Item:OSWdb485a954a88465287b341d2897a84d6: Difference between revisions

From OpenSemanticWorld
Item:OSWdb485a954a88465287b341d2897a84d6
(Update package: OSW Docs - Core)
(add Link to related technologies)
Tag: 2017 source edit
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== Motivation ==
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</div> doi: https://doi.org/10.5281/zenodo.8086418
 
==Background==
[[File:OSWa81f4a8b552e4057888796a9a496dad3.png|none|thumb|1200x1000px|from: https://github.com/General-Process-Ontology/ontology]]
 
==KIproBatt Project Usecase==
[[File:OSWb620db8af84847acabf76a88633f980c.png|none|thumb|1200x1000px|from: https://kiprobatt.de]]
<!-- <img src="/w/index.php?title=Special:Redirect/file/OSWb620db8af84847acabf76a88633f980c.png" style="width:70%"></img> -->
 
 
==Motivation==
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== OSW ==
==OpenSemanticWorld Concept==
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== Technology Stack ==
==Technology Stack==
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*** other options like mustache and markdown
*** other options like mustache and markdown
** > 1000 [[mediawikiwiki:Category:All_extensions|extensions]]: UI, data handling, custom content, etc.
** > 1000 [[mediawikiwiki:Category:All_extensions|extensions]]: UI, data handling, custom content, etc.
* ... but it's just a container, the core JSON-based concept is highly portable  
* ... but it's just a container, the core JSON-based concept is highly portable
 
==Link to related technologies==
{{Template:Editor/DrawIO
| file_name = diagram-01
| page_name = Item:OSWdb485a954a88465287b341d2897a84d6
| uuid = 2f275e34-41c8-4f63-a6cb-ee2861c488f2
| width = 50%
}}
 
==Link to Ontologies==


== Ontologies ==
* Ontology classes are just specific schemas / schemas represent "icons" of "real objects"
*Automatic import via python (see: [https://github.com/OpenSemanticLab/osw-python/blob/main/examples/ontology_import.py Python Examples])
*Combination with data schemas, e. g. to populate autocomplete fields
*''Not just a static documentation'': Planned community interaction features
**Comments => Github Issues,
**Edits => Re-export => Github Pull request


* Ontology classes are just specific schemas
<!-- == Link to Ontologies: Dual hierarchy ==
* Automatic import
* Combination with data schemas
* Reexport => Pull request


== Usecases ==
{{#mermaid:
classDiagram
 
    class Schema_Entity {
        String uuid
    }
    class Schema_Class {
    }
 
    Schema_Class <-- Schema_Entity: type
    Schema_Entity <-- Class_Entity: schema
 
    class Schema_OntologyTerm{
    }
    Schema_Class <|-- Schema_OntologyTerm : allOf
    Schema_OntologyTerm <-- Class_OwlThing : schema
 
 
    Class_OwlThing <|-- Class_Entity: subclassOf
 
    class Schema_Item {
        String type
        subclassOf Class_Item category
    }
 
    class Class_Entity {
        Schema_Entity schema
    }
    Schema_Entity <|-- Schema_Item : allOf
    Schema_Item <-- Class_Item: schema
    Class_Entity <|-- Class_Item: subclassOf
 
    class Schema_Physical {
        String location
    }
    Schema_Item <|-- Schema_Physical : allOf
 
    Class_Item <|-- Class_Device : subclassOf
    Schema_DeviceClass <-- Class_Device : schema
 
    class Schema_DeviceClass {
        String manufacturer
        subclassOf Class_Device category
    }
    Schema_Item <|-- Schema_DeviceClass : allOf
  |
  config.theme = neutral
}}  -->
 
<!-- == Link to Ontologies: Example ==
{{#mermaid:
classDiagram
    class Schema_Physical {
        String location
    }
    Schema_Item <|-- Schema_Physical : allOf
 
    Class_Item <|-- Class_Device : subclassOf
    Class_Device <|-- Class_MeasurementDevice : subclassOf
    Schema_DeviceClass <-- Class_Device : schema
 
    class Schema_DeviceClass {
        String manufacturer
        subclassOf Class_Device category
    }
    Schema_Item <|-- Schema_DeviceClass : allOf
 
    class Instance_DeviceType1 {
        manufacturer: CompanyABC
        category: Class_MeasurementDevice
    }
    Schema_Item <|-- Instance_DeviceType1 : type
    Schema_DeviceClass <-- Instance_DeviceType1 : type
 
    class Schema_DeviceInstance {
        Schema_DeviceClass device_type
        String location
    }
    Schema_Physical <|-- Schema_DeviceInstance : allOf
    Schema_DeviceClass o-- Schema_DeviceInstance : device_type
 
    class Instance_MyDevice {
        device_type: Instance_DeviceType1
        location: somewhere
    }
    Schema_DeviceInstance <-- Instance_MyDevice : type
    Instance_DeviceType1 o-- Instance_MyDevice : device_type
  |
  config.theme = neutral
}}
-->
==Usecases and Applications==


* Ontologies Documentation, Visualization, Demonstration
*Schema / Dataspace Catalogue
* Tool and Workflow Registry
*Ontologies Documentation, Visualization, Demonstration (s. a. [https://onto-wiki.eu/wiki/Main_Page Onto-Wiki])
* Dataspace Catelogue
*Driver (=> CAMELS) , Tool and Workflow Registry ([https://demo.open-semantic-lab.org/wiki/Item:OSWd94b2ac3a2194dab8f9873d495752a24 Early Demo])
*Easy access to data science workflows: [https://onterface.open-semantic-lab.org/wiki/ Onterface]
*LIMS, ELN ([https://demo.open-semantic-lab.org Demo]), etc. in connection with ELN Standard Format, NOMAD, etc.
*... whatever you want it to be

Revision as of 10:06, 1 September 2023

OSW Introduction [OSWdb485a954a88465287b341d2897a84d6]
ID OSWdb485a954a88465287b341d2897a84d6
UUID db485a95-4a88-4652-87b3-41d2897a84d6
Label OSW Introduction
Machine compatible name OswIntroduction
Statements (outgoing)
Statements (incoming)
Keywords

Description

Introduction into the open-source software stack OpenSemanticLab: https://github.com/OpenSemanticLab/mediawiki-extensions-OpenSemanticLab

Item
Type(s)/Category(s) Tutorial
CreativeWork
Article
Tutorial
Prerequisites (required)
Prerequisites (optional)
Follow-up (recommended) Transcend wikitext to store and edit structured & linked data
OSW Python Package
OSW Ontology Import
Item:OSW92619b0700984fe7913e5fbbd7f194dc

View as slide show

doi: https://doi.org/10.5281/zenodo.8086418

Background

KIproBatt Project Usecase


Motivation

OpenSemanticWorld Concept

Technology Stack

Why (Semantic) MediaWiki?

Link to related technologies

Link to Ontologies

  • Ontology classes are just specific schemas / schemas represent "icons" of "real objects"
  • Automatic import via python (see: Python Examples)
  • Combination with data schemas, e. g. to populate autocomplete fields
  • Not just a static documentation: Planned community interaction features
    • Comments => Github Issues,
    • Edits => Re-export => Github Pull request


Usecases and Applications


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