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

122

results

How to

losp - Linked open specialities RF
http://sparql.sstu.ru:3030/speciality/

Ontology Specialties describes all possible specialties (directions) in the RF, in which the UGNS they are composed, as well as information about their old codes / groups / names. @en
rsctx - Recommender System Context
http://softeng.polito.it/rsctx

This ontology represent context which may be interesting in providing recommendations to users. @en
dfc-t - A common vocabulary for digital food platforms (Technical Part)
http://static.datafoodconsortium.org/ontologies/DFC_TechnicalOntology.owl

A common vocabulary for digital food platforms (Technical Part) @en
bot - BotDCAT-AP - Data Catalogue vocabulary Application Profile for chatbots
http://swa.cefriel.it/ontologies/botdcat-ap

A vocabulary to describe data sources in a way they can be easily reused and accessed by chatbots. @en
datex - Linked Datex II
http://vocab.datex.org/terms#

This document gives URIs to all terms used within Datex II. the Datex standard was developed for information exchange between traffic management centres, traffic information centres and service providers in Europe @en
comm - Vocabulary related to incident communication
http://vocab.resc.info/communication

This vocabulary is intended to describe all the aspects which are needed to communicate incident related information for fire department services @en
amlo-core - AMLO-core vocabulary
http://w3id.org/amlo/core

The AMLO-core is the main module of the AMLO projects that extends the Financial Industry Business Ontology (FIBO) with some concepts to describe the Anti Money Laundering (AML) knowledge and facts. @en
akts - AKT Support Ontology
http://www.aktors.org/ontology/support

The AKT Reference Ontology has been designed to support the AKT-2 demonstrator ("AKTive Portal"), and subsequent activities @en
roh - The ASIO ontology
http://w3id.org/roh

An ontology to address the Research Management of the CRUE's Spanish University System (Sistema Universitario Español) by applying an encompassing model not only capable of addressing the universities of the CRUE but also more belonging to the European Union. @en
km4c - km4city, the DISIT Knowledge Model for City and Mobility
http://www.disit.org/km4city/schema

A Knowledge Model to describe a smart city, that interconnect data from infomobility service, Open Data and other source @en
marl - Marl Ontology Specification
http://www.gsi.dit.upm.es/ontologies/marl/ns

Marl is a standardised data schema designed to annotate and describe subjective opinions expressed on the web or in particular Information Systems. @en
onyx - Onyx Emotion Ontology
http://www.gsi.dit.upm.es/ontologies/onyx/ns

Onyx is a vovabulary designed designed to annotate and describe the emotions expressed by user-generated content on the web or in particular Information Systems. @en
vag - The Vagueness Ontology
http://www.essepuntato.it/2013/10/vagueness

The Vagueness Ontology (VO) allows one to specify vagueness characterisations of the TBox entities of an ontology. @en
tag - Tag ontology
http://www.holygoat.co.uk/owl/redwood/0.1/tags/

An ontology that let users define relationships between Tag objects and URIs of Semantic Web resources @en
lifecycle - IoT-Lifecycle
http://www.irit.fr/recherches/MELODI/ontologies/IoT-Lifecycle

This ontology is a specialization of the lifecycle vocabulary (http://purl.org/vocab/lifecycle/schema) meant to be used in the context of IoT. It is used as a module in the IoT core domain ontology IoT-O (www.irit.fr/recherches/MELODI/ontologies/IoT-O). IoT-Lifecycle adds a specific state definition (ParametrizedState) and a specific transition (Update) that is useful to model actuators. @en

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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)