> For the complete documentation index, see [llms.txt](https://guide.transmute.industries/verifiable-data-platform/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://guide.transmute.industries/verifiable-data-platform/learning-center/json-ld.md).

# JSON-LD

[JavaScript Object Notation for Linked Data (JSON-LD)](https://www.w3.org/TR/json-ld11/) is a lightweight way to represent linked data that is compatible with the [Resource Description Framework (RDF)](https://www.w3.org/RDF/). This compatibility is very valuable since RDF has been used to represent knowledge and information for a long time, and this allows those representations to be understood by modern software systems.

One major goal and benefit of JSON-LD is its compatibility with JSON. Developers familiar with JSON should be able to quickly understand and modify existing systems to process JSON-LD. The most notable difference between JSON and JSON-LD is the inclusion of the concept of a “[context](https://www.w3.org/TR/json-ld11/#the-context).” This context is used to map terms to [Internationalized Resource Identifiers (IRIs)](https://en.wikipedia.org/wiki/Internationalized_Resource_Identifier), which allows machines and humans to understand not just *what* is communicated in the data, but *what is meant* by the data being communicated.

For example, take the following snippet of JSON:

```
"name": "Jane Austen"
```

While human readers know that “Jane Austen” is a person’s name, a machine does not because we have not defined what kind of data a “name” is. To a machine, the following JSON would be just as valid and sensible:

```
"blorp": "Jane Austen"
```

By adding a context, however, we are able to clarify what we mean by “name”:

```
"@context": {
    "name": "https://schema.org/name"
}
```

This allows both humans *and* machines to understand what is meant by “name,” because we have linked that variable to a shared understanding outlined in Schema.org.

### Linked Data 101

Linked data is “[structured data which is interlinked with other data](https://en.wikipedia.org/wiki/Linked_data)” so that it becomes more useful. [Tim Berners-Lee](https://en.wikipedia.org/wiki/Tim_Berners-Lee), director of the [World Wide Web Consortium](https://en.wikipedia.org/wiki/World_Wide_Web_Consortium) (W3C), coined the term “linked data” in a 2006 design note about the [Semantic Web](https://en.wikipedia.org/wiki/Semantic_Web) project.[\[2\]](https://en.wikipedia.org/wiki/Linked_data#cite_note-DesignIssues-2) The “Semantic Web” refers to a broad vision of the Web as being comprised of linked data.

Generally, supporters of the semantic web have focused on making information available to both humans and machines. This helps search engines, advertisers, and AI-related projects better understand the content on web sites and its potential relationship to visitors of those sites.

Some of the most popular semantic web projects include [Freebase](https://en.wikipedia.org/wiki/Freebase_\(database\)), which was acquired by Google and [Schema.org](https://schema.org/). Schema.org is used by a large variety of companies and organizations across the web to describe

### Traceability Vocab

The [traceability vocabulary](https://w3id.org/traceability) is a W3C CCG Work Item dedicated to applying [W3C Verifiable Credentials](https://www.w3.org/TR/vc-data-model/) and the best industry and academic ontologies to the challenges associated with global supply chain traceability. The vocabulary strives not to reinvent any wheels and instead leverages the best industry ontologies available including [schema.org](https://schema.org/), [GS1 Web Vocabulary](https://www.gs1.org/voc/), and Chemical Entities of Biological Interest ([ChEBI](https://www.ebi.ac.uk/chebi/)).\
\
Leveraging these existing ontologies enables certification authorities to issue semantically unambious claims about supply chain organizations and products that help with transparency and accountability issues associated with product origin and global trade requirements.


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://guide.transmute.industries/verifiable-data-platform/learning-center/json-ld.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.
