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

137

results

How to

sdmx-code - SDMX Code
http://purl.org/linked-data/sdmx/2009/code

Defines subclasses and instances of codes used in SDMX, such as currencies, decimals, frequencies ... @en
limo - Linked Statistical Models Vocabulary
http://purl.org/limo-ontology/limo/

A Vocabulary for Incorporating Predictive Models into the Linked Data Web @en
sdmx-dimension - SDMX Dimension
http://purl.org/linked-data/sdmx/2009/dimension

Defines dimensions for the statistical "cubes" defined by SDMX @en
ipo - IPO - Issue Procedure Ontology
http://purl.org/ipo/core

Vocabulary for describing issues (or problems) and corresponding symptoms and solutions to a broad variety of contexts. It is intended to provide a generic, reusable core ontology that can be extended or specialized for use in domain-specific situations, aimed at supporting linked data publishing. The solutions are represented by procedures, which are possible workflows for solving corresponding issues. @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
cco - Cognitive Characteristics Ontology
http://purl.org/ontology/cco/core#

The Cognitive Characteristics Ontology specification provides a vocabulary for describing cognitive pattern within contexts, their temporal dynamics and their origins, on/ for the Semantic Web. @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
dpo - Diabetes Pharmacology Ontology
http://purl.org/twc/dpo/ont/diabetes_pharmacology_ontology.ttl

The Diabetes Pharmacology Ontology contains the classes needed to describe antihyperglycemic therapies. @en
rel - Relationship
http://purl.org/vocab/relationship/

A vocabulary for describing relationships between people @en
wai - Roles and Profiles Ontology
http://purl.org/wai#

WAI vocabulary aims to extend the FOAF specification through introducing the concepts of roles and profiles. In society, people are more than just persons, they can be musicians, presidents of government, firemen, football players or car drivers in a traffic jam. @en
bio - BIO: A vocabulary for biographical information
http://purl.org/vocab/bio/0.1/

A vocabulary for describing biographical information about people, both living and dead. @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

1 2 345 6...10

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (137)
property/class >
agent >

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English (112)
French (8)
German (6)
Spanish (6)
Portuguese (3)
Dutch (2)
Arabic (1)
Basque (1)
Chinese (1)
Italian (1)
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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)