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

110

results

How to

qb - The data cube vocabulary
http://purl.org/linked-data/cube

This vocabulary allows multi-dimensional data, such as statistics, to be published in RDF. @en
wf-invoc - Workflow Invocation Ontology
http://purl.org/net/wf-invocation

Wf-invoc is a simple profile of the P-plan ontology to describe how workflow steps are invoked within a workflow execution. @en
wfm - The Workflow Motif Ontology
http://purl.org/net/wf-motifs

Ontology for describing Workflow Motifs. Workflow Motifs outline the kinds of data-intensive activities that are observed in workflows (data-operation motifs) and the different manners in which activities are implemented within workflows (workflow-oriented motifs). @en
p-plan - The P-PLAN Ontology
http://purl.org/net/p-plan#

The Ontology for Provenance and Plans (P-Plan) is an extension of the PROV-O ontology [PROV-O] created to represent the plans that guided the execution of scientific processes. P-Plan describes how the plans are composed and their correspondence to provenance records that describe the execution itself. @en
co - Counter Ontology
http://purl.org/ontology/co/core#

The Counter Ontology specification provides basic concepts and properties for describing a general counter concept and some important sub counters @en
stories - Stories Ontology
http://purl.org/ontology/stories/

The Stories ontology was developed in collaboration with the BBC, with an aim to creating an ontology for narrative representation that could be applied across a diverse set of cases. These included accounts of events in Northern Ireland, the storylines of Doctor Who episodes, and key events of the Battle of Britain. @en
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
reco - RECommendations Ontology
http://purl.org/reco#

The RECO ontology defines the vocabulary for representing preferences-as-constraints and preferences-as-ratings as RDF graphs. This lightweight vocabulary provides domain-independent means to describe user profiles in a coherent and context-aware way. RECO has been designed as an extension of both Friend-Of-A-Friend (FOAF) and Who Am I! (WAI) ontologies. @en
wo - Weighting Ontology
http://purl.org/ontology/wo/core#

The Weighting Ontology specification provides a vocabulary for describing weightings and their referenced scales, on/ for the Semantic Web. @en
theatre - Theatre Ontology
http://purl.org/theatre#

An ontology for organising theatrical data. @en
sou - QUDT VOCAB Systems of Units Release 2.1.34
http://qudt.org/2.1/vocab/sou

QUDT VOCAB Systems of Units Release 2.1.34 @en
qudt - Quantities, Units, Dimensions and Types
http://qudt.org/schema/qudt

The QUDT, or 'Quantity, Unit, Dimension and Type' collection of ontologies define the base classes properties, and restrictions used for modeling physical quantities, units of measure, and their dimensions in various measurement systems. @en
disco - DDI-RDF Discovery Vocabulary
http://rdf-vocabulary.ddialliance.org/discovery

A metadata vocabulary for documenting research and survey data @en
idemo - Demographic ontology from the French Statistics Institute
http://rdf.insee.fr/def/demo

Ontology with classes and properties used for demography, mostly in the census of the population @en
odv - Organogram Data Vocabulary
http://reference.data.gov.uk/def/organogram

Extension of data cube for civil service junior posts @en

1 234 5...8

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)