Improving user adoption with AI
Experts live - Improving user adoption with AI
 
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
Orchestrating the Future: Navigating Today's Data Workflow Challenges with Ai...
 
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
一比一原版马来西亚博特拉大学毕业证(upm毕业证)如何办理
 
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging DataPredictably Improve Your B2B Tech Company's Performance by Leveraging Data
Predictably Improve Your B2B Tech Company's Performance by Leveraging Data
 
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
一比一原版(Sheffield毕业证书)谢菲尔德大学毕业证如何办理
 
一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理一比一原版(UO毕业证)渥太华大学毕业证如何办理
一比一原版(UO毕业证)渥太华大学毕业证如何办理
 
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
06-12-2024-BudapestDataForum-BuildingReal-timePipelineswithFLaNK AIM
 
Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024Open Source Contributions to Postgres: The Basics POSETTE 2024
Open Source Contributions to Postgres: The Basics POSETTE 2024
 
Build applications with generative AI on Google Cloud
Build applications with generative AI on Google CloudBuild applications with generative AI on Google Cloud
Build applications with generative AI on Google Cloud
 
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
一比一原版英国赫特福德大学毕业证(hertfordshire毕业证书)如何办理
 
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
一比一原版(曼大毕业证书)曼尼托巴大学毕业证如何办理
 
Drownings spike from May to August in children
Drownings spike from May to August in childrenDrownings spike from May to August in children
Drownings spike from May to August in children
 
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理 原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
原版一比一爱尔兰都柏林大学毕业证(UCD毕业证书)如何办理
 
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
一比一原版多伦多大学毕业证(UofT毕业证书)学历如何办理
 
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
一比一原版英属哥伦比亚大学毕业证(UBC毕业证书)学历如何办理
 

euclid_linkedup WWW tutorial (Besnik Fetahu)

  • 1. Online Learning and Linked Data Lessons Learned and Best Practices Dataset Profiling 3. April 2014 1Besnik Fetahu
  • 2. LinkedUp: Data Catalog Features  34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)  VoID representations of datasets include the following information:  Manual dataset schema alignments  Accessibility information, i.e. SPARQL endpoint URL 3. April 2014 2Besnik Fetahu http://purl.org/ontology/bibo/Thesis owl:equivalentClass http://purl.org/ontology/bibo/Thesis http://swrc.ontoware.org/ontology#Article owl:equivalentClass http://purl.org/ontology/bibo/AcademicArticle http://data.linkededucation.org/linkedup/dataset/data-open-ac-uk void:sparqlEndpoint http://data.open.ac.uk/queryCo-occurence graph of data types in 146 datasets: 144 Vocabularies, 588 highly overlapping types, 719 Properties Assessing the Educational Linked Data Landscape, D’Aquin, M., Adamou, A., Dietze, S., ACM Web Science 2013 (WebSci2013), Paris, France, May 2013.
  • 3. LinkedUp: Data Catalog Features  34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)  VoID representations of datasets include the following information:  Datasets’ resources type graph  Datasets’ Topic Extraction (Dataset Profiling) 3. April 2014 3Besnik Fetahu morelab OpenCourseWare
  • 4. LinkedUp: Data Catalog Features  34 linked datasets of educational relevance (http://datahub.io/dataset?organization=linked-education)  VoID representations of datasets include the following information:  Federated query interface: 3. April 2014 4Besnik Fetahu PREFIX void: <http://rdfs.org/ns/void#> PREFIX aiiso: <http://purl.org/vocab/aiiso/schema#> SELECT DISTINCT ?endpoint WHERE{ ?ds void:sparqlEndpoint ?endpoint. {{ ?ds void:classPartition [void:class aiiso:School] } UNION {?ds void:subset [void:classPartition [void:class aiiso:School]] }} }
  • 5. LinkedUp: Why dataset profiling? 3. April 2014 5Besnik Fetahu  Few linked dataset characteristics (from Linked Open Data Cloud). Growing number of datasets: 227 datasets Data represented as triples: 31 billion triples Multi-lingual content: 18 languages Broad set of topics covered Inter-dataset links Domain Number of datasets Triples % (Out-)Links % Media 25 1,841,852,061 5.82 % 50,440,705 10.01 % Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 % Government 49 13,315,009,400 42.09 % 19,343,519 3.84 % Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 % Cross-domain 41 4,184,635,715 13.23 % 63,183,065 12.54 % Life sciences 41 3,036,336,004 9.60 % 191,844,090 38.06 % User-generated content 20 134,127,413 0.42 % 3,449,143 0.68 % 295 31,634,213,770 503,998,829 Domains covered by “lod-cloud” datasets
  • 6. LinkedUp: Why dataset profiling? 3. April 2014 6Besnik Fetahu Domain Number of datasets Triples % (Out-)Links % Media 25 1,841,852,061 5.82 % 50,440,705 10.01 % Geographic 31 6,145,532,484 19.43 % 35,812,328 7.11 % Government 49 13,315,009,400 42.09 % 19,343,519 3.84 % Publications 87 2,950,720,693 9.33 % 139,925,218 27.76 % Cross-domain 41 4,184,635,715 13.23 % 63,183,065 12.54 % Life sciences 41 3,036,336,004 9.60 % 191,844,090 38.06 % User-generated content 20 134,127,413 0.42 % 3,449,143 0.68 % 295 31,634,213,770 503,998,829 How do I find information about “renewable energy”? 31 billion resources 18 languages 180 organisations  How can we do that? Check datasets that cover such topic? Use SPARQL filter clause? What are all possible forms of renewable energy? 38 out of 228 datasets contain topic coverage information regex(*) filter clause needs to check all triples that contain a specific keyword renewable energy: solar energy, wind energy, geothermal…...
  • 7. LinkedUp: How to profile Linked Data? 3. April 2014 7Besnik Fetahu  What is a linked data profile? Linked Dataset profiles consist of structured information describing their topic coverage. A profile is represented as a graph. The vertices in the profile graph consist of datasets, resources, and topics. The edges of the profile graph are constructed between the tuples ‹dataset, resources› and ‹resources, topics›. Finally, edges between resources and topics are weighted conveying the relevance of a topic for a dataset. Profile Definition <resource_uri_1> ?predicate_x value <resource_uri_1> ?predicate_y value <resource_uri_1> ?predicate_z value A dataset consists of a set of resource instances. A resource is represented by a set of triples. A topic is equivalent to a DBpedia category, associated to one of the resource values. <resource_uri_1> <resource_uri_2> …… <resource_uri_n>
  • 8. Linked-Up: Profiling Linked Data 3. April 2014 8Besnik Fetahu i. Metadata extraction ii. Sampling of resource instances iii. Entity and topic extraction iv. Topic ranking (PageRank with Priors, HITS with Priors and K-Step Markov) v. Weighted dataset-topic profile graphs vi. Profiles representation A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles. Besnik Fetahu, Stefan Dietze, Bernardo Pereira Nunes, Marco Antonio Casanova, Davide Taibi, and Wolfgang Nejdl. In Proceedings of the 11th Extended Semantic Web Conference, Springer, 2014 (to appear).
  • 9. Profiling Linked Data – (I) 3. April 2014 9Besnik Fetahu i. Metadata extraction:  DataHub’s CKAN API i. Sampling of resource instances  weighted, random, centrality i. Entity and topic extraction  Consider only the textual values assigned to a resource  NER: Disambiguate and extract named entities (DBpedia Spotlight)
  • 10. Profiling Linked Data – (II) 3. April 2014 10Besnik Fetahu i. Topic ranking (PageRank with Priors, HITS with Priors and K-Step Markov)  Rank topics for each dataset, and compute their relevance w.r.t the associated resources i. Weighted dataset-topic profile graph  The computed topic weights for each dataset, represent the weights for the edges <dataset, topic> i. Profiles representation (Vocabulary of Interlinked Datasets (VoID) and Vocabulary of Links (VoL))  VoID: Captures information about a Linked Dataset as a set of links  VoL : Defines a link (of entity or topic type), along with the provenance information and the relevance score of such link
  • 11. Profiling Linked Data: Representation Example 3. April 2014Besnik Fetahu 11 Dataset Profile Metadata Dataset’s Profile and Index Entity Type Link extracted entity extracted topic Provenance information (resources) for the entity link Provenance information (entities) for the topic link Topic Type Link topic relevance score
  • 12. SELECT ?dataset ?link ?score ?link_1 ?entity ?resource WHERE { ?dataset a void:Linkset. ?dataset vol:hasLink ?link. ?link vol:linksResource <http://dbpedia.org/resource/Category:Renewable_energy>. ?link vol:derivedFrom ?entity. ?link vol:hasScore ?score. ?link_1 vol:linksResource ?entity. ?dataset vol:hasLink ?link_1. ?link_1 vol:derivedFrom ?resource } ORDER BY DESC(?score) 3. April 2014Besnik Fetahu 12 How are the profiles useful? • “Renewable Energy” is in different forms: • Solar Energy • Wind-farms • Biogas • Hydroelectricity etc. http://enipedia.tudelft.nl/wiki/Windmar_Renewable_Energy http://enipedia.tudelft.nl/data/page/eGRID/Plant/57050 http://enipedia.tudelft.nl/wiki/Us_Energy_Biogas_Corp http://www.reegle.info/profiles/JP How do I find information about “renewable energy”?
  • 13. Profiling Linked Data: Evaluation 3. April 2014Stefan Dietze 13 Profiling accuracy for the different ranking approaches using the full sample of analysed resource instances, and with NDCG score averaged over all datasets. The correlation between ranking accuracy (averaged over all datasets and for ∆NDCG ) and ranking time.
  • 14. Profiling Linked Data: Example use cases 3. April 2014Besnik Fetahu 14  Type specific views on datasets/ categories  “Document” (foaf:document)  “Person “ (foaf:person)  “Course” (aaiso:course)  LinkedUp Catalog only (as schema mappings already available here)  Exploratory functionalities over the dataset profiles  Available for LinkedUp catalog and the LOD-Cloud.
  • 15. Online Learning and Linked Data Lessons Learned and Best Practices Cite4Me and Linked Challenge 3. April 2014Besnik Fetahu 15
  • 16. Semantic Search and Retrieval of Publications 3. April 2014Besnik Fetahu 16 Semantic Search Graph Search Paper Recommendation In-depth Analysis Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications. Bernardo Pereira Nunes, Besnik Fetahu, Stefan Dietze, and Marco Antonio Casanova. Proceedings of the 12th International Semantic Web Conference, Sydney, Australia, (2013)
  • 17. LinkedUp: Veni Challenge 3. April 2014Besnik Fetahu 17 DataConf. KnowNodes Mismuseos ReCredible YourHistory 3. April 2014 http://www.globe-town.org/ WeShare - 3rd price / people‘s choice GlobeTown - 2nd price http://seek.cloud.gsic.tel.uva.es/weshare/ http://www.polimedia.nl/ PoliMedia – 1st price
  • 18. Demos and Other Resources 3. April 2014Besnik Fetahu 18 Cite4Me: A Semantic Search and Retrieval Web Application for Scientific Publications. Bernardo Pereira Nunes, Besnik Fetahu, Stefan Dietze, and Marco Antonio Casanova. Proceedings of the 12th International Semantic Web Conference, Sydney, Australia, (2013) A Scalable Approach for Efficiently Generating Structured Dataset Topic Profiles. Besnik Fetahu, Stefan Dietze, Bernardo Pereira Nunes, Marco Antonio Casanova, Davide Taibi, and Wolfgang Nejdl. In Proceedings of the 11th Extended Semantic Web Conference, Springer, 2014 (to appear). Assessing the Educational Linked Data Landscape, D’Aquin, M., Adamou, A., Dietze, S., ACM Web Science 2013 (WebSci2013), Paris, France, May 2013.  LinkedUp Catalog: http://data.linkededucation.org/linkedup/catalog/  DevTalk LinkedUp: http://data.linkededucation.org/linkedup/devtalk/  LOD Profile Data: http://data-observatory.org/lod-profiles/sparql  LOD Profile Explorer: http://data-observatory.org/lod-profiles/profile-explorer  Cite4Me Application: http://www.cite4me.com/  LinkedUp Challenge: http://linkedup-challenge.org/