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

results

How to

cart - cartCoordOnt
http://purl.org/net/cartCoord#

Ontology for representation of cartesian co-ordinates @en
tsn - Territorial Statistical Nomenclature Ontology
http://purl.org/net/tsn#

This RDF ontology allows describing any Territorial Statistical Nomenclature (TSN) (i.e., partition of the territory) used as a support to socio-economic data (statistical data that describe territory in terms of population, unemployement rate, transport access, etc.). @en
step - Semantic Trajectory Episodes
http://purl.org/net/step

A lightweight ontology for representing semantic trajectories and contextual elements in terms of features of interests and episodes. @en
place - The Places Ontology
http://purl.org/ontology/places

The Places Ontology is a simple lightweight ontology for describing places of geographic interest. @en
posocm - Positioning System Ontology Common Technologies, Algorithms and Systems
http://purl.org/poso/common/

This ontology provides the terminologies used for positioning systems. @en
poso - Positioning System Ontology
http://purl.org/poso/

This ontology provides the terminologies used for positioning systems. @en
igeo - French Statistical ontology for geolocation
http://rdf.insee.fr/def/geo

Ontology describing geographic entities as seen by the French Statistical Institute @en
juso - Juso Ontology
http://rdfs.co/juso/

Juso Ontology is a Web vocabulary for describing geographical addresses and features. @en
juso.kr - South Korea Extension to Juso Ontology
http://rdfs.co/juso/kr/

South Korea Extension to Juso Ontology is a Web vocabulary that extends Juso Ontology to describe geographical addresses and features in South Korea. @en
isoadr - ISO19160-1:2015 Address ontology
http://reference.data.gov.au/def/ont/iso19160-1-address

This ontology is a version of the ISO TC211, Group for Ontology Management (GOM)'s OWL ontology interpretation of the ISO19160-1:2015 "Addressing -- Part 1: Conceptual model" standard (see https://www.iso.org/standard/61710.html) taken from that ontology's source code, published at https://github.com/ISO-TC211/GOM/tree/master/isotc211_GOM_harmonizedOntology/19160-1/2015. @en
dave - Data Value Vocabulary (DaVe)
http://theme-e.adaptcentre.ie/dave/dave.ttl

The Data Value Vocabulary (DaVe) is an extensible core vocabulary that allows user to use custom data value dimensions and metrics to characterise data value in a specific context. This flexibility allows for the comprehensive modelling of data value. As a data value model, DaVe allows users to monitor data value as it occurs within a data exploitation or value creation process (data value chain) @en
frappe - FraPPE: Frame, Pixel, Place, Event vocabulary
http://streamreasoning.org/ontologies/frappe#

FraPPE is a vocabulary to enable Visual Analytics operations on geo-spatial time varying data. By enabling Visual Analytics instruments FraPPE ease the capture, correlation and comparison operations on geo-spatial data from different sources evolving over time @en
rooms - Buildings and Rooms Vocabulary
http://vocab.deri.ie/rooms

A simple vocabulary for describing the rooms in a building. @en
geod - Administrative vocabulary for Norway
http://vocab.lenka.no/geo-deling

Vocabulary describing the administrative subdivision of Norway @en
arp - Arpenteur Ontology
http://www.arpenteur.org/ontology/Arpenteur.owl

Arpenteur ontology is dedicated to photogrammetry, archeology and oceanology communities in order to perform tasks such as image processing, photogrammetry and modelling. @en

1 234 5

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (64)
property/class >
agent >

Language

English (43)
French (12)
Dutch (5)
Chinese (4)
German (4)
Russian (4)
Spanish (4)
Italian (3)
Korean (3)
Portuguese (3)
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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)