cbor-ld-ex 0.1.0

Compact Binary Linked Data with Semantic Reasoning for Constrained IoT Networks

CBOR-LD-ex

Compact Binary Linked Data with Semantic Reasoning for Constrained IoT Networks

CBOR-LD-ex extends CBOR-LD with bit-packed Subjective Logic primitives — compliance status, opinion tuples, operator provenance, and tiered reasoning metadata — enabling edge IoT devices to exchange semantically-rich compliance annotations at a fraction of the cost of JSON-LD.

Built on jsonld-ex and its compliance algebra (Syed et al. 2026).

Key Properties

• 5-byte semantic annotations on constrained devices (vs ~280 bytes in JSON-LD)
• Tiered encoding adapts to device capability: 1-byte headers on MCUs, 4-byte+ on gateways/cloud
• Three formal axioms — backward compatibility, algebraic closure, quantization correctness
• Constrained quantization preserves b + d + u = 1 exactly in the compact representation
• 8 theorems proven bounding quantization error, operator propagation, and constraint preservation

Installation

pip install cbor-ld-ex

Or with Poetry:

poetry add cbor-ld-ex

Optional: CoAP transport

pip install cbor-ld-ex[transport]

Quick Start

from cbor_ld_ex.opinions import quantize_binomial, dequantize_binomial
from cbor_ld_ex.headers import (
    Tier1Header, ComplianceStatus, PrecisionMode
)
from cbor_ld_ex.annotations import Annotation, encode_annotation, wrap_cbor_tag

# Quantize an opinion: 85% belief, 5% disbelief, 10% uncertainty
b_q, d_q, u_q, a_q = quantize_binomial(0.85, 0.05, 0.10, 0.50, precision=8)
# (217, 13, 25, 128) — SL constraint preserved exactly: 217 + 13 + 25 = 255

# Build a Tier 1 annotation (constrained device)
header = Tier1Header(
    compliance_status=ComplianceStatus.COMPLIANT,
    delegation_flag=False,
    has_opinion=True,
    precision_mode=PrecisionMode.BITS_8,
)
ann = Annotation(header=header, opinion=(b_q, d_q, u_q, a_q))

# Encode: 5 bytes total (1 header + 4 opinion)
wire_bytes = encode_annotation(ann)
assert len(wire_bytes) == 5

# Wrap in CBOR tag for interoperability
tagged = wrap_cbor_tag(wire_bytes)

Architecture

Tier 1 (Constrained)     Tier 2 (Edge Gateway)      Tier 3 (Cloud)
┌─────────────────┐      ┌─────────────────────┐    ┌──────────────────────┐
│ 1-byte header   │      │ 4-byte header        │    │ 4-byte + extensions  │
│ 4-byte opinion  │─────>│ Fused opinion         │──>│ Provenance chain     │
│ = 5 bytes total │      │ Operator provenance   │    │ Full audit trail     │
│                 │      │ Source count           │    │ Byzantine metadata   │
└─────────────────┘      └─────────────────────┘    └──────────────────────┘
     ~85% smaller              Fusion + filtering         Full reasoning
     than JSON-LD              at the edge                 reconstruction

Formal Guarantees

Axiom	Property	Guarantee
Axiom 1	Backward Compatibility	Strip annotations → valid CBOR-LD → valid JSON-LD
Axiom 2	Algebraic Closure	Every operator produces valid annotations
Axiom 3	Quantization Correctness	b̂ + d̂ + û = 2ⁿ − 1 exactly

Precision	Max error (b,d)	Max error (u)	Opinion bytes
8-bit	~0.002	~0.004	4
16-bit	~0.000008	~0.000015	8
32-bit	IEEE 754	IEEE 754	16

Development

git clone https://github.com/jemsbhai/cbor-ld-ex.git
cd cbor-ld-ex
poetry install
poetry run python -m pytest tests/ -v

TDD Methodology

This project follows strict test-driven development. Every module has comprehensive tests including property-based testing via Hypothesis.

Project Structure

cborldex/
├── src/cbor_ld_ex/
│   ├── opinions.py       # Quantization codec (Theorems 1–3)
│   ├── headers.py        # Tier-dependent header codec (§5)
│   └── annotations.py    # Annotation assembly + CBOR tagging (§5.3)
├── tests/
│   ├── test_opinions.py  # 38 tests incl. Hypothesis property tests
│   ├── test_headers.py   # Tier 1/2/3 header roundtrips
│   └── test_annotations.py  # Assembly + Axiom 1 verification
├── spec/
│   ├── FORMAL_MODEL.md   # Formal specification v0.1.0-draft
│   └── IMPLEMENTATION_PLAN.md
├── pyproject.toml
└── LICENSE

References

• Syed, M., Silaghi, M., Abujar, S., and Alssadi, R. (2026). A Compliance Algebra: Modeling Regulatory Uncertainty with Subjective Logic. Working paper.
• Jøsang, A. (2016). Subjective Logic: A Formalism for Reasoning Under Uncertainty. Springer.
• Bormann, C. and Hoffman, P. (2020). RFC 8949: CBOR. IETF.
• Shelby, Z. et al. (2014). RFC 7252: CoAP. IETF.
• CBOR-LD Specification (W3C Community Group Draft).
• JSON-LD 1.1 (W3C Recommendation).

License

MIT — see LICENSE.