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

168

results

How to

cff - Climate and Forecast (CF) features
http://purl.oclc.org/NET/ssnx/cf/cf-feature

This is an ontology representation of the generic features defined by Climate and Forecast (CF) standard names vocabulary (http://cf-pcmdi.llnl.gov/documents/cf-standard-names/), maintained by the Program for Climate Model Diagnosis and Intercomparison (http://cf-pcmdi.llnl.gov/ ) which is intended for use with climate and forecast data, in the atmosphere, surface and ocean domains. @en
of - Open Fridge vocabulary
http://owlrep.eu01.aws.af.cm/fridge

Ontology for Open Fridge project @en
semsur - The Semantic Survey Ontology (semsur)
http://purl.org/SemSur/

SemSur, the Semantic Survey Ontology, is a core ontology for describing individual research problems, approaches, implementations and evaluations in a structured, comparable way. @en
coreo - Core-o: Competence Reference Ontology
http://purl.org/coreo

An ontology to describe competences and human capabilities @en
fiesta-iot - FIESTA-IoT Ontology
http://purl.org/iot/ontology/fiesta-iot

The FIESTA-IoT ontology takes inspiration from the well-known Noy et al. methodology for reusing and interconnecting existing ontologies. To build the ontology, we leverage a number of core concepts from various mainstream ontologies and taxonomies, such as Semantic Sensor Network (SSN), M3-lite (a lite version of M3 ontology), WGS84, IoT-lite, Time, and DUL ontology. @en
fiesta-priv - FIESTA-Priv Ontology
http://purl.org/iot/ontology/fiesta-priv#

FIESTA-Priv Ontology @en
iottaxolite - The IoTTaxonomy-lite Taxonomy
http://purl.org/iot/vocab/iot-taxonomy-lite#

The IoT-Taxonomy-lite is adapted from M3-lite taxonomy. This taxonomy is refactored and defines many other concepts such as subclasses of Feature-of-Interest and Quality-of-Observation. @en
holy - Hydrogen Ontology
http://purl.org/holy/ns#

This is the Hydrogen Ontology (HOLY). HOLY is a domain ontology for describing the complex structure of hydrogen-based markets. HOLY contributes to the systemic modeling of the hydrogen domain with a focus on its value chain. Hence, it provides a foundation for retrieval, storage, and delivery of market insights. @en
sdmx - SDMX-RDF vocabulary
http://purl.org/linked-data/sdmx

This vocabulary extends the data cube vocabulary to support publication of statistical data in RDF, using an information model based on SDMX @en
sdmx-code - SDMX Code
http://purl.org/linked-data/sdmx/2009/code

Defines subclasses and instances of codes used in SDMX, such as currencies, decimals, frequencies ... @en
sdmx-dimension - SDMX Dimension
http://purl.org/linked-data/sdmx/2009/dimension

Defines dimensions for the statistical "cubes" defined by SDMX @en
limo - Linked Statistical Models Vocabulary
http://purl.org/limo-ontology/limo/

A Vocabulary for Incorporating Predictive Models into the Linked Data Web @en
m3lite - The Machine-to-Machine Measurement (M3) Lite Ontology
http://purl.org/iot/vocab/m3-lite#

M3 lite taxonomy is designed for the FIESTA-IOT H2020 EU project. We refactor, clean and simplify the M3 ontology designed by Eurecom (Amelie Gyrard). M3 ontology lite is currently aligned with the quantity taxonomy used by several testbeds: SmartSantander (Spain), University of Surrey (United Kingdom), KETI (Korea) and Com4Innov (France). @en
ipo - IPO - Issue Procedure Ontology
http://purl.org/ipo/core

Vocabulary for describing issues (or problems) and corresponding symptoms and solutions to a broad variety of contexts. It is intended to provide a generic, reusable core ontology that can be extended or specialized for use in domain-specific situations, aimed at supporting linked data publishing. The solutions are represented by procedures, which are possible workflows for solving corresponding issues. @en
qb - The data cube vocabulary
http://purl.org/linked-data/cube

This vocabulary allows multi-dimensional data, such as statistics, to be published in RDF. @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)