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

133

results

How to

bimerr-op - Occupancy Profile ontology
http://bimerr.iot.linkeddata.es/def/occupancy-profile#

The Occupancy Profile ontology has been developed to represent people’s behavior inside building spaces. @en
plink - PersonLink Ontology
http://cedric.cnam.fr/isid/ontologies/PersonLink.owl

A Multilingual and Multicultural Ontology Representing Family Relationships. @en
agrelon - Agent Relationship Ontology
http://d-nb.info/standards/elementset/agrelon

The ontology of agent relationships, AgRelOn, defines relations of persons to other persons and to organisations @en
graphql - GraphQL Vocabulary
http://datashapes.org/graphql

A vocabulary to annotate RDF schemas (in particular SHACL shapes) with metadata to define mappings to GraphQL. @en
bperson - Person
http://data.vlaanderen.be/ns/persoon

Person ontology in Dutch @en
obws - Object with states ontology
http://delicias.dia.fi.upm.es/ontologies/ObjectWithStates.owl

Ontology including the content ontology design pattern for modelling objects with states. @en
poder - Poder Vocabulary
http://dev.poderopedia.com/vocab/schema

A vocabulary to express information about people and their relations with Organizations, Companies, etc. @en
h2o - Ontology for conversion of ISO/TC 211
http://def.seegrid.csiro.au/isotc211/iso19150/-2/2012/basic

This ontology establishes classes corresponding to stereotypes used in ISO-conformant models, as used in the rules for conversion of the ISO TC 211 Harmonized Model from the UML to OWL representations @en
sam - The Sampling Features Schema Vocabulary
http://def.seegrid.csiro.au/isotc211/iso19156/2011/sampling

An OWL representation of the Sampling Features Schema described in clauses 8-10 of ISO 19156:2011 Geographic Information - Observations and Measurements. @en
mexcore - MEX Core Vocabulary
http://mex.aksw.org/mex-core

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-core layer represents the core information gathered from a basic machine learning experiment design. @en
mexalgo - MEX Algorithm Ontology
http://mex.aksw.org/mex-algo

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-algo layer represents the algorithm information existing into a basic machine learning experiment. @en
mexperf - MEX Performance Ontology
http://mex.aksw.org/mex-perf

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-perf layer is the 3rd level of the MEX for representing the machine learning algorithm's performances. @en
rdarel2 - RDA Relationships GR2
http://metadataregistry.org/uri/schema/RDARelationshipsGR2

RDA Relationships for Persons, Corporate Bodies, Families @en
dbowl - Relational to Ontology Mapping Primitive
http://ontology.cybershare.utep.edu/dbowl

Primitive ontology for database to Semantic Web mapping which subsumes classes that represent mappings to explicit OWL constructs, such as OWL class, object property, data property, etc. Classes in this ontology are populated by individuals representing components of the database schema being mapped. @en
dbug - DOAP Bugs
http://ontologi.es/doap-bugs#

An extension of DOAP for the description of bugs @en

123 4...9

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (133)
property/class >
agent >

Language

English (111)
French (8)
German (6)
Spanish (5)
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)