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

193

results

How to

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
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
dvia - The visualization vocabulary for LOD applications
http://purl.org/ontology/dvia

dvia is an RDF vocabulary designed to facilitate interoperability between visualization applications published on the 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
rss - Vocabulary for Rich Site Summary (RSS) 1.0
http://purl.org/rss/1.0

RDF Schema declaration for Rich Site Summary (RSS) 1.0 @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
ofrd - Fridge and Freezer Vocabulary
http://purl.org/opdm/refrigerator#

Vocabulary to describe fridges and freezers @en
toco - Toucan Ontology
http://purl.org/toco/

A ontology developed for telecommunciation network systems with hybrid technologies, e.g., WiFi, LiFi, LTE, 2G/3G, optical, etc. @en
summa - SUMMA Vocabulary
http://purl.org/voc/summa/

The SUMMA Vocabulary enables to request and represent summarized RDf resources. It should be used in context to the SUMMA API definition. @en
vvo - Volkswagen Vehicles Ontology
http://purl.org/vvo/ns#

A vocabulary for describing Volkswagen-specific features of automobiles and their components @en
xapi - xAPI Controlled Vocabulary Ontology
http://purl.org/xapi/ontology#

This ontology contains a list of the classes and properties that can be used when for creating and publishing a controlled vocabulary dataset for xAPI communities of practice. @en

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Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (193)
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Portuguese (4)
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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)