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

opmv - Open Provenance Model Vocabulary
http://purl.org/net/opmv/ns#

OPMV, the Open Provenance Model Vocabulary, provides terms to enable practitioners of data publishing to publish their data responsibly. @en
prv - Provenance Vocabulary Core Ontology
http://purl.org/net/provenance/ns#

The Provenance Vocabulary Core Ontology provides the main classes and properties required to describe provenance of data on the Web. @en
prvt - Provenance Vocabulary types
http://purl.org/net/provenance/types#

Extends the Provenance Vocabulary by defining subclasses of the types of provenance elements introduced in the core ontology. @en
pr - Property Reification Vocabulary
http://purl.org/ontology/prv/core#

A vocabulary for describing the ontology design pattern of property reification. @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
pav - Provenance, Authoring and Versioning
http://purl.org/pav/

PAV is a lightweight ontology for tracking Provenance, Authoring and Versioning. PAV specializes the W3C provenance ontology PROV-O in order to describe authorship, curation and digital creation of online resources. @en
uneskos - UNESKOS Vocabulary
http://purl.org/umu/uneskos

An RDF vocabulary for extending some SKOS and ISO-THES functions in order to improve the linked data consumption of SKOS datasets @en
cs - Changeset
http://purl.org/vocab/changeset/schema

This vocabulary defines a set of terms for describing changes to resource descriptions. @en
cdm - Conceptual Depth and Momentum
http://purl.org/twc/ontology/cdm.owl#

An attempt to represent how universal/accepted/popular a URI is @en
conversion - Conversion Ontology
http://purl.org/twc/vocab/conversion/

Ontology used to describe interpretations of tabular literals to produce RDF @en
ruto - Test-Driven Data Debugging Ontology
http://rdfunit.aksw.org/ns/core#

The Databugger ontology describes concepts used in Databugger, a test driven data-debugging framework that can run automatically generated (based on a schema) and manually generated test cases against an endpoint. @en
isoadr - ISO19160-1:2015 Address ontology
http://reference.data.gov.au/def/ont/iso19160-1-address

This ontology is a version of the ISO TC211, Group for Ontology Management (GOM)'s OWL ontology interpretation of the ISO19160-1:2015 "Addressing -- Part 1: Conceptual model" standard (see https://www.iso.org/standard/61710.html) taken from that ontology's source code, published at https://github.com/ISO-TC211/GOM/tree/master/isotc211_GOM_harmonizedOntology/19160-1/2015. @en
odrs - Open Data Rights Statement Vocabulary
http://schema.theodi.org/odrs

A vocabulary that supports the publication of Open Data by providing the means to capture machine-readable "rights statements", e.g. the licensing information, copyright notices and attribution requirements that are associated with the publication and re-use of a dataset. @en
odapps - The vocabulary for (L)OD ideas and applications
http://semweb.mmlab.be/ns/odapps

odapps is an RDF vocabulary defined to facilitate the description of Open-Data-based ideas and applications published on the Web. @en
dqc - The Data Quality Constraints Library
http://semwebquality.org/ontologies/dq-constraints

This RDF document contains a library of data quality constraints represented as SPARQL query templates based on the SPARQL Inferencing Framework (SPIN). The data quality constraint templates are especially useful for the identification of data quality problems during data entry and for periodic quality checks during data usage. @en

123 4...7

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (94)
property/class >
agent >

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English (59)
en (6)
Czech (2)
French (2)
German (2)
Italian (2)
Japanese (2)
Spanish (2)
Arabic (1)
Greek (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)