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

prog - The Event Programme Vocabulary
http://purl.org/prog/

This Vocabulary provides the means to create a document which describes a large event or other connected series of events. The primary purpose is to help humans comprehend the programme, not describe absolute truth. A single event (or even series) may have multiple programmes. @en
theatre - Theatre Ontology
http://purl.org/theatre#

An ontology for organising theatrical data. @en
cmo - Conceptual Model Ontology
http://purl.org/twc/ontologies/cmo.owl

An ontology to tie classes and properties to SKOS concepts @en
schema - Schema.org vocabulary
http://schema.org/

Search engines including Bing, Google, Yahoo! and Yandex rely on schema.org markup to improve the display of search results, making it easier for people to find the right web pages. @en
sem - The SEM Ontology
http://semanticweb.cs.vu.nl/2009/11/sem/

The SEM Ontology defines entities that make up the context of an event: Events, Actors, Places, Times. @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
tp - Tourpedia Ontology
http://tour-pedia.org/download/tp.owl

A vocabulary to describe touristic places: accommodations, points of interest, restaurants and attractions. @en
umbel - Upper Mapping and Binding Exchange Layer
http://umbel.org/umbel

UMBEL provides a general vocabulary of classes and predicates for describing domain ontologies, with the specific aim of promoting interoperability with external datasets and domains. @en
drm - Data Reference Model
http://vocab.data.gov/def/drm

A metamodel for government data @en
ceon-processODP - Circular Economy Ontology Network (CEON) - Process ODP
http://w3id.org/CEON/ontology/processODP/

A core ODP of the CEON ontology network, defining aspects of the process concept. @en
ceon-plan - Circular Economy Ontology Network (CEON) - Plan Module
http://w3id.org/CEON/ontology/plan/

The Plan module of CEON (Circular Economy Ontology Network). @en
ceon-process - Circular Economy Ontology Network (CEON) - Process Module
http://w3id.org/CEON/ontology/process/

The Process module of CEON (Circular Economy Ontology Network). @en
bbccore - BBC Core Concepts
http://www.bbc.co.uk/ontologies/coreconcepts

The generic BBC ontology for people, places,events, organisations, themes which represent things that make sense across the BBC. This model is meant to be generic enough, and allow clients (domain experts) link their own concepts @en
crm - CIDOC Conceptual Reference Model
http://www.cidoc-crm.org/cidoc-crm/

This is the encoding approved by CRM-SIG in the meeting 21/11/2012 as the official current version for the CIDOC CRM namespace. Note that this is NOT a definition of the CIDOC CRM, but an encoding derived from the authoritative release of the CIDOC CRM v5.0.4 on http://www.cidoc-crm.org/official_release_cidoc.html @en
sport - BBC Sport Ontology
http://www.bbc.co.uk/ontologies/sport

A simple ontology for representing competitive sports events. @en

123 4

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (58)
property/class >
agent >

Language

English (44)
Italian (9)
Russian (5)
French (4)
German (4)
Portuguese (4)
Greek (3)
Chinese (2)
Dutch (2)
Japanese (2)
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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)