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Convert data model from CSV to JSONLD
schematic schema convert input.csv output.jsonld
Schematic DB
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Formatted for readability:
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Schematic dev mode helps find and deal with erors by iteratively checking JSON-LD
Generate JSON-LD from CSV
schematic schema convert data_model.csv
Data Model Validation
/wiki/spaces/SCHEM/pages/2645262364
Ontology
Data Model Visualization
https://linkml.io/linkml/intro/tutorial.html
https://docs.google.com/spreadsheets/d/1vDdcqt3Lgehyq1iCnlF1H9JZi63pLj-u/edit#gid=1939820452
https://portal.includedcc.org/dashboard
https://linkml.io/schemasheets/#examples
https://docs.google.com/spreadsheets/d/1w6zDfz3_yrCjjrqfpXBGNmd0LZL4B03gr1KfzJtk5Cs/edit#gid=674286209
https://docs.google.com/presentation/d/129pSx58qDm7Y1OQmSSHKDq6tsoD3pW_gDRNXiX2rd0w/edit#slide=id.g4d21a8c2ba_0_11
/wiki/spaces/SCHEM/pages/2453176326
/wiki/spaces/SCHEM/pages/2458419217
Glossary
Manifest - metadata table submitted for datasets
JSON for Linking Data
JSON-LD
Data models are defined in https://www.json.org/json-en.html . Specifically, JSON-LinkedDirectory (JSON-LD) files.
https://cambridgesemantics.com/blog/semantic-university/learn-rdf/rdf-nuts-bolts-2/
One reason we use JSON-LD in schematic is its support by http://schema.org.
And a reason for http://schema.org is dataset discoverability: https://datasetsearch.research.google.com/
JSON-LD useful for search engines
Error Troubleshooting
Create a data model formatted as a CSV
Where is the reference to how data model needs to be formatted?
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model
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schematic schema convert input.csv output.jsonld
Guide to Developing Data Models in JSON-LD
JSON-LD, or JavaScript Object Notation for Linked Data, is a JSON-based format for serializing Linked Data. It extends JSON with additional functionality to represent linked data structures, such as contexts, @id, and @type. JSON-LD is a lightweight and flexible format that can be used to represent a variety of data models.
This guide provides an introduction to developing data models in JSON-LD. It covers the following topics:
JSON-LD syntax
JSON-LD contexts
Modeling entities and relationships
Using vocabularies
Best practices for developing JSON-LD data models
JSON-LD Syntax
JSON-LD documents are valid JSON documents. They consist of key-value pairs, where the keys are strings and the values can be strings, numbers, objects, arrays, or booleans. JSON-LD documents can also contain additional keywords that provide additional information about the data.
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@context: The context URI specifies the vocabulary that is used to interpret the data. In this case, the vocabulary is http://Schema.org .@id: The@idproperty uniquely identifies the resource. In this case, the resource is a book.type: Thetypeproperty specifies the type of the resource. In this case, the resource is a book.name: Thenameproperty specifies the name of the book.author: Theauthorproperty specifies the author of the book.
JSON-LD Contexts
JSON-LD contexts are used to map IRIs (Internationalized Resource Identifiers) to human-readable names. Contexts can also be used to define prefixes for IRIs. This can make JSON-LD documents easier to read and write.
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The type property is now prefixed with schema:. This makes the document easier to read and understand.
Modeling Entities and Relationships
Entities in a JSON-LD data model are represented by objects. Relationships between entities are represented by properties. For example, the following JSON-LD document describes a book and a person:
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The author property in the book object refers to the person object. This indicates that Douglas Adams is the author of The Hitchhiker's Guide to the Galaxy.
Using Vocabularies
Vocabularies are collections of terms and definitions that are used to describe data. JSON-LD data models can use vocabularies to provide a common understanding of the data.
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When developing a JSON-LD data model, it is important to choose the appropriate vocabulary. The vocabulary should be relevant to the type of data that you are modeling.
**Best PracticesData models are formatted in JavaScript Object Notation-LinkedData (JSON-LD).
https://cambridgesemantics.com/blog/semantic-university/learn-rdf/rdf-nuts-bolts-2/
JSON-LD in schematic is its support by http://schema.orgdataset discoverability in search engines like: Dataset Search
Error Checking
Schematic dev mode helps find and deal with errors by iteratively checking data models
Data Model Visualization
Data Model Validation
/wiki/spaces/SCHEM/pages/2645262364
References
https://linkml.io/linkml/intro/tutorial.html
https://docs.google.com/spreadsheets/d/1vDdcqt3Lgehyq1iCnlF1H9JZi63pLj-u/edit#gid=1939820452
https://portal.includedcc.org/dashboard
https://linkml.io/schemasheets/#examples
https://docs.google.com/spreadsheets/d/1w6zDfz3_yrCjjrqfpXBGNmd0LZL4B03gr1KfzJtk5Cs/edit#gid=674286209
https://docs.google.com/presentation/d/129pSx58qDm7Y1OQmSSHKDq6tsoD3pW_gDRNXiX2rd0w/edit#slide=id.g4d21a8c2ba_0_11
/wiki/spaces/SCHEM/pages/2453176326
/wiki/spaces/SCHEM/pages/2458419217
Glossary
Manifest - metadata table submitted for datasets
Upload Data
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