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

100

results

How to

seq - Sequence Pattern
http://www.ontologydesignpatterns.org/cp/owl/sequence.owl

Intended to represent sequence schemas. It defines the notion of transitive and intransitive precedence and their inverses. It can then be used between tasks, processes, time intervals, spatially locate objects, situations, etc. @en
infor - Information Realization
http://www.ontologydesignpatterns.org/cp/owl/informationrealization.owl

Allows designers to model information objects and their realizations. This allows to reason about physical objects and the information they realize, by keeping them distinguished. @en
odpart - Ontology Design Pattern Participation
http://www.ontologydesignpatterns.org/cp/owl/participation.owl

The basic participation pattern, without temporal indexing. It clones equivalent elements from DOLCE-UltraLite. @en
irw - The Identity of Resources on the Web ontology
http://www.ontologydesignpatterns.org/ont/web/irw.owl

This ontology is an evolution of IRE ontology. It describes identification of resources on the Web, through the definition of relationships between resources and their representations on the Web. The requirement is to describe what can be identified by URIs and how this is handled e.g. in form of HTTP requests and reponds. @en
hdo - HelpDesk support Ontology
http://www.samos.gr/ontologies/helpdeskOnto.owl

Simple ontology developed for integration purposes. Describe helpdesk entities used to record support tickets for diagnosis and resolve purpuses. The ontology re-uses a) W3C ORG and REGORG ontologies, b) DUL upper ontology, and c) GoodRelations ontology. @en
test - Test Metadata
http://www.w3.org/2006/03/test-description

This ontology aims at defining the Quality Assurance Framework by collecting the test development experience of W3C Working Groups and summarizing the work done about tests and metadata. @en
gso - Generic Specific Ontology
http://www.w3.org/2006/gen/ont

Ontology for Relating Generic and Specific Information Resources @en
cert - The Cert Ontology
http://www.w3.org/ns/auth/cert#

Ontology for Certificates and crypto stuff. @en
dqv - Data Quality Vocabulary
http://www.w3.org/ns/dqv

The Data Quality Vocabulary (DQV) is seen as an extension to DCAT to cover the quality of the data, how frequently is it updated, whether it accepts user corrections, persistence commitments etc. When used by publishers, this vocabulary will foster trust in the data amongst developers. @en
common - The Delivery Context Ontology
http://www.w3.org/2007/uwa/context/deliverycontext.owl

The Delivery Context Ontology models the knowledge of the environment in which devices interact with the Web or other services @en
earl - Evaluation and Report Language
http://www.w3.org/ns/earl

EARL is a vocabulary, the terms of which are defined across a set of specifications and technical notes, and that is used to describe test results. The primary motivation for developing this vocabulary is to facilitate the exchange of test results between Web accessibility evaluation tools in a vendor-neutral and platform-independent format. It also provides reusable terms for generic quality assurance and validation purposes. @en
lexdcp - Lexicon Model for Ontologies - Decomp
http://www.w3.org/ns/lemon/decomp

A model for the representation of lexical information relative to ontologies. Decomposition module. @en
lime - Lexicon Model for Ontologies - LIngusitic MEtadata (LIME)
http://www.w3.org/ns/lemon/lime

LIME (LInguistic MEtadata) is a vocabulary for expressing linguistic metadata about linguistic resources and linguistically grounded datasets. @en
mls - Machine Learning Schema
http://www.w3.org/ns/mls

ML-Schema is a collaborative, community effort with a mission to develop, maintain, and promote standard schemas for data mining and machine learning algorithms, datasets, and experiments @en
oa - Open Annotation Data Model
http://www.w3.org/ns/oa#

The Open Annotation Core Data Model specifies an interoperable framework for creating associations between related resources, annotations, using a methodology that conforms to the Architecture of the World Wide Web. This ontology is a non-normative OWL formalization of the textual OA specification at http://www.openannotation.org/spec/core/20130208/index.html @en

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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)