GCRI · Data and Compute

Data engineering and stewardship

Data engineering, interoperability and stewardship is the second method this platform stewards. It designs how data are collected, described, stored, linked, versioned and shared, so that they can be found, trusted and reused across institutions and over time.

01Register

Data engineering and stewardship on the record.

Method recordSTEM method
  1. MethodData engineering, interoperability and stewardship
  2. StewardData and Compute
  3. Applied inData and Compute
  4. 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 energy, 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.

FAIR data assessment

Datasets are assessed against the FAIR principles using published metrics, and improvements to identifiers, metadata, licences and formats are prioritised.

Interoperable catalogues

Catalogues are described with DCAT and shared vocabularies so that datasets from different agencies can be searched and combined.

Data quality pipelines

Automated checks validate schema, ranges, completeness and consistency at each stage, with failures logged and reported to data owners.

03Geography

Connected activity in the contiguous United States.

Night lights, population density and true-colour imagery over the contiguous United States, from NASA GIBS. Each layer carries its own date.

The interactive map needs JavaScript; the layer list and sources are below.

Layers 3

Connected activity, for this page

Latest available

NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © OpenStreetMap contributors (ODbL) · Natural Earth

Loading the latest NASA imagery.

Drag to move. Ctrl or ⌘ and scroll, pinch or the buttons to zoom; hover for the values under the pointer; reset returns to the region.

Connected activity, framed on the contiguous United States.Satellite and model products as NASA publishes them, each with its own date. They are indicators, not assessments of any place.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · NASA EONET · NASA HLS S30Sources and licences

  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • VIIRS Black Marble night-time lights, NASA Goddard Space Flight Center; distributed by the NASA Level-1 and Atmosphere Archive and Distribution System (LAADS DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Center for International Earth Science Information Network (CIESIN), Columbia University. 2018. Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11. NASA Socioeconomic Data and Applications Center (SEDAC). Licensed under CC BY 4.0. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). doi:10.7927/H49C6VHW. CC BY 4.0
  • VIIRS near-real-time products (flood, land surface temperature, snow cover, corrected reflectance), NASA LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • MODIS land products (vegetation indices, gross primary production, land cover), NASA LP DAAC and LANCE; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • ASTER GDEM is a product of METI and NASA (ASTER Global Digital Elevation Model V003, NASA LP DAAC); imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). Cite as: NASA/METI/AIST/Japan Spacesystems and U.S./Japan ASTER Science Team (2019). ASTER Global Digital Elevation Model V003. doi:10.5067/ASTER/ASTGTM.003. NASA open data
  • Made with Natural Earth. Free vector and raster map data @ naturalearthdata.com. Public domain
  • © OpenStreetMap contributors (ODbL), via NASA GIBS (coastlines, boundaries, roads and place names). Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
  • Context on the globe and flat map: coastlines, boundaries, roads and place names from NASA GIBS reference layers (OpenStreetMap data, ODbL, © OpenStreetMap contributors); Blue Marble imagery as an optional base; 3D terrain and the elevation read-out from the ASTER GDEM elevation colour index (5 m to 200 m classes, exaggerated for legibility). Boundaries are drawn as published and imply no position on any territory.
  • Live events: NASA Earth Observatory Natural Event Tracker (EONET); events are indicative and keep their original source links.
  • Observed (EO): NASA HLS S30 (contains modified Copernicus Sentinel data 2026). We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • NASA GIBS: We acknowledge the use of imagery provided by services from NASA's Global Imagery Browse Services (GIBS), part of NASA's Earth Science Data and Information System (ESDIS).
  • Optional layers (5 sources in the layer list: live, forecast, observed and context) print their provider credit on the map and here when switched on; forecasts are model output and derived indices are estimates.

Layers and dates

  • Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Land cover type (IGBP), yearly: MODIS Terra and Aqua land cover (MCD12Q1), NASA LP DAAC · 2024
  • Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
  • Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026

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
Repository and catalogue metadataFAIR assessmentOBSERVED
Schema and vocabulary registriesInteroperabilityPublished statistics
Validation logsQualityOBSERVED
05Twin and cascade simulator

Model data engineering and stewardship as a system. Run the cascade.

Assembled from the Nexus Standards area profile Digital, telecom and platforms: the hazards it names, the systems and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full System Builder.

Hazards

Controls

  • NS-0 Constitution and principles
  • NS-9 Contextual UNIs (deployments, instances, programme instances)
  • NS-11 Verification and monitoring (evidence, attestations, zero-trust conformance observation)
  • NS-12 Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)
  • NRS-H86 Hazard family: Telecom and data-centre failure (NHS-1 infra.digital)
  • NRS-H54 Hazard family: Signal and platform disruption (NHS-1 cyber.platform)
  • NRS-H93 Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)
  • NRS-H94 Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)
  • NRS-T8 Software and supply-chain integrity risk
  • NRS-X6 Cyber and digital security risk

Observation

  • ITU DataHub ICT indicators (listed for reference)
  • World Development Indicators (listed for reference)
  • WMO Alert Hub and Register of Alerting Authorities (listed for reference)
  • Proportion of population covered by a mobile network, by technology
  • Fixed broadband subscriptions per 100 inhabitants, by speed
  • Individuals using the Internet (% of population)
  • Number of people per 100,000 that are covered by early warning information through local governments or through national dissemination mechanisms

Example geography

  • North America: 243 hexagonal cells
  • Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
  • Vegetation disturbance alerts, 30 m (OPERA DIST-ALERT), NASA GIBS
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
Metadata completenessRequired metadata fields are checked for every dataset
Identifier resolutionPersistent identifiers are tested to resolve
Validation coverageQuality checks cover every critical field

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

07Methods and evidence

How data engineering and stewardship 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.

Datasets and provenance

The data classes behind data engineering and stewardship and what is recorded about each before it is used.

Data classProvenance recordedResolution statedLicence checked
Satellite imagery, optical and radarsensor, processing level, acquisition datepixel size and revisitper scene
Reanalysis and climate model outputmodel, experiment, member, versiongrid and time stepper release
In-situ sensors and gaugesstation, instrument, calibration recordpoint and sampling rateper network
Population and asset exposuremethod, vintage, input sourcescell size and unitper release
Boundaries and reference geographyproducer, edition, datescaleper edition
Lineage
W3C PROV record from source to figure
Principles
FAIR: findable, accessible, interoperable, reusable
Gaps
shown as missing, never filled silently
Data classes and the provenance fields recorded for each; a dataset is listed by name only once its licence admits the use.
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
09Process

How the process runs.

Process

Data engineering and stewardship: 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.

10Stewardship

Who maintains the method.

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

11Questions

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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Editors and the expert reviewers named on each article decide what we publish. Funders and partners do not review or approve articles before publication.

Licence

Articles: CC BY 4.0. Figures, maps, twins and data: CC BY 4.0. Other uses: ask through the permissions form.