Ontology Hub

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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

898

results

How to

mexalgo - MEX Algorithm Ontology
http://mex.aksw.org/mex-algo

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-algo layer represents the algorithm information existing into a basic machine learning experiment. @en
mexcore - MEX Core Vocabulary
http://mex.aksw.org/mex-core

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-core layer represents the core information gathered from a basic machine learning experiment design. @en
mexperf - MEX Performance Ontology
http://mex.aksw.org/mex-perf

MEX is an RDF vocabulary designed to facilitate interoperability between published machine learning experiments results on the Web. The mex-perf layer is the 3rd level of the MEX for representing the machine learning algorithm's performances. @en
mil - Military Ontology Specification
http://rdf.muninn-project.org/ontologies/military

The Muninn Military Ontology marks up information about military people, organizations and events. @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
mo - Music Ontology
http://purl.org/ontology/mo/

The Music Ontology Specification provides main concepts and properties fo describing music (i.e. artists, albums and tracks) on the Semantic Web @en
moac - Management of a Crisis Vocabulary
http://www.observedchange.com/moac/ns#

MOAC, the Management of a Crisis Vocabulary, is a lightweight vocabulary aiming to provide terms to enable practitioners to relate different "things" in crisis management activities together as Linked Data. The initial MOAC terms originated from the Inter Agency Standing Committee (IASC), Emergency Shelter Cluster in Haiti, UNOCHA 3W Who What Where Contact Database @en
moat - Meaning of a Tag Ontology
http://moat-project.org/ns#

An ontology that let users define relationships between Tag objects and URIs of Semantic Web resources @en
mod - MOD: Metadata for Ontology Description and publication
http://www.isibang.ac.in/ns/mod

This specification describes MOD, a metadata vocabulary to describe and publish ontologies @en
modp - Metadata for Ontology Description and publication
https://w3id.org/mod

Metadata for Ontology Description and publication @en
modsci - ModSci, Modern Science Ontology.
https://w3id.org/skgo/modsci#

ModSci is a reference ontology for modelling different types of modern sciences and related entities, such as scientific discoveries, renowned scientists, instruments, phenomena ... etc. @en
mrel - MARC Code List for Relators
http://id.loc.gov/vocabulary/relators

MARC relators are defined as both RDF properties and SKOS concepts @en
msm - Minimal Service Model
http://iserve.kmi.open.ac.uk/ns/msm

A simple RDF(S) ontology able to capture (part of) the semantics of both Web services and Web APIs @en
mso-em - MSO-EM: Ontologies for modelling, simulation, optimization (MSO) and epistemic metadata (EM)
https://www.purl.org/mso-em

MSO-EM is a system of ontologies for documenting the knowledge status of models and data; the aim is to make models and data explainable-AI-ready (XAIR). @en
msr - Measurement Ontology
http://www.telegraphis.net/ontology/measurement/measurement#

The Measurement Ontology is an ontology in which measurements may be rendered @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)