1. Semantic Technologies for Linked
Open Data at the STLab
Aldo Gangemi*, Andrea Nuzzolese, Valentina Presutti*, Diego
Reforgiato, Alberto Salvati*,
Eva Blomqvist, Enrico Daga*, Francesco Draicchio, Paolo
Ciancarini°, Sergio Consoli, Silvio Peroni°, Daria Spampinato*
CNR Semantic Technology Lab, ISTC-CNR, Rome/Catania
name.surname@istc.cnr.it ; *name.surname@cnr.it ; °surname@cs.unibo.it
http://stlab.istc.cnr.it
http://wit.istc.cnr.it/stlab-tools
http://data.cnr.it

2. People
• STLab@ISTC
Aldo Gangemi
Valentina Presutti
Daria Spampinato
Andrea Nuzzolese
Diego Reforgiato
Stefania Capotosti
Sergio Consoli
Alessio Iabichella
•
• STLab@SI
Alberto Salvati
Gianluca Troiani
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STLab (Semantic Technology Lab) è un laboratorio dell’ISTC
sco
ance
Fr
(Istituto di Scienze e Tecnologie Cognitive) del CNR, con sedi a
Roma e Catania, attivo anche a Bologna e Parigi
2

3. Outline
• The Linked Open Data (LOD) of CNR
!
• The Semantic Scout
!
• Machine reading for the Semantic Web
!
• Knowledge pattern discovery and usage
3

4. Linked Open Data in Public
Administrations
A practical experience: data.cnr.it and
the Semantic Scout
Joint work by STLab and the Information Systems unit of CNR
Thanks to
Alberto Salvati, Enrico Daga, Gianluca Troiani, Andrea Pompili, Angelo Olivieri
Past collaboration with Claudio Baldassarre (UN-FAO) and Alfio Gliozzo (now IBM-Watson)
4

5. Objective and results
• Objectives
• Publishing CNR data as LOD
• Matching the research demand to the research supply in the largest
research institution (CNR) in Italy
!
• Results
• data.cnr.it
• The CNR ontology network and data available as LOD
• Semantic interoperability between heterogeneous data sources
• The Semantic Scout - http://bit.ly/semanticscout
• Expert finding based on competence
• Monitoring funding and evolution of different research areas and units
• Browsing and reporting capabilities
5

6. data.cnr.it
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7. data.cnr.it
6

8. data.cnr.it
6

9. Methods for data conversion, extraction, inference,
integration, linking, publishing, and searching
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10. Semantic scout
Semantic search
http://bit.ly/semanticscout
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11. Semantic scout
Browsing
http://bit.ly/semanticscout
8

12. Semantic scout
Relation explorer
http://bit.ly/semanticscout
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13. Semantic scout
Exporting exploration results
http://bit.ly/semanticscout
8

14. Semantic scout
Automated reporting
http://bit.ly/semanticscout
8

15. Machine reading for
the Semantic Web

16. Apache Stanbol
• A set of reusable components for semantic content
management
• To extend traditional content management systems with semantic services
accessible as HTTP REST services
• Stanbol is the main software result of the EU IP IKS
!
• Our contribution: the Knowledge Representation and
Reasoning layer of Stanbol
• Services used to define and manipulate semantic data models in CMS, i.e.,
Ontology Network Manager component
• Services able to retrieve additional semantic information about content,
i.e., Reaoners and Rules components
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17. Stanbol in a nutshell
NER and linking to LOD datasets
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18. FRED
E
R
l
fu
ST
http://wit.istc.cnr.it/stlab-tools/fred/
•
The Black Hand might not have decided to barbarously assassinate Franz Ferdinand
after he arrived in Sarajevo on June 28th, 1914
semantic roles
tense
co-reference
events
qualities
negation
modality
dates
NER
sample RDFa annotation
type induction
WSD
taxonomy inductio
The <span xmlns:dbo="http://dbpedia.org/ontology/" xmlns:dbr="http://dbpedia.org/resource/"
about="dbr:Black_Hand_(Serbia)" typeof=”dbo:Agent">Black Hand</span> might not have decided to
barbarously assassinate <span xmlns:schemaorg="http://schema.org/" xmlns:dbr="http://dbpedia.org/
resource/" about="dbr:Archduke_Franz_Ferdinand_of_Austria" typeof=”schemaorg:Person”>Franz Ferdinand</
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span> after he arrived in <span xmlns:schemaorg="http://schema.org/" xmlns:dbr="http://dbpedia.org/
resource/" about="dbr:Sarajevo” typeof=”schemaorg:City”>Sarajevo</span> on June 28th, 1914
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19. Tìpalo
•
Motivation
•
It is difficult to automatically generate enterprise taxonomies from data
available as plain documents
!
•
Objective
•
To enable automatic generate taxonomies by exploiting the richness of natural
language text
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20. Typing DBpedia entities with Tìpalo
“Pakito is the alias of french electronic dance music artist Julien Ranouil”
(cf. wikipedia.org)
Typing
NER
RE
ST
fu
l
Alignment to Dolce
Taxonomy induction
WSD
Alignment to WordNet supersenses
http://wit.istc.cnr.it/stlab-tools/tipalo/
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21. Sentilo
•
Sentilo is a new method of Sentic Computing
•
i.e., Semantic Sentiment Analysis, which is a new research area
!
•
Motivations
•
Sentiment Analysis does not take into account semantic features when
computing opinion scores
•
Semantics can give a lot of information for Sentiment Analysis methods
!
•
Objectives
•
•
To provide Sentiment Analysis methods with Semantic information
To identify more easily and also using semantic information the opinion
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22. ul
f
T
S
Sentilo
E
R
“Robert is happy because
Silvio Berlusconi finally was
condemned by judges”
Sentiment scores
Opinions
Sub topics
Topic
http://wit.istc.cnr.it/stlab-tools/sentilo
Opinion holder
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23. Knowledge pattern discovery

24. Bottom-up: schema extraction
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25. Encyclopedic Knowledge
Patterns
• 184 Encyclopaedic Knowledge Patterns (EKPs) were discovered
by identifying invariances in the structure of Wikipedia page
links
!
• EKPs are represented as OWL2 ontologies
!
• They capture concepts that are typically used by Wikipedia
users for describing things of a certain type
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26. An EKP for OfficeHolder
http://ontologydesignpatterns.org/ekp/
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27. An EKP for OfficeHolder
Formal represenation
http://ontologydesignpatterns.org/ekp/
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28. An EKP for OfficeHolder
Access to data
http://ontologydesignpatterns.org/ekp/
20

29. An EKP for OfficeHolder
Textual grounding
From wikipedia.org
http://ontologydesignpatterns.org/ekp/
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30. Aemoo
• Aemoo exploits EKPs for
• Entity summarisation and Exploratory search
• Distinguishing between core and peculiar knowledge
!
• The data sources are Wikipedia, DBpedia, Twitter, and
GoogleNews
!
• Aemoo is a KP-aware application
• Benefits from KPs for addressing knowledge interaction tasks
• Uses KPs as the basic unit of mean for representing, exchanging, as well as
reasoning with knolwedge
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31. Aemoo UI
http://aemoo.org
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32. Conclusions
• We have provided a practical overview about how to build
Linked Open Data
!
• We have provided case studies and scenarios for exploiting
Linked Data
!
• We have shown Linked Data-compliant algorithms and tools
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33. Thank you!
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