JSON-LD

isComparandOf https://sookocheff.com/post/api/on-choosing-a-hypermedia-format/

Features

"@context": {
  "": "http://example.com/default/",
}

is the same as, I think:

"@context": "http://example.com/default/"

attach a contextual document in the response

"Provide a context in an HTTP Link header

A method for attaching a JSON context to a plain JSON object via an HTTP Link header is described by the JSON-LD specification, section 4.9, Interpreting JSON as JSON-LD. In short, a plain JSON file that is passed via HTTP can be accompanied by a separate JSON-LD context document. The URI of the JSON-LD context document is passed via an HTTP Link header, using the link relation http://www.w3.org/ns/json-ld#context."

Keywords

@id (Private) keyword allows you to give a node a URI
@context (Private) lets you define vocabulary references
- this is more versatile than turtle and other RDF formats, because have more granularity and can "define terms", so no prefixing is required
@import (Private) "Context files are imported/re-used by creating the context as an array where the first value(s) is the path(s) to the imported context, followed by an object" (https://www.w3.org/TR/json-ld-syntax/#the-context).
- https://www.w3.org/TR/json-ld/#imported-contexts
Each of the JSON-LD keywords, except for @context (Private), may be aliased to application-specific keywords.
@type (Private) specifies the subject's class
- objects can have multiple types, e.g. "@type": ["Person", "Author"]
@graph (Private) allows multiple subjects in one document
@included (Private)

Best Practices

https://stackoverflow.com/questions/42398060/json-ld-to-normal-json
http://niem.github.io/json/reference/json-ld/context/ discuss context, expansions, and contractions

vs RDF

In JSON-LD properties can be IRIs or blank nodes whereas in RDF properties (predicates) have to be IRIs. This means that JSON-LD serializes generalized RDF Datasets.
In JSON-LD lists are part of the data model whereas in RDF they are part of a vocabulary, namely [RDF11-SCHEMA].
RDF values are either typed literals (typed values) or language-tagged strings whereas JSON-LD also supports JSON's native data types, i.e., number, strings, and the boolean values true and false. The JSON-LD Processing Algorithms and API specification [JSON-LD-API] defines the conversion rules between JSON's native data types and RDF's counterparts to allow round-tripping.

Streaming

https://www.w3.org/TR/json-ld11-streaming/

@chatgpt.4

what's the best practices for referencing other entities/objects in json-ld ChatGPT

In JSON-LD, best practices for referencing other entities or objects include:

Use of @id and @type Properties: Assign a unique identifier (@id) to each entity and specify its type (@type). This helps in clearly distinguishing and referencing different entities.

Consistent and Descriptive Identifiers: Ensure identifiers are consistent and descriptive across your JSON-LD data. This aids in readability and maintainability.

Utilizing Well-Known Contexts: Reference standard vocabularies or contexts (like schema.org) for common types and properties. This enhances compatibility and interoperability with other systems.

Embedding vs. Linking: Decide whether to embed other objects directly or just link to them using their @id. Embedding can make the data self-contained, while linking keeps the JSON-LD document concise.

Handling Multiple References: When referencing multiple entities, use an array of objects or identifiers. This keeps the structure organized and easy to parse.

Contextualizing Relationships: Use descriptive property names that accurately represent the relationship between entities. This adds semantic clarity to your data.

Maintaining JSON-LD Best Practices: Apart from referencing, follow general JSON-LD best practices like using a compact and readable format, validating your JSON-LD, and ensuring it aligns with the intended semantic meaning.

Documentation: Document how references and entities are structured and related in your JSON-LD. This is crucial for others who will use or extend your data.

These practices help in creating a well-structured, understandable, and semantically rich JSON-LD document, facilitating better data integration and usage.

Resources

References:

Children

JSON-LD-star

Backlinks