Linked Open Vocabularies

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SPARQL/Dump
Patterns

How to

Select the ontologies from which you want to extract patterns.

Select patterns options:

Name, Type or both:

Name: Ontology elements in the patterns represent specific classes and properties names.

For example:

# INPUT
s4bldg:BuildingSpace rdfs:subClassOf [
  rdf:type owl:Restriction ;
  owl:onProperty s4bldg:isSpaceOf ;
  owl:allValuesFrom [
    rdf:type owl:Class ;
    owl:unionOf (
      s4bldg:Building
      s4bldg:BuildingSpace
    )
  ]
]

# OUTPUT
Pattern 16
owl:Class
|rdfs:subClassOf
| |owl:Restriction
| | |owl:allValuesFrom
| | | |owl:Class
| | | | |owl:unionOf
| | | | | |rdf:List
| | | | | | |rdf:first
| | | | | | | |owl:Class
| | | | | | |rdf:rest
| | | | | | | |rdf:List
| | | | | | | | |rdf:first
| | | | | | | | | |owl:Class
| | | | | | | | |rdf:rest
| | | | | | | | | |rdf:nil
| | |owl:onProperty

# INPUT
s4bldg:BuildingSpace rdfs:subClassOf [
  rdf:type owl:Restriction ;
  owl:onProperty s4bldg:isSpaceOf ;
  owl:allValuesFrom [
    rdf:type owl:Class ;
    owl:unionOf (
      s4bldg:Building
      s4bldg:BuildingSpace
    )
  ]
]

# OUTPUT
Pattern 16
owl:Class
|rdfs:subClassOf
| |owl:Restriction
| | |owl:allValuesFrom
| | | |owl:Class
| | | | |owl:unionOf
| | |owl:onProperty

Type: Ontology elements in the patterns are generalized according to the OWL elements used.

No specific classes or properties are used, but OWL skeletons like:

owl:Class
  |rdfs:subClassOf
  |  |owl:Restriction
  |  |  |owl:onProperty
  |  |  |  |owl:DatatypeProperty, owl:FunctionalProperty
  |  |  |owl:someValuesFrom
  |  |  |  |rdfs:Datatype

Flatten or not:
1. Flatten: If there are collections of classes or individuals in the pattern, the full collection is not included.
  ¿SERGIO esto aplica a los named? O solo a los que se generalizan como Type?
  
  Otra cosa es que estaría bien indicar algunos ejemplos, pensaba que se incluían 3.
```
owl:Class
  |owl:equivalentClass
  |  |owl:Class
  |  |  |owl:oneOf
```

Output: Tengo que ver el output final y definir esto en detalle

The retrieved .zip file contains the following folders and documents:

“Data” folder. This folder contains the files:
- A
- B
- C
“flatten” folder (if selected): This folder contains the files:
- A
- B
- C
“not_flatten” folder (if selected): This folder contains the files:
- A
- B
- C
HTML folder. This folder contains the files:
- A
- B
- C

131

results

How to

hpo - Hyperdimensional Polymer Ontology
http://w3id.org/emmo-hpo/hpo

An ontology to capture the staggering diversity of polymeric materials and their applications. @en
dstv - DSTV:Steel Construction Ontology
http://w3id.org/dstv

DSTV ontology @en
cbcm - The European Union Company Mobility Ontology (EUCM ontology)
http://w3id.org/um/cbcm/eu-cm-ontology

This ontology describes terms concerning companies, their cross-border movements within the European Union (EU), and associated EU company legislation. @en
akt - AKT Reference Ontology
http://www.aktors.org/ontology/portal

The AKT Reference Ontology has been designed to support the AKT-2 demonstrator ("AKTive Portal"), and subsequent activities. The ontology, designed by the AKT-2 group and codified by Enrico Motta, extends Version 1. @en
dk - The Data Knowledge Vocabulary
http://www.data-knowledge.org/dk/

The Data Knowledge Vocabulary allows for a comprehensive description of data assets and enterprise data management. It covers a business data dictionary, data quality management, data governance, the technical infrastructure and many other aspects of enterprise data management. The vocabulary represents a linked data implementation of the Data Knowledge Model which resulted from extensive applied research. @en
km4c - km4city, the DISIT Knowledge Model for City and Mobility
http://www.disit.org/km4city/schema

A Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
ivoam - Messengers
http://www.ivoa.net/rdf/messenger

A vocabulary of particles used for observations in astronomy. This list started its existence as the controlled vocabulary for VODataService's vs:Waveband type; the machine-readable identifiers are in upper case for backwards compatibility. @en
ceo - Consumer Electronics Ontology
http://www.ebusiness-unibw.org/ontologies/consumerelectronics/v1

An Ontology for Consumer Electronics Products and Services @en
traffic - Road Traffic Management
http://www.sensormeasurement.appspot.com/ont/transport/traffic

An ontology that describes the management of the traffic in a straight road with two lanes, both in the same direction. @en
vin - Wine Ontology
http://www.w3.org/TR/2003/PR-owl-guide-20031209/wine

This ontology was used as example in the first OWL Recommendation (February 2004) @en
fowl - Food Ontology in OWL
http://www.w3.org/TR/2003/PR-owl-guide-20031215/food

Along with Wine Ontology, was used as example in the first OWL Recommendation (February 2004) @en
duv - Dataset Usage Vocabulary
http://www.w3.org/ns/duv

The Dataset Usage Vocabulary (DUV) is used to describe consumer experiences, citations, and feedback about datasets from the human perspective. @en
rov - Registered Organization Vocabulary
http://www.w3.org/ns/regorg

The Registered Organization Vocabulary is a profile of the Organization Ontology for describing organizations that have gained legal entity status through a formal registration process, typically in a national or regional register. @en
rma - Verisav RMA / Ticketing Vocabulary
https://ns.verisav.fr/rma#

Vocabulary for Return Merchandise Authorization (RMA) and service ticket management, standardizing communication between consumers, retailers, and repairers. @en
dpp - Verisav Digital Product Passport Vocabulary
https://ns.verisav.fr/dpp#

Vocabulary for Digital Product Passports (DPP) managing product lifecycle, warranties, repairs, and compliance with EU regulations (ESPR EU 2024/1781). Aligned with GS1 Digital Link standards, including GTIN, GLN, granularity (model/batch/serial) and compound identifier support. @en

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Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

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Este trabajo ha recibido financiación del proyecto PIONERA (Potenciando la interoperabilidad en espacios de datos mediante inteligencia artificial), un proyecto financiado en el contexto de la convocatoria Productos y Servicios tecnológicos para Espacio de Datos del Ministerio para la Transformación Digital y de la Función Pública en el marco del PRTR financiado por Unión Europea (NextGenerationEU)