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

912

results

How to

lc - The Linked Connections ontology
http://semweb.mmlab.be/ns/linkedconnections#Ontology

This ontology provides the predicates necessary to describe a connection or hop from one transit stop to another. @en
odapps - The vocabulary for (L)OD ideas and applications
http://semweb.mmlab.be/ns/odapps

odapps is an RDF vocabulary defined to facilitate the description of Open-Data-based ideas and applications published on the Web. @en
oh - The Opening Hours vocabulary
http://semweb.mmlab.be/ns/oh

A vocabulary to describe opening hours using calendars (recommended: iCal, RDFCal or schema.org) published on the Web. @en
st - The Stop Times ontology
http://semweb.mmlab.be/ns/stoptimes#Ontology

This ontology provides the predicates necessary to describe an arrival of a transit vehicle and its departure at a certain Stop. @en
dqc - The Data Quality Constraints Library
http://semwebquality.org/ontologies/dq-constraints

This RDF document contains a library of data quality constraints represented as SPARQL query templates based on the SPARQL Inferencing Framework (SPIN). The data quality constraint templates are especially useful for the identification of data quality problems during data entry and for periodic quality checks during data usage. @en
ha - Home Activity
http://sensormeasurement.appspot.com/ont/home/homeActivity#

An ontology to detect activity in a smart home @en
security - Security Ontology
http://securitytoolbox.appspot.com/securityMain

A security ontology to annotate resources with security-related information @en
stac - Security Toolbox : Attacks and Countermeasures
http://securitytoolbox.appspot.com/stac

A vocabulary to describe main security and cryptographic concepts: attacks, security mechanisms, OSI model, security protocols, security tools in numerous technologies: Web applications, network management, Sensor networks, Cellular (2G, 3G, 4G) and Wireless (Wifi), etc. @en
maso - Mobile Agents Security
http://securitytoolbox.appspot.com/MASO

Ontology for security of mobile agents @en
mdr - The Semantic Turkey metadata registry ontology
http://semanticturkey.uniroma2.it/ns/mdr

An application profile of DCAT combining it with other metadata vocabularies (e.g. VoID, DCTERMS, LIME) to meet requirements elicited in various use cases of the Semantic Web platform Semantic Turkey @en
apps4X - The vocabulary for Co-creation Events based on Open Data
http://semweb.mmlab.be/ns/apps4X

apps4X is an RDF vocabulary defined to facilitate the description of Open-Data-based Co-creation events @en
sio - Semanticscience Integrated Ontology
http://semanticscience.org/ontology/sio.owl

The semanticscience integrated ontology (SIO) provides a simple, integrated ontology (types, relations) for objects, processes and their attributes. This project provides foundational support for the Bio2RDF (http://bio2rdf.org) and SADI (http://sadiframework.org) projects. @en
algo - Algorithms Ontology
http://securitytoolbox.appspot.com/securityAlgorithms#

An ontology describing cryptographic algorithms @en
sem - The SEM Ontology
http://semanticweb.cs.vu.nl/2009/11/sem/

The SEM Ontology defines entities that make up the context of an event: Events, Actors, Places, Times. @en
spcm - Software Process Control Model
http://spi-fm.uca.es/spdef/models/deployment/spcm/1.0

Planning and monitoring the execution of software projects can be carried out with different supporting tools, from issue tracking systems to Gantt chart tools or even with using simple spreadsheets. This vocabulary includes the common elements for controlling software development or maintenance projects. @en

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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)