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

152

results

How to

ceo - Consumer Electronics Ontology
http://www.ebusiness-unibw.org/ontologies/consumerelectronics/v1

An Ontology for Consumer Electronics Products and Services @en
oum - Ontology of units of Measure (OM)
http://www.ontology-of-units-of-measure.org/resource/om-2/

The Ontology of units of Measure (OM) 2.0 models concepts and relations important to scientific research. It has a strong focus on units, quantities, measurements, and dimensions. @en
moac - Management of a Crisis Vocabulary
http://www.observedchange.com/moac/ns#

MOAC, the Management of a Crisis Vocabulary, is a lightweight vocabulary aiming to provide terms to enable practitioners to relate different "things" in crisis management activities together as Linked Data. The initial MOAC terms originated from the Inter Agency Standing Committee (IASC), Emergency Shelter Cluster in Haiti, UNOCHA 3W Who What Where Contact Database @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
ssn - Semantic Sensor Network Ontology
http://www.w3.org/ns/ssn/

This ontology describes sensors, actuators and observations, and related concepts. It does not describe domain concepts, time, locations, etc. these are intended to be included from other ontologies via OWL imports. @en
uiot - Urban IoT Ontologies - Core Module
http://www.w3id.org/urban-iot/core

Core module of the suite of ontologies for urban IoT devices. @en
uiote - Urban IoT Ontologies - Electric Mobility Module
http://www.w3id.org/urban-iot/electric

Electric Mobility module of the suite of ontologies for urban IoT devices. @en
sosa - Sensor, Observation, Sample, and Actuator (SOSA) Ontology
http://www.w3.org/ns/sosa/

This ontology is based on the SSN Ontology by the W3C Semantic Sensor Networks Incubator Group (SSN-XG), together with considerations from the W3C/OGC Spatial Data on the Web Working Group. @en
caso - Context Aware System Observation Ontology
http://www.w3id.org/def/caso#

CASO (Context Aware System Observation) is an ontology for context aware system and observation services. Its goal is to describe all the processing of the context. @en
atts - Air Traffic Temporal and Spacial Vocabulary
https://data.nasa.gov/ontologies/atmonto/general#

Defines temporal / spatial concepts and general-purpose datastructures @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
tresiot - Ontology for Trust Recommendation in Social Internet of Things
https://liidr.org/trust-recommendation-in-social-internet-of-things/

This ontology models trust recommendation concepts in SIoT to bridge the gap between abstract trust concepts and real-world device concepts. @en
eqp - Aircraft Equipment Vocabulary
https://data.nasa.gov/ontologies/atmonto/equipment#

Defines aircraft models, aircraft systems / subsystems, and aircraft characteristics @en
atd - Air Traffic Data
https://data.nasa.gov/ontologies/atmonto/data#

Defines concepts related to airport status, including weather, forecasts, and airport operations @en

1...3 456 7...11

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)