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

126

results

How to

aws - Ontology for Meteorological sensors
http://purl.oclc.org/NET/ssnx/meteo/aws

This ontology is part of the Agriculture Meteorology example showcasing the ontology developed by the W3C Semantic Sensor Networks incubator group (SSN-XG). It is published here in order to generalize the potential usage and the alignment with other standardization efforts of the SSN ontology. @en
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
loc - Location Vocabulary
http://purl.org/ctic/infraestructuras/localizacion

This vocabulary is used to describe the physical location of public places. @en
ctorg - Vocabulary for the structure of the public organizations
http://purl.org/ctic/infraestructuras/organizacion

The goal of this vocabulary is to create a scheme to define the contents of information related to the government structure and public centers. @en
elec - Vocabulary for Vote Results
http://purl.org/ctic/sector-publico/elecciones

The objective of this vocabulary is to describe the vote process and results. @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
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
tsnc - Territorial Statistical Nomenclature Change Ontology
http://purl.org/net/tsnchange#

The TSN-Change ontology aims at describing changes that occured from one version of a Territorial Statistical Nomenclature (TSN) (i.e., partition of the territory) and its subsequent (e.g., change in territorial units boundaries to reflect an administrative reorganisation). @en
cart - cartCoordOnt
http://purl.org/net/cartCoord#

Ontology for representation of cartesian co-ordinates @en
tsn - Territorial Statistical Nomenclature Ontology
http://purl.org/net/tsn#

This RDF ontology allows describing any Territorial Statistical Nomenclature (TSN) (i.e., partition of the territory) used as a support to socio-economic data (statistical data that describe territory in terms of population, unemployement rate, transport access, etc.). @en
step - Semantic Trajectory Episodes
http://purl.org/net/step

A lightweight ontology for representing semantic trajectories and contextual elements in terms of features of interests and episodes. @en
place - The Places Ontology
http://purl.org/ontology/places

The Places Ontology is a simple lightweight ontology for describing places of geographic interest. @en

1 234 5...9

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

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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)