The Open Data Projects of STLab: Digital Libraries, Research Objects, Cultural Heritage, Food, Fishery Products and Smart Cities

The Open Data Projects of STLab:
Digital Libraries, Research Objects,
Cultural Heritage, Food, Fishery
Products and Smart CiBes
A. Gangemi, V. PresuG, L. Asprino, G. Lodi, A. G. Nuzzolese,
D. Reforgiato Recupero, A. Russo
SemanBc Technology Laboratory (STLab) – ISTC-CNR

SemanBc Technology Lab - ISTC CNR
October 2015 STLab Open Data Projects 2
Roma, Catania, Bologna
http://stlab.istc.cnr.it
http://wit.istc.cnr.it/stlab-tools

STLab People
Andrea Nuzzolese
Diego Reforgiato
Silvio Peroni
Misael Mongiovì
Aldo Gangemi
Valentina Presutti
Luigi Asprino
Giorgia Lodi
Alessandro Russo
Martina Sangiovanni

Linked Open Data in 2007...
4 October 2015 STLab Open Data Projects
“Linking Open Data cloud diagram, by Richard Cyganiak and Anja Jentzsch.
http://lod-cloud.net/”

...2008

...2009

...2010

...2011

...2014 (crawlable)

...2014 (potenBal)

SoluBon 1: import
•  Recipes to import data from relaBonal databases
– W3C recommendaBon
– h[p://www.w3.org/TR/r2rml/
•  Pro: no need to change exisBng content
•  Con: error prone, needs human checks

SoluBon 2: extract
•  HTML scraping and natural language processing
(NLP) techniques to extract semanBc
informaBon from exisBng content / sites
– Generic soluBons: OpenCalais, Zemanta, Apache
Stanbol, NERD, FOX, FRED
•  Pro: no need to change exisBng content
•  Con: error prone, needs human checks

SoluBon 3: export
•  RDFa and microformats are used to embed
semanBc informaBon (expressed using the RDF
model) into regular web pages
•  RDFa does it using exisBng (rel) and addiBonal
(about, property, typeof) a[ributes
•  Microformats only use usual HTML a[ributes
(class)

SoluBon 4: reuse
•  Linked Open Data: (usually large) data
repositories available on the web (for free or
not), expressed using the RDF model
•  Interoperability between these repositories
(how to align their ontologies and enBty
names?) is usually parBal

Research
•  Open Knowledge ExtracBon
–  SemanBc Web Machine Reading
–  SemanBc SenBment Analysis
–  Complex RelaBon ExtracBon and RepresentaBon
–  AbstracBve SummarizaBon
•  Similarity reasoning
•  RoboBc natural language understanding
–  IntegraBon of acBon schemas, linked data, and OKE
frames
–  Social pracBces and norms
–  Irony
–  Modality

Development
•  Open Knowledge ExtracBon, ReconciliaBon, Enrichment (Basic research)
•  Design of ontology and data networks (Basic research)
•  Geolinked data: shape files in RDF, use of ontology pa[erns (PRISMA)
•  Geolinked semanBc iBneraries (PRISMA, HERMES)
•  Address ontology pa[erns (S&TDL)
•  ArBcle abstract finding (S&TDL)
•  Automated enBty categorizaBon (S&TDL)
•  Cultural objects ontology (MIBACT)
•  DOP ontology extracBon and design (FOOD)
•  SemanBc mulBlingual nomenclature of fishery products (MARE)
•  Smart chat bots (MARIO)

STLab LOD Cloud

Cultural Heritage: Ontology and Linked
Open Data on Italian cultural insBtutes,
sites and events
Luigi Asprino
STLab – ISTC-CNR
STLab Meetup
October 2015

Context: Cultural InsBtutes or Sites
•  The Italian cultural heritage code deﬁnes as
Cultural insBtute or site (“Luogo della cultura”)
any insBtuBon with responsibility of collecBng,
conserving and exposing artworks
•  Museums
•  Historical archives
•  Libraries
•  Monuments, archeological sites and so on
October 2015 19 STLab Open Data Projects

Context: DB Unico 2.0
•  Registry of Italian cultural inCtutes or sites and cultural
events
•  GeospaBal informaBon, contacts, access informaBon,
organizaBonal informaBon, Bckets, documentaBon
(photos, videos etc.)
•  ParBally available in Open Data: REST service providing
data in XML, license CC-BY 3.0
•  AgID classiﬁed DB Unico 2.0 as high value dataset to be
released in LOD

ObjecBves
Project funded by an agreement between CNR ISTC and Ministero
dei beni e delle aGvità culturali e del turismo (MiBACT)
ObjecBves
•  IntegraCon and raConalisaCon of MiBACT's data
sources related to cultural heritage
•  Deﬁne a model and a reference ontology for
represenBng data on cultural insCtute or sites and
cultural events
•  Release DB Unico 2.0 in Linked Open Data by producing
an RDF dataset aligned with the deﬁned ontology

?
Italian CH LOD cloud
October 2015 22
SAN
ACS
Cultura
Italia
Matera
ICCD
STLab Open Data Projects

Italian CH LOD cloud
October 2015 23
SAN
ACS
Cultura
Italia
Matera
ICCD
Cultural
insBtutes
or sites

Ontology deﬁniBon: methodology
•  The majority of central insBtuBons involved in
cultural heritage managment took part in the
deﬁniBon of the ontology requirements (i.e. ICAR,
ICCU, ICCD, ISCR)
•  Reuse of core ontologies (e.g. DC, Core LocaBon,
Org, FOAF, LODE, Time etc.) and ontology design
pa[erns
•  Reuse of CIDOC-CRM
•  Follow the InternaBonal and Italian guidelines for
semanBc interoperability

Example
October 2015 25
Museo di
Capodimonte
Museo di
Capodimonte
Dr. Mario
Rossi
Director
2011-2016
Exposure:
Vincenzo Gemito
Ticket: 9€
From Nov
28 to Jul 16
Ticket: 15€
1950 ->
Museo di
Capodimonte
Via Miano 2
Napoli
hasAddress
ContactPoint
Museo di
Capodimonte
hasContactPoint
hasCollection
8:30 – 19:00
hasNameInTime
prefLabel
roleFor
withRole
isReferencedBy
involves
takesPlace
During

Data extracBon process and RDF triples producBon
October 2015 26
Qualified
editors
DB
Unico
D2R
Ontology
Mapping
script
Linking

Current status and future works
•  The ontology is currently under-review by all the
central insBtutes of MiBACT and will be
published soon by the Ministry
•  The publicaBon plarorm is ready (Virtuoso,
LODLive)
•  Data cleaning
•  Dataset generaCon
•  Deﬁne a common policy for reusing data in the
Italian cultural heritage cloud

FOod in Open Data (FOOD): Ontologies
and Linked Open Data on Food Quality
CerBﬁcaBon Schemes
Giorgia Lodi
STLab – ISTC-CNR
STLab Meetup
October 2015

Context and ObjecBves
ObjecBves
•  Define and make available standardization models and reference
ontologies for representing data on food quality certification schemes
–  Protected Designation of Origin – in Italian DOP
–  Protected Geographical Indication – in Italian IGP
•  Produce the Linked Open Data (RDF datasets)
–  aligned with the defined ontologies
–  using data extracted from food product specifications published by the
Ministry
•  Make publicly available for re-use the RDF datasets so as to facilitate
the development of applications/services
Project funded by ISTC-CNR (STLab) and Agenzia per l’Italia Digitale
(AgID), and carried out with the collaboration of the Ministry of Agricultural,
Food and Forestry Policies

Where did we start...
274 PDF policy documents for products different from wine
573 PDF policy documents for wine products
+

Example of policy document for wine “Abruzzo”
1.  Type of designaBon
2.  DesignaBon name
3.  Wine typologies
1.  Raw material
2.  Raw material percentage
required to produce the
wine

Example of policy document for a “pasta” product
1.  Type of designaBon
2.  DesignaBon name
1.  Raw material
2.  CharacterisBcs of the
consumer product
1.  ProducBon area

OWL Ontology for Product DesignaBons

Ontologies for each product: wine example

Which data to extract
•  Not all the data included in the policy
documents J
•  Data more oriented to consumers
–  designation
–  product typology
–  raw material and percentage of raw material which
contributes to product composition
–  production area
–  characteristics of the consumer product (for products
different from wines)

Data extracBon process and RDF triples producBon
Scripts
Manual effort
Food product
specifications
Ontologies

PublicaBon – Technical Aspects
•  Persistent URIs
•  Dereferenced URIs
– through LodView
•  SPARQL endpoint
– human readability
– machine-to-machine interacBons
•  Info, download and data access
– h[p://w3id.org/food

Possible future work
•  IntegraBon with other data (vine/grape varieBes)
already made available as relaBonal databases
by the Ministry of Agricultural, Food and
Forestry Policies
•  Extend the ontologies for modelling data of
interest for producers (producBon methods,
logos, etc.)
•  Extract the corresponding data for producing
RDF triples

RDF Data – Turtle: example
prod:vino-abruzzo-bianco upper:haDescrizione draw:vino-abruzzo-bianco-
materia-prima-1,
draw:vino-abruzzo-bianco-materia-prima-2 .
draw:vino-abruzzo-bianco-materia-prima-1 a
upper:DescrizioneMateriaPrima ;
rdfs:label "Vitigno 'Trebbiano Abruzzese', Vitigno 'Trebbiano Toscano':
minimo (>=) 50%" ;
upper:haMateriaPrima raw:vitigno-trebbiano-abruzzese,
raw:vitigno-trebbiano-toscano ;
upper:haValoreMinimo "50%" .
draw:vino-abruzzo-bianco-materia-prima-2 a
upper:DescrizioneMateriaPrima ;
rdfs:label "Vitigno 'Altre Varietà A Bacca Bianca': massimo (<=) 50%" ;
upper:haMateriaPrima raw:vitigno-altre-varieta-a-bacca-bianca ;
upper:haValoreMassimo "50%" .

MARE: A Single InformaBon System for
Fishery and Aquaculture Products
Marketed in the EU
Alessandro Russo
STLab – ISTC-CNR
STLab Meetup
October 2015

Context and ObjecBves
•  Conceived by the Directorate-General for MariBme Affairs and
Fisheries (DG MARE) of the European Commission
–  call for tender issued in the general context of the reformed
Common Fisheries Policy (CFP) and Common OrganisaBon of the
Markets (CMO) in fishery and aquaculture products
•  ObjecBve: establishment of an informaCon system able to
manage all informaBon related to commercial designa0ons of
fisheries and aquaculture products marketed in the European
Union
•  Target: all actors and stakeholders of the fishery supply chain
–  strengthen the informaBon available to European consumers
–  saBsfy different informaBonal needs of fishmongers, producers,
processors, importers, retailers, control authoriBes, etc.
•  Partners: STLab - R2M SoluBon - Università di Catania

EU Labelling Requirements
Source: © EC - A pocket guide to the EU’s new fish and aquaculture consumer labels
Transparency and accuracy of labelling of fisheries and aquaculture products
Great! But…where do I find all the related information?

From Sca[ered Data and InformaBon Sources...
Commercial Designations lists
of the EU Member States
Yearly published EU
TACs and quotas
Scientific names
and taxonomic
classifications
…
FAO
Fishing Areas

...to a Single InformaBon System!

Data Complexity and Challenges
•  Bring together heterogeneous data and interact with mulBple
informaBon sources
–  different informaBon content
•  commercial designaBons, scienBfic names, producBon methods, fishing
areas and gears, markeBng standards, pictograms, distribuBon maps, ect.
–  different data sources
•  commercial designaBons lists published by naBonal authoriBes, taxonomic
systems, species factsheets, FAO classificaBon schemes, EU RegulaBons,
etc.
–  different data formats and gathering modaliBes
•  from database records accessible through Web services (e.g., taxonomic
systems) to unstructured text human-readable only (e.g., EU RegulaBons)
•  XML/JSON/CSV data, spreadsheets, HTML Web resources, PDF and text
documents, etc.
•  Deal with exisBng informaBon at local/regional, naBonal and
internaBonal levels, combined with mulBlingual perspecBve
–  28 EU Member States and 24 official languages

InformaBon Model and Data Sources

Ontology DefiniBon Methodology
FAO ontologies (cf.
also NeOn project),
iMarine ontology,
Darwin core, etc.
Hierarchical data
(partOf) and
taxonomies, Bme-
indexed situaBons,
literal reificaBon etc.
Reusable modules:
scienBfic and taxonomic data
(Mare Taxa), commercial and
legal requirements (Mare),
georgraphical data (Mare Geo)
Enable semanBc
interoperability
through alignments to
external authoritaBve
ontologies (FAO, Dublin
core, Darwin core, etc.)
State of the art analysis, ontology design patterns adoption, modularization and
external alignments to produce open, interoperable and reusable models and data

Datasets ProducBon Process
From relaBonal data to RDF
datasets aligned with the
MARE ontology modules via
D2RQ scripts
RDF graphs with materializaBon of
both the core elements of the Mare
ontologies and the alignments to
external ontologies
DeﬁniBon and
materializaBon of links to
other exisBng linked data in
the Web of data

Current Status and Future Work
•  InformaBon system available as a fully operaBonal
mulBlingual prototype
–  more than 86 000 scienBﬁc names (about 38 000 valid
names) an more than 15 000 diﬀerent commercial
designaBons
–  24 EU languages
–  project results currently under review by DG MARE
•  Possible long-term operaBonalizaBon of the system
•  OWL ontologies, RDF linked datasets and a SPARQL
endpoint for data access will be available soon

Linked Data for Smart CiBes:
the case of Catania
ValenBna PresuG
Diego Reforgiato Recupero
STLab – ISTC-CNR
STLab Meetup
October 2015

Project goal and context
•  PON project “Pia[afoRme cloud Interoperabili per SMArt-
government” (PRISMA)
•  CiBes, industry, ciBzens and ICT together for improving urban life ->
smart ciBes
•  ExperimenBng social eGovernment systems for supporBng the
Municipality of Catania (MoC)
•  Envisioned results:
–  intelligent ICT services
–  ciBzens-based evaluaBon of the city administraBon
–  conceiving, designing and prototyping smart applicaBons for the MoC
•  Linked open data are an important part of this picture…

Architectural Model

Linked Open Data for Catania: Data sources
Geographic InformaBon System of the MoC
Data on lines and stops of the public bus
transportaBon system
Maintenance of the public lighBng system of the
city
Maintenance of roads, sidewalks, signs and
markings
Historical data on municipal waste collecBon
Historical data on the urban fault reporBng
service


city
markings
service

•  Geo-referenced places of provincia di
Catania
•  For each record a shape file
•  Road graphs, gas network, road signs and
markings, etc.

city
markings
service

Geo-referenced bus lines
trajectories and stops

city
markings
service

Fault messages, the state of
faults and the life-cycle of
faults

city
markings
service

Services for the collecBon of
municipal waste and disposal
of large-size garbage

city
markings
service

Reports, acBons required,
status, workﬂows, geo-
localisaBon, addresses, etc.

Linked Open Data for Catania: Methodology
EnCty Linking
GIS
Public transport
Public lighiting
system
Roads
maintenance
Municipal waste
Fault reporting
TABELS
D2RQ
JAVA
JAVA
D2RQ
D2RQ
PRISMA
ontology and linked data
CollecCon
Ontology
NeoGeo
OrganizaCon
Ontology
WGS84
Ontology Design
Pa[erns
manual effort

GIS of provincia di Catania
Tables
http://idi.fundacionctic.org/tabels/
Refactoring by
SPARQL constructs
Keyhole
Markup
Language
Mapping to existing vocabularies (NeoGeo, Collections Ontology, WGS84)

Example of KML data visualised on Google Maps

Modeling urban public transportaBon
Ordered spatial composition
ontology pattern
Specialisation
in PRISMA ontology

Modeling urban public transportaBon
Time table
ontology pattern
Specialisation in PRISMA ontology

Modeling maintenance of the lighBng system
opened
ongoing
completed

Modeling urban fault reporBng service

Online resources
•  PRISMA ontology
•  h[p://www.ontologydesignpa[erns.org/ont/prisma/ontology.owl
•  SPARQL endpoint
• h[p://wit.istc.cnr.it:8894/sparql
• Select <prisma-ont> and <prisma>
•  Endpoint also accessible as REST web service
•  PRISMA web portal demo:
• h[p://wit.istc.cnr.it/prisma/WebContent/home.html

WebVOWL visualisaBon

LodView visualisaBon

LodLive visualisaBon

Andrea Giovanni Nuzzolese
STLab – ISTC-CNR
STLab Meetup
October 2015

Context and Objectives
• Project funded by CNR and Agenzia per l’Italia Digitale (AgID), and carried
out with the collaboration of the Ministry of Instruction, Research, and
University (MIUR)
• Objectives
• designing and implementing a Digital Library (DL) for spreading of science
and technologies
• exploiting Semantic Technologies for publishing the Linked Open Data
(LOD) of the DL
• Result
• LOD dataset
• counting of ~8.4M RDF triples modelled by using an Ontology Design
Pattern (ODP) based methodology
• describing ~150K bibliographic resources
• linked to DBpedia, data.cnr, and Geonames
20/10/2015 STLab Open Data Projects - Rome Meetup 2

DL Data
• The DL organises heterogeneous
contents
• e.g., research products, datasets, data about
research activities, projects, researchers and
expertise, digitised content of historical and
cultural interest
• coming from different organisations

5
Producing LOD: problems
Where do they come from?

5
Who is the ﬁrst author?

5
What is this?
Who is the ﬁrst author?

6
Affiliations and roles
Time Indexed Person Role ODP

7
Authors ordering
Sequence ODP

8
FRBR
Functional Requirements for Bibliographic Records

9
Ongoing work
• Integration of more data sources
• More data linking (e.g., DBLP, Semantic Publishing
LOD, ACS, etc.)
• Publishing of data.stdl.cnr.it (still some policy
issues)
• More sophisticated identity resolution (e.g.,
homonyms detection)
• Integration of visual paradigms for Linked Data
exploration

Andrea Giovanni Nuzzolese
STLab – ISTC-CNR
STLab Meetup
October 2015
The Linked Open Data
plarorm of CNR: data.cnr.it

Context and Objectives
• Joint work by STLab and the Information
Systems unit of CNR
• Objective
• providing a Open Data platform to enable
public access to the information of the CNR
organization

4
The Ontology Network
ODP-based design

6
Semantic Scout
Semanticsearch

6
Semantic Scout
Relationexplorer

6
Semantic Scout
Exportingexplorationresults

6
Semantic Scout
Automatedreporting

Results
• data.cnr.it
• the CNR Ontology Network and data
available as LOD
• counting of ~8.2M RDF triples
• linked to DBpedia and Geonames
• The Semantic Scout
• expert finding based on competence
• monitoring funding and evolution of
different research areas and units
• browsing and reporting capabilities
http://data.cnr.it
http://goo.gl/MFlStF

8
• More data linking (e.g. DBLP)
• Automatic synchronisation with or virtual RDF
access to data sources
• More visual paradigms
Ongoing work

9
Grazie
andrea.nuzzolese@istc.cnr.it

The Open Data Projects of STLab: Digital Libraries, Research Objects, Cultural Heritage, Food, Fishery Products and Smart Cities

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