Trusted Data

Trust in data means being able to explain where it came from.

Trusted Data is not a label for every stream. It is a property engineered through identity, provenance, integrity and auditability, proportionate to risk and the required evidential value.

Two engineers verify a sensor and its integrity and provenance chain on laboratory monitors.

From measurement to evidence

Trust starts at the measurement bench.

Device identity, timestamps, integrity and transformations are verified alongside the signal quality that originates the record.

  1. 01Measure
  2. 02Identity
  3. 03Audit

TRUST CHAIN

Trust is built across the entire chain.

A record is verifiable only when the measurement, device identity, transformations and access remain connected by coherent evidence.

TRUST MODEL / 01—05Linked evidence
  1. 01
    MeasureSignal & context
  2. 02
    IdentityDevice & credentials
  3. 03
    IntegritySignature & fingerprint
  4. 04
    LineageRules & versions
  5. 05
    VerifyEvidence & audit

FOUNDATIONS / 01—04

Four properties, designed together

01

Provenance

Origin, device, context, software version and transformations remain reconstructable.

02

Identity

Devices and services are authenticated; producers, transformers and readers are distinguishable.

03

Integrity

Signatures, hashes, protected transport and controls prevent or expose tampering.

04

Auditability

Events, access and transformations create evidence aligned with retention policy.

FIT / NOT FASHION

Where it is relevant

The required rigour depends on the consequences of contested data, not on the most fashionable technology.

  • 01Compliance and inspection
  • 02Disputes or accountability
  • 03Supply chain and chain of custody
  • 04Measurements shared across organisations
  • 05Decisions based on contestable data
  • 06Maintenance and safety of critical assets

TRUST DELIVERABLES

What we design in practice

The solution may use signatures, hashes, append-only logs or notarisation: the choice follows the trust model and the required evidential value.

01 / IDENTITY

Identity registry

Provisioning, credentials, roles, revocation and device-to-asset association.

02 / INTEGRITY

Signatures and fingerprints

Canonicalisation, signatures or hashes, plus transport and storage protection.

03 / LINEAGE

Transformation chain

Reconstructable software versions, rules, processing steps and ownership.

04 / VERIFY

Verification and audit

APIs, receipts, reports and procedures for checking a record without exposing secrets.

BOUNDARY

What we do not promise

A blockchain or immutable ledger cannot make an incorrect source measurement true. Measurement quality, device identity, firmware security and transformation governance come first. Notarisation technology is a later decision, not the starting point.

VERIFY

Verify an existing record

Check a record through its identifier and view its inclusion status, date, hash and associated signature.

Explore

Projects

Trusted Data starts with the system producing the measurement.

The Projects section shows contexts where identity, timestamps, transformations and accountability may become part of the architecture.

Explore projects and applications

Data that must become verifiable?

Start from the trust model, not from blockchain.

We define who produces the data, how it is transformed, what evidence is required and how it can be verified over time.

Discuss the trust model