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

174

results

How to

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
dita - DITA RDF ontology
http://purl.org/dita/ns#

The DITA RDF ontology translates the semantics of a subset of the vocabulary described in the DITA 1.2 specification in a format that can be understood in the semantic Web of data. By Colin Maudry, licensed under the terms of the Unlicense (public domain). @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
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
pat - Patch Request Ontology
http://purl.org/hpi/patchr#

The Patch Request Ontology provides a schema to describe desired changes in Linked Data. By wrapping the Graph Update Ontology (guo) patch requests can be formulated to add, modify or delete particular triples (or subgraphs) within a dataset. @en
dsn - DSNotify Eventsets: A vocabulary for change events in linked data sources
http://purl.org/dsnotify/vocab/eventset/

DSNotify Eventsets is a vocabulary for events that change resources in linked data sources. @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
api - Linked Data API Vocabulary
http://purl.org/linked-data/api/vocab#

Configuration vocabulary for the Linked Data API @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
ofrd - Fridge and Freezer Vocabulary
http://purl.org/opdm/refrigerator#

Vocabulary to describe fridges and freezers @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
vvo - Volkswagen Vehicles Ontology
http://purl.org/vvo/ns#

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

123 4...12

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)