GCRI · Foundry

Data engineering at Foundry

Data engineering decides whether evidence from different sectors can be combined at all. In this field it covers ingestion, validation, standardisation, provenance and stewardship: source passports, schemas and ontologies, frozen data cuts, and lineage that lets a correction reach every product built on the corrected source.

01Register

Data engineering at Foundry on the record.

Method recordSTEM method
  1. MethodData engineering, interoperability and stewardship
  2. Applied inFoundry
  3. Canonical pageSTEM Commons
02Application

What data engineering, interoperability and stewardship does here.

Data engineering, interoperability and stewardship cover the pipelines, standards and governance that make data usable and trustworthy. They determine whether information from different sectors can be combined for joint risk assessment. In data and compute and methods and modelling, sound data engineering allows hazard, exposure and financial data to be linked consistently. It supports transparent and repeatable analysis of interconnected risk. The canonical description is on the STEM Commons.

Validation at the ingest boundary

Each incoming batch is checked against its declared schema, units and code lists before it is accepted. Failures are quarantined with a reason, and the original is retained unchanged beside the standardised record.

Frozen data cuts for reproducible products

Indices and loss estimates are computed from versioned, immutable snapshots, so a product can be re-run months later from exactly the data that produced it.

Correction impact through lineage

When a source owner issues a correction, the lineage graph lists every derived table, map and index that depends on it, and those products are marked stale until recomputed.

03Methods and evidence

How Data engineering at Foundry is modelled, measured and tested.

The model, its assumptions, its data and its uncertainty, in the form a scientist or engineer would check. Structures follow published methods. The values drawn are illustrative, not findings.

Model, equations and assumptions

The model structure used for Data engineering at Foundry, the assumptions it makes and how each is tested.

Risk of element iRi = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacity
Expected annual lossEAL = ∑k pk · Lkover events k with annual probability pk
Coupled systemsxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error
AssumptionWhy it is madeHow it is tested
Hazard and exposure are independent within an eventKeeps the loss integral tractableCompare with a copula fit on joint records
Couplings are linear near the operating pointLets shocks propagate through APerturb beyond the linear range and compare
Vulnerability curves transfer between placesLocal curves are rarely availableValidate against observed losses where they exist
Inputs
versioned datasets with provenance
Outputs
distributions, never single numbers
Code
released with the model card and tests
Reproduction
same data, code, environment and seed
Standard risk and state-space formulations; the assumptions listed are typical of the method, stated for review, not results.
FAIR guiding principles · GO FAIR and FORCE11W3C PROV · World Wide Web ConsortiumGuidance on consistent treatment of uncertainties · IPCCCEOS Analysis Ready Data · Committee on Earth Observation Satellites
04Data

What the method consumes.

Datasets and records used by data engineering, interoperability and stewardship on this platform, with the role each plays and the label its values carry. Sources are listed in the source register.

DataRoleLabel
Source passportsOwner, licence, cadence, authority class and limitsDECLARED
Schemas and ontology shapesValidation at ingestDECLARED
Pipeline run logsLineage and failure analysisOBSERVED
Published statistics and registersAuthoritative reference valuesPublished statistics
Catalogue metadata in DCAT and STACDiscovery and reuseDECLARED
05Process

How the process runs.

Process

Data engineering at Foundry: Build, sign and accept

An admitted mission becomes a cycle project; the build is pinned, verified and signed, and the Global Risks Forum (GRF) records acceptance for exercise, not permission to deploy.

  1. 01 Request and sources

    1. 01Admitted mission becomes a cycle projectRecord · Universe to FoundryAn admitted mission becomes a cycle project with a decision case.
    2. 02Qualify data sources and resourcesStep · the Global Centre for Risk and Innovation (GCRI)GCRI qualifies data sources and resource offers and builds the scenario models. An offer is not an allocation.
  2. 02 Build and verify

    1. 03Source snapshotRecord · NXS-FAC (blueprints, builds and signing)The snapshot pins the commit, dependencies and generator versions.
    2. 04Build contractRecord · NXS-FAC (blueprints, builds and signing)The build contract declares the artefact kind, environment and reproducibility envelope.
    3. 05Integrate and buildModel · GCRIGCRI integrates software and data, signs builds, and tests security and interoperability.
    4. 06Verification suiteGate · NXS-FAC (blueprints, builds and signing)Required and advisory checks stay separate. Reproducibility needs pinned inputs, declared nondeterminism and independent rebuilds.
  3. 03 Sign and admit

    1. 07Sign the exact artefactStep · NXS-FAC (blueprints, builds and signing)NXS-FAC builds, attests and requests a signature via a scoped signer identity. It holds no key material.
    2. 08Package admissionStep · NXS-NXQ (software, models and capability lifecycle)NXS-NXQ receives the signed package and keeps admission evidence that binds the task, data class, evaluation suite and expiration.
  4. 04 Accept

    1. 09Core Build ReportRecord · GCRIThe Core Build Report is the go or no-go record. Universe assembles the Core and holds the decision for the exercise.
    2. 10G3 · Build accepted for exerciseGate · The Global Risks ForumGRF records whether the build is accepted for exercise. A signed build or release candidate is not permission to deploy to production.

The programme year · NXS-FAC · UniverseDesigned programme process, not a record of operation. No cycle has run and every programme is at service level R0. A gate is a programme decision, never a public-authority approval, certification or deployment authorisation. The record order follows the Builds and Releases room lists of NXS-FAC.

06Validation

How results are checked.

Pipelines are tested with automated quality checks, schema validation and lineage audits. Reconciliation against source systems confirms completeness.

CheckHow it is done
Reconciliation with the sourceRow counts, totals and keys are compared with the source system after each load
Schema and unit validationRecords are tested against shapes, controlled vocabularies and CF or SI units before acceptance
Lineage auditA sample of published figures is traced back to the original records and the transformation steps are re-run
Licence checkEvery source and derived product carries a licence that permits its intended use

Incompatible standards, missing metadata and restrictive licences block integration. Legacy systems and undocumented transformations introduce silent errors.

08Stewardship

Who maintains the method.

Data and Compute stewards data engineering, interoperability and stewardship for the Consortium and reviews how it is applied across platforms.

10Questions

Questions and answers.

What are the limits of data engineering, interoperability and stewardship in this field?
Incompatible standards, missing metadata and restrictive licences block integration. Legacy systems and undocumented transformations introduce silent errors.
How are results checked?
Pipelines are tested with automated quality checks, schema validation and lineage audits. Reconciliation against source systems confirms completeness.
Are the values on this page real?
The data names, roles and checks are real descriptions of practice. The canvas shows a design of the method’s use, not a run; no result is reported here.
Where else is this method applied?
The canonical method page lists every platform that applies it.
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Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.

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