The document discusses how semantic web technologies like ontologies, linked open data, and knowledge graphs can benefit cultural heritage applications. It provides ArCo, an Italian cultural heritage knowledge graph, as an example. ArCo converts Italian cultural property catalog records from XML to RDF, and uses ontologies to represent cultural heritage concepts and logically connect data from different sources. This enriches data and improves interoperability. The document outlines how ArCo can be explored through its SPARQL endpoint, visualizations, and other tools.
Human Factors of XR: Using Human Factors to Design XR Systems
Semantic Web for Cultural Heritage valorisation
1. Semantic Web for Cultural
Heritage valorisation
ArCo: a virtuous example
Valentina Anita Carriero
PhD student @ DISI, University of Bologna
valentina.carriero3@unibo.it
twitter: @vale_carriero
2. Semantic web in the CH domain
Semantic technologies,
Linked Open Data,
and ontologies
are being widely and successfully exploited within the
cultural heritage field
2
4. Semantic web
The Semantic Web is an extension of the current web in
which information is given well-defined meaning, better
enabling computers and people to work in cooperation.
[Berners-Lee et al., 2001]
4
machine-readable
data
5. Linked Data / knowledge graphs
Structured data interlinked with other data
5
knowledge is formally
represented by schemas
defining categories of concepts
(classes) and relations between
concepts
ontologies are
formal descriptions of domain models
a type of
knowledge base
using a graph
structure
node
edge
6. standards
RDF OWL SPARQL …
6
Triple-based data model
set of 3 entities representing
a statement about data in the form
subject‒predicate‒object
World Wide Web Consortium
International community developing open standards for the Web
7. Semantic triples
7
Moscow
place of birth
Fyodor
Dostoyevsky
Triple-based data model
set of 3 entities representing
a statement about data in the form
subject‒predicate‒object
«Fyodor Dostoyevky
was born in Moscow»
8. 8
Fyodor
Dostoyevsky
place of birth
Moscow
place of birth
Human City
Triple-based data model
set of 3 entities representing
a statement about data in the form
subject‒predicate‒object
Semantic triples
instance of
9. 9
place of birth
Moscow
place of birth
Human City
every part of an RDF triple is
individually addressable via
unique URIs https://www.wikidata.org
/entity/Q991
Fyodor
Dostoyevsky
https://www.wikidata
.org/entity/Q649
https://www.wikidata.org
/entity/Q7930989
https://www.wikidata
.org/entity/Q5
sequence of characters for
uniquely identifying resource
of the web
e.g.
Unique identifiers
https://www.
wikidata.org/
entity/P19
https://www.
wikidata.org/
entity/P31
instance of
10. Linked Open Data
10
1255 datasets
with 16174 links
(as of May 2020)
https://lod-cloud.net/
Linked data can be open
Linked Data Cloud
knowledge graph
connecting open RDF
datasets
12. Cultural heritage mission
Museums, libraries, archives, private collections, other
cultural institutions
to preserve the cultural objects they collect
12
GOAL
HOW by describing these objects
through data
that keeps memory of them,
their life cycle, their artistic,
social, and historical context
13. Cultural heritage mission
Museums, libraries, archives, private collections, other
cultural institutions
to preserve the cultural objects they collect
13
GOAL
HOW by describing these objects
through data
that keeps memory of them,
their life cycle, their artistic,
social, and historical context
if data is shared, it can
be used as a means of
enhancing cultural
properties
14. Cultural heritage data as silos
CH data is still often managed separately like silos,
by different organisations
with various classifications and definitions
to describe the same concepts
14
dispersed
not interoperable
not easily accessible
15. Cultural heritage data as networks
By using semantic technologies,
CH data is represented by ontologies,
and data from different sources
is interconnected in knowledge graphs
15
linked
interoperable
accessible
16. Cultural heritage data as networks
By using semantic technologies,
CH data is represented by ontologies,
and data from different sources
is interconnected in knowledge graphs
16
vast
interconnected
open
digital
cultural heritage
ontologies and
LOD empower
the cultural
heritage field
18. Italian cultural heritage
18
ICCD (MiC) coordinates
cataloguing activities and CH
data management
cataloguing standards,
controlled lists
catalogue records
30 types of cultural
properties
General Catalogue
of Italian CH
Catalogo Generale
dei Beni Culturali
21. From XML to RDF
21
ONTOLOGIES
KNOWLEDGE
GRAPH
DATA
eXtreme Design
methodology
22. Why Linked Open Data? (1)
22
Ontologies clearly define the semantics of the
concepts of a domain
not only names and textual comments
but also logical axioms
23. Example from ArCo (1)
23
:ComplexCulturalProperty
owl:equivalentClass
[rdf:type owl:Restriction ;
owl:onProperty :hasCulturalPropertyComponent ;
owl:someValuesFrom :CulturalPropertyComponent ].
«A complex cultural property must have some
cultural property components.»
24. 24
Reasoning about the facts stored in a knowledge base
using rules and other forms of logic
to deduce new facts
or highlight inconsistencies
Why Linked Open Data? (2)
26. Example from ArCo (2)
26
rdf:type
:ComplexCulturalProperty
THEN:
Cultural Property
Component Y
:hasCulturalProperty
Component
Cultural
Property X
:ComplexCulturalProperty owl:equivalentClass
[rdf:type owl:Restriction ;
owl:onProperty :hasCulturalPropertyComponent ;
owl:someValuesFrom :CulturalPropertyComponent
].
27. Why Linked Open Data? (3)
27
Ontologies often allow for more expressiveness
29. Why Linked Open Data? (4)
29
If different datasets use the same ontology,
or different ontologies properly aligned,
interoperability between datasets is guaranteed
30. Example from ArCo (4)
30
rdfs:subClassOf
a-cd:Title crm:E35_Title
alignment
31. Why Linked Open Data? (5)
31
Identity links between the resources of different datasets
can mutually enrich the datasets
32. Example from ArCo (5)
32
wd:Q762
owl:sameAs
a-res:Agent/
2481e14c9522a1d40
6369514e9e9e316
Leonardo Da Vinci Leonardo Da Vinci
a-cd:isAuthorOf
studi e annotazioni di meccanica
a-res:HistoricOr
ArtisticProperty/
0500446151A
wd:Q3739104
natural causes
wd:P1196
manner of death
33. Why Linked Open Data? (6)
33
Linked Open Data support reuse of data from different
actors
e.g. tourism, researchers, private companies, public
administrations, scholars, …
34. Example from ArCo (6.1)
34
Support to archaeological research methodologies
by integrating ArCo data on the creation of the
archaeological site
with data on earthquakes from external databases
for answering research questions such as
«When was an archaeological site built, inhabited, and
stopped being one?»
35. Example from ArCo (6.2)
35
For this reason, ArCo adopts an open gathering of
requirements
• Extended customer team (not only ICCD)
• Early Adoption Program
43. References
43
Tim Berners-Lee, James Hendler, Ora Lassila. The semantic web. Scientific American. 2001 May 1; 284(5): 34-43.
Eva Blomqvist, Valentina Presutti, Enrico Daga, Aldo Gangemi: Experimenting with eXtreme Design. EKAW 2010: 120-
134
Valentina Anita Carriero, Aldo Gangemi, Maria Letizia Mancinelli, Andrea Giovanni Nuzzolese, Valentina Presutti, Chiara
Veninata: Pattern-based design applied to cultural heritage knowledge graphs. Semantic Web, Volume 12(2), 2021.
Special Issue on Semantic Web for Cultural Heritage
Valentina Anita Carriero, Aldo Gangemi, Maria Letizia Mancinelli, Ludovica Marinucci, Andrea Giovanni
Nuzzolese, Valentina Presutti, Chiara Veninata: ArCo: The Italian Cultural Heritage Knowledge Graph. ISWC
(2) 2019: 36-52
Valentina Anita Carriero, Aldo Gangemi, Andrea Giovanni Nuzzolese, Valentina Presutti:
An Ontology Design Pattern for Representing Recurrent Events. WOP@ISWC 2019: 59-70
Giorgia Lodi, Luigi Asprino, Andrea Giovanni Nuzzolese, Valentina Presutti, Aldo Gangemi, Diego Reforgiato Recupero,
Chiara Veninata, Annarita Orsini: Semantic web for cultural heritage valorisation. Data Analytics in Digital Humanities
2017. 3-37