Linked Open Vocabularies

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Terms
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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

200

results

How to

brk - Key Register Cadastre (BRK) vocabulary
http://brk.basisregistraties.overheid.nl/def/brk

Vocabulary for the Dutch key register of the cadastre (BRK) @en
bag - Vocabulary for the Dutch base registration of buildings and addresses (BAG)
http://bag.basisregistraties.overheid.nl/def/bag

Vocabulary for the Dutch key register of buildings and addresses (BAG) @en
brt - Key Register Topography (BRT) vocabulary
http://brt.basisregistraties.overheid.nl/def/top10nl

Vocabulary for the Dutch key register of topography (BRT) @en
geop - FAO Geopolitical Ontology
http://aims.fao.org/aos/geopolitical.owl

FAO's geopolitical ontology version 1.1 was populated with FAO, UN and internationally recognized data sources. @en
dnbt - DNB Metadata Terms
http://d-nb.info/standards/elementset/dnb

The DNB RDF Vocabulary (dnb:) is a collection of classes, properties and datatypes used within the DNB's linked data service.It complements the GND Ontology (gndo:) which is specifically geared towards authority data from the Integrated Authority File (GND), whereas this vocabulary is more general-purpose. @en
cc - Creative Commons Rights Expression Language
http://creativecommons.org/ns

The Creative Commons Rights Expression Language (CC REL) lets you describe copyright licenses in RDF @en
dataid - DataID
http://dataid.dbpedia.org/ns/core#

DBpedia Data ID is an ontology with the goal of describing LOD datasets via RDF files in a uniform way. Established vocabularies like DCAT, VoID, Prov-O and SPARQL Service Description are used for maximum compatibility. @en
lom - Learning Object Metadata Ontology
http://data.opendiscoveryspace.eu/lom_ontology_ods.owl

An ontology and vocabulary used for exposing IEEE LOM, a metadata standard for educational contents, as Linked Data. It is intended as a bridge for linkage of educational metadata into Linked Open Data (LOD). In this ontology, we designed a mapping of IEEE LOM elements to RDF based on Linked Data principles. @en
postcode - Postcode Ontology
http://data.ordnancesurvey.co.uk/ontology/postcode/

An ontology describing the postcode geography in Great Britain. @en
osadm - The administrative geography and civil voting area ontology
http://data.ordnancesurvey.co.uk/ontology/admingeo/

An ontology describing the administrative and voting area geography of Great Britain @en
g50k - 50K Gazetteer Vocabulary
http://data.ordnancesurvey.co.uk/ontology/50kGazetteer/

A vocabulary developed to describe the Ordance Survey 50k Gazetteer linked data @en
ekc - EKC Data Model Vocabulary: Ontology Design for the Encyclopedic Archives of Korean Culture (ekc)
http://dh.aks.ac.kr/ontologies/ekc

The present specification is based on the document \"Ontology:EKC 2022\", originally led by Hyeon Kim in the Center for Digital Humanities at the Academy of Korean Studies. @en
om - ISO 19156 Observation Model
http://def.seegrid.csiro.au/isotc211/iso19156/2011/observation

An OWL representation of the Observation Schema described in clause 6 of ISO 19156:2011 Geographic Information - Observations and Measurements @en
oml - OWL for Observations
http://def.seegrid.csiro.au/ontology/om/om-lite

An OWL representation of the Observation Schema described in clauses 7-8 of ISO 19156:2011 Geographic Information - Observations and Measurements / OGC Abstract Specification - Topic 20. @en
samfl - OWL for Sampling Features
http://def.seegrid.csiro.au/ontology/om/sam-lite

A simple OWL representation of the Sampling Features Schema described in clauses 9-11 of ISO 19156:2011 Geographic Information - Observations and Measurements @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)