JSON-LD 1.2 and Beyond
Extensions for machine learning data exchange.
jsonld-ex is a reference implementation of proposed JSON-LD 1.2 extensions that address twelve gaps in the current specification for machine learning workflows: confidence tracking via Subjective Logic, provenance, security hardening, native validation, vector embeddings, temporal modeling, GDPR compliance, and FHIR R4 clinical interoperability.
This site lets you exercise the extensions live in your browser. Every demo runs the official @jsonld-ex/core package — the same TypeScript implementation that has 100% feature parity with the Python reference.
§ 1Install
pip install jsonld-exnpm install @jsonld-ex/core§ 2Quick start
from jsonld_ex import annotate, validate_node, Opinion, cumulative_fuse
# Annotate a value with AI/ML provenance
name = annotate(
"John Smith",
confidence=0.95,
source="https://ml-model.example.org/ner-v2",
method="NER",
)
# Validate against a shape
shape = {
"@type": "Person",
"name": {"@required": True, "@type": "xsd:string"},
"age": {"@type": "xsd:integer", "@minimum": 0, "@maximum": 150},
}
result = validate_node({"@type": "Person", "name": "John", "age": 30}, shape)
assert result.valid
# Formal confidence algebra (Subjective Logic)
a = Opinion(belief=0.8, disbelief=0.1, uncertainty=0.1)
b = Opinion(belief=0.7, disbelief=0.05, uncertainty=0.25)
fused = cumulative_fuse(a, b)§ 3Explore the extensions
Each section pairs a runnable demo with the equivalent Python call.
- 1. Annotation & provenanceannotate, getProvenance, filterByConfidence
- 2. @shape validationvalidateNode — required, type, min/max, pattern
- 3. Backward compatibilityStrip extensions to recover valid JSON-LD 1.1
- 4. @integrity & allowlistSRI-style context hashing + DNS-poisoning defense
- 5. @vector embeddingsVector container + cosine similarity
- 6. FHIR R4 interopAnnotated clinical resources
§ 4Cite
@inproceedings{syed2026jsonldex,
title = {JSON-LD 1.2 and Beyond: Extensions for Machine Learning Data Exchange},
author = {Syed, Muntaser and Silaghi, Marius and Abujar, Sheikh
and Alssadi, Rwaida and Khushbu, Sharun Akter},
booktitle = {Proceedings of the 39th International Florida Artificial
Intelligence Research Society Conference (FLAIRS-39)},
year = {2026},
}§ 5Authors
Muntaser Syed, Marius Silaghi, Sheikh Abujar, Rwaida Alssadi, Sharun Akter Khushbu — Florida Institute of Technology · University of Alabama at Birmingham · Daffodil International University.