Linked Open Vocabularies

Vocabs
Terms
Agents
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

140

results

How to

iot-lite - Iot-lite ontology
http://purl.oclc.org/NET/UNIS/fiware/iot-lite#

iot-lite is a lightweight ontology based on SSN to describe Internet of Things (IoT) concepts and relationships. @en
of - Open Fridge vocabulary
http://owlrep.eu01.aws.af.cm/fridge

Ontology for Open Fridge project @en
acco - Accomodation Ontology
http://purl.org/acco/ns

A vocabulary for the description of hotels, vacation homes, camping sites, and other accommodation offers for e-commerce @en
cold - 'Configuration as Linked Data' ontology
http://purl.org/configurationontology

Ontology for the description of customizable products. It models the configuration process as the traversal of a graph of partially defined products, or "Configurations" @en
coo - Car Options Ontology
http://purl.org/coo/ns#

The COO provides a vocabulary for exposing available configuration options for car models. It allows indicating choices that can be made as well as compatibility, dependency, and inclusion information. The ontology imports and extends the GoodRelations ontology for e-commerce @en
inno - Ontology for Innovation
http://purl.org/innovation/ns

One key use case for this ontology is to facilitate the matching of needs and innovations. @en
fiesta-iot - FIESTA-IoT Ontology
http://purl.org/iot/ontology/fiesta-iot

The FIESTA-IoT ontology takes inspiration from the well-known Noy et al. methodology for reusing and interconnecting existing ontologies. To build the ontology, we leverage a number of core concepts from various mainstream ontologies and taxonomies, such as Semantic Sensor Network (SSN), M3-lite (a lite version of M3 ontology), WGS84, IoT-lite, Time, and DUL ontology. @en
gr - The GoodRelations Ontology for Semantic Web-based E-Commerce
http://purl.org/goodrelations/v1

The GoodRelations ontology provides the vocabulary for annotating e-commerce offerings (1) to sell, lease, repair, dispose, or maintain commodity products and (2) to provide commodity services. @en
fiesta-priv - FIESTA-Priv Ontology
http://purl.org/iot/ontology/fiesta-priv#

FIESTA-Priv Ontology @en
iottaxolite - The IoTTaxonomy-lite Taxonomy
http://purl.org/iot/vocab/iot-taxonomy-lite#

The IoT-Taxonomy-lite is adapted from M3-lite taxonomy. This taxonomy is refactored and defines many other concepts such as subclasses of Feature-of-Interest and Quality-of-Observation. @en
m3lite - The Machine-to-Machine Measurement (M3) Lite Ontology
http://purl.org/iot/vocab/m3-lite#

M3 lite taxonomy is designed for the FIESTA-IOT H2020 EU project. We refactor, clean and simplify the M3 ontology designed by Eurecom (Amelie Gyrard). M3 ontology lite is currently aligned with the quantity taxonomy used by several testbeds: SmartSantander (Spain), University of Surrey (United Kingdom), KETI (Korea) and Com4Innov (France). @en
ofrd - Fridge and Freezer Vocabulary
http://purl.org/opdm/refrigerator#

Vocabulary to describe fridges and freezers @en
tio - The Tickets Ontology
http://purl.org/tio/ns#

A vocabulary for describing tickets for events, transportation, or points of interest for e-commerce. @en
vso - Vehicle Sales Ontology
http://purl.org/vso/ns

The Vehicle Sales Ontology for Semantic Web-based E-Commerce @en
vvo - Volkswagen Vehicles Ontology
http://purl.org/vvo/ns#

A vocabulary for describing Volkswagen-specific features of automobiles and their components @en

123 4...10

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (140)
property/class >
agent >

Language

English (111)
Spanish (12)
French (11)
German (10)
Italian (7)
Dutch (4)
Bulgarian (2)
Chinese (2)
Czech (2)
Finnish (2)
show more...

: Linked Open Vocabularies

Documentation

About
API documentation
Contact

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)