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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

results

How to

icon - ICON Ontology
https://w3id.org/icon/ontology/

The ICON ontology deals with high granularity art interpretation. It was developed by conceptualizing Panofsky's theory of levels of interpretation, therefore artworks can be described according to Pre-iconographical, Iconographical and Iconological information. @en
loin - Level of Information Need (LOIN) Ontology
https://w3id.org/loin

The Level of Information Need (LOIN) Ontology is defined for specifying information requirements for delivery of data in a buildings' life cycle. The LOIN ontology is based on the standard BS EN 17412-1 (2020). Furthermore, it is extended with vocabulary for connecing Information Delivery Specifications (IDS) and Information containers for linked document delivery (ICDD) as per ISO 21597-1 (2020). @en
ontouml - OntoUML Metamodel Vocabulary
https://w3id.org/ontouml

A reference implementation of the OntoUML metamodel in OWL. @en
sdont - The Software Description Ontology
https://w3id.org/okn/o/sd

An ontology for describing software and their links to inputs, outputs and variables. The ontology extends schema.org and codemeta vocabularies @en
okh - Open Know How (OKH) ontology
https://w3id.org/oseg/ont/okh

Used for indexing, searching and comparing Open Source Hardware projects @en
nno - The Neural Network Ontology
https://w3id.org/nno/ontology

This is the Neural Network Ontology. Designed by the AIFB (http://www.aifb.kit.edu/web/Web_Science) @en
pep - Process Execution ontology.
https://w3id.org/pep/

The process execution ontology is a proposal for a simple extension of both the [W3C Semantic Sensor Network](https://www.w3.org/TR/vocab-ssn/) and the [Semantic Actuator Network](https://www.irit.fr/recherches/MELODI/ontologies/SAN.owl) ontology cores. @en
seas-stats - The SEAS Statistics ontology.
https://w3id.org/seas/StatisticsOntology

This ontology defines common evaluation interpretation concepts for statistics. @en
seas-eval - The SEAS Evaluation ontology
https://w3id.org/seas/EvaluationOntology

The Evaluation ontology describes evaluation of [`seas:Property`ies](https://w3id.org/seas/Property). There may be: - direct evaluations, or - qualified evaluations. @en
rains - The RAInS Ontology
https://w3id.org/rains

An ontology to model accountability of AI systems which use machine learning. @en
pko - Procedural Knowledge Ontology (PKO)
https://w3id.org/pko

The Procedural Knowledge Ontology (PKO) addresses the Procedural Knowledge (PK) domain, and models procedures, their executions, and related resources and agents. @en
swemls - Semantic-Web Machine Learning System (SWeMLS) Ontology
https://w3id.org/semsys/ns/swemls

An ontology to describe a Semantic-Web Machine Learning System (SWeMLS) @en
tido - The Threat Intelligence Decision Ontology
https://w3id.org/tido#

The TIDO ontology can be used to describe the decision processes within the threat intelligence domain @en
tribont-sample - Sample module
https://w3id.org/tribont/sample

The goal of this module is to represent the sample systems , and the undelaying samples, involved in the tribological experiments. @en
tree - TREE
https://w3id.org/tree

A hypermedia specification for fragmenting collections. @en

1...3 456

Selected vocabularies

Patterns?:	type name both
Flatten?:	yes no

Type

vocabulary (82)
property/class >
agent >

Language

English (68)
French (3)
German (3)
Portuguese (3)
Spanish (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)