Structed Data Workshop
Item:OSW70b4d6464c1d44a887eb86e3b39b8751 /
| Structed Data Workshop [OSW70b4d6464c1d44a887eb86e3b39b8751] | |
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| ID | OSW70b4d6464c1d44a887eb86e3b39b8751 |
| UUID | 70b4d646-4c1d-44a8-87eb-86e3b39b8751 |
| Label | Structed Data Workshop |
| Machine compatible name | StructedDataWorkshop |
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Description
No description found
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| Type(s)/Category(s) | Tutorial |
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| Tutorial | |
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| Prerequisites (optional) | |
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State of the art regarding data standards
- Documents
- Formats themselves are highly standardized (pdf, MS Office, OpenDocument family)
- Support for metadata, but implementation in the UI mostly limited to generic information
- Images
- Formats themselves are highly standardized (png, jpeg, tiff, etc.)
- Metadata beyond generic information only supported by special formats like tiff
- Tabular data
- CSV widely used, supported by almost all software systems
- Extensive degrees of freedom almost always require prior knowledge for correct interpretation
- Domain-specific data (chemistry, engineering, computer science, etc.)
- Depends strongly on the use case
- How can we generate arbitrary structured (meta)data in a well-defined format?
- e. g. for processes running in different labs around the world?
The JSON Standard Family
- What can be expressed directly in JSON, what can be described indirectly? => JSON Tutorial
- How do references work in JSON?
- How can a JSON document be specified and validated? (json-schema) => JSON-SCHEMA Tutorial
- How can the meaning of data be defined? (json-ld) => JSON-LD Tutorial
Application & Hands-on
- ... using OpenSemanticLab as example implementation => OO-LD Tutorial
- UI generation (json-schema based editors & renderers)
- Knowledge Graph Generation
- Code Generation (python dataclasses) => osw python package
jsondata
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| uuid | "70b4d646-4c1d-44a8-87eb-86e3b39b8751" | |||||
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| image | "" | |||||
| name | "StructedDataWorkshop" |