GCRI · Data and Compute
Data and Compute
Data infrastructure, national computational capacity and advanced computing in service of public knowledge. Data and Compute is an established platform of The Global Centre for Risk and Innovation.
- STEM methods
- 7
- Canonical methods this field applies
- Topics
- 8
- Subject pages in the field
- Counterparts
- 0
- Platforms in shared fields across the network
- Report series
- 2
- Reports series it contributes to
The workspace for Data and Compute.
Compute facility console
HPC facility · Month 3 · Example interface, not a record
- Utilisation, % of nodes91Active
- PUE1.35Normal
- WUE0.2l/kWhWatch
- Queue wait, p501.7h
Energy by use
- IT load
- Cooling
- Other
Allocations
| Climate ensemble | 216 | 918 | Near quota |
| Flood modelling | 240 | 413 | Within |
| Genomics pipeline | 152 | 283 | Near quota |
Data and Compute · Compute facility console. Compute facility console: example names and illustrative values, not a record.
The areas of data and compute this platform takes on.
Data and Compute studies the infrastructure behind public knowledge: data systems that serve the public interest, high-performance, cloud and edge computing, the chips they run on, the rights and trust that govern data, reproducible pipelines, the energy and water computing uses, and fair access to research infrastructure. Its pages set out the standards, measures and evidence for each, with every value labelled and every limit stated. It prepares evidence; research infrastructures, statistics offices, regulators and governments decide.
Public-interest data infrastructure
Statistical systems, registries, open data portals and research repositories that society relies on.
High-performance computing
Supercomputers and the science, forecasting and engineering that depend on them.
Cloud and edge systems
Distributed computing from hyperscale cloud to devices at the network edge, and its dependencies.
Chips and semiconductors
The processors and accelerators national computing capacity depends on, and their supply.
Data rights and trust
Privacy, consent, data sovereignty and governance that decide who may use data and how.
Reproducible pipelines
Workflows, provenance and versioning that let results be rerun and checked.
Compute, energy and water
Electricity, cooling and water used by data centres and supercomputers, and their efficiency.
Research infrastructure access
Who can use national and international computing and data facilities, and on what terms.
A cascade through interdependent networks.
A hazard footprint takes out co-located assets in every layer; fragmentation, dependency between layers and overload of the survivors then spread the failure. The 3D view separates the layers by depth. Teaching model with stated illustrative values, not a prediction. The map on this page shows The contiguous United States; the model itself is not tied to a place.
Controls
- Assets per layer
- 18
- Hazard footprint
- 8% of area
- Assets that depend on another layer
- 60%
- Spare capacity (tolerance)
- 30%
Readouts
- Assets hit by the hazard
- 7%
- Assets still working
- 56%
- Amplification of the initial damage
- 6.0 times
- Steps to settle
- 4
Numbers, methods and sources
| Step | Data centres working (%) | Networks working (%) | Power working (%) |
|---|---|---|---|
| 0 | 83 | 94 | 100 |
| 1 | 61 | 89 | 94 |
| 2 | 61 | 78 | 72 |
| 3 | 61 | 72 | 44 |
| 4 | 61 | 72 | 33 |
Methods
- Interdependent networks Buldyrev and others (2010), Catastrophic cascade of failures in interdependent networks, Nature 464
- Overload cascades Motter and Lai (2002), Physical Review E 66
- Betweenness load Brandes (2001), Journal of Mathematical Sociology 25
- Multilayer networks Kivela and others (2014), Journal of Complex Networks 2
- Infrastructure interdependencies Rinaldi, Peerenboom and Kelly (2001), IEEE Control Systems 21(6)
- Uncertainty fan (parameter Monte Carlo) Spiegelhalter, Pearson and Short (2011), Visualising uncertainty about the future, Science 333
- One-at-a-time sensitivity (tornado) Saltelli and others (2008), Global Sensitivity Analysis: The Primer, Wiley
Data
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
- Major roads Natural Earth
- Railways Natural Earth
- Seaports Natural Earth
- Airports Natural Earth
- Urban extents Natural Earth
- Night lights tonight, outages (VIIRS Day/Night Band) NASA/NOAA VIIRS (Suomi NPP) · register nasa.gibs.context-live-layers
- Natural events (NASA EONET) NASA EONET · register nasa.eonet.events
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Data and Compute in Foundry
- Tested at Data and Compute in Universe
- Codified in Data and Evidence in Standards
- Published in Data and Compute in Reports
- Taught in Faculty of Technology and Digital Systems in Academy
The questions this field works on.
Public interest data infrastructure
Dataspaces and interoperable evidence.
TopicHigh performance computing
HPC/GPU workloads and scientific compute.
TopicCloud and edge systems
Hybrid, local and sovereign computing options.
TopicChips and semiconductors
Critical compute hardware and supply chains.
TopicData rights and trust
Data access, licensing and privacy.
TopicReproducible pipelines
Pipelines, models and experiment provenance.
TopicCompute energy water
Infrastructure impacts and sustainability.
TopicResearch infrastructure access
Cost and governance of scientific facilities.
Model Data and Compute 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
- Sea-ice loss
- Coastal erosion (set off downstream)
- Biodiversity loss (set off downstream)
- Arctic winter sea-ice collapse (set off downstream)
- Polar vortex disruption (set off downstream)
Systems and couplings
- Digital, telecom and platforms
- Energy utilities and grids Coupling
- Media and information Coupling
- Finance, insurance and capital markets Coupling
- Defence and civil protection Coupling
Controls
NS-0Constitution and principlesNS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-12Software, model and AI/ML artefacts (supply chain, model cards, dataset sheets)NRS-H86Hazard family: Telecom and data-centre failure (NHS-1 infra.digital)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H93Hazard family: Identity, trust and cryptographic failure (NHS-1 cyber.identity)NRS-H94Hazard family: Systemic cyber events (NHS-1 cyber.systemic-cyber)NRS-T8Software and supply-chain integrity riskNRS-X6Cyber 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
What the work is read against.
The platform does not set standards. It reads its evidence against the frameworks that competent bodies have adopted, so a finding can be placed where a decision-maker already works.
| Framework or standard | Body | What it sets |
|---|---|---|
| FAIR Guiding Principles for scientific data management and stewardship | GO FAIR and the FORCE11 community | Principles to make data findable, accessible, interoperable and reusable |
| CARE Principles for Indigenous Data Governance | Global Indigenous Data Alliance | Collective benefit, authority to control, responsibility and ethics for Indigenous data |
| Fundamental principles for national statistical systems (resolution 68/261) | United Nations General Assembly | Professional independence, confidentiality and quality principles for national statistics |
| Recommendation on Enhancing Access to and Sharing of Data | OECD Council | Principles for trusted data access and sharing across sectors |
| General Data Protection Regulation | European Union | Rules for processing personal data, rights of data subjects and international transfers |
| Data Governance Act and Data Act | European Union | Frameworks for data intermediaries, altruism and fair access to data from connected products |
| Global Digital Compact | United Nations General Assembly | Commitments on digital inclusion, data governance and AI governance |
| ISO/IEC 30134 series data centre key performance indicators | ISO and IEC | Definitions of power usage effectiveness, water usage and other data centre metrics |
| Data Catalog Vocabulary (DCAT) | World Wide Web Consortium (W3C) | A standard vocabulary for describing datasets in catalogues |
The sector signature of Data and Compute.
The sectors Data and Compute touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Energy and its partners
Energy gives power for transport and telecoms to infrastructure (0.8), pumping and treatment to water (0.5) and fertiliser, machinery and cold chains to food (0.5).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Energy → Infrastructure · power for transport and telecoms0.8
- Water → Energy · cooling water and hydropower0.6
- Water → Food · irrigation0.8
- Infrastructure → Water · pipes, dams and treatment works0.6
What Data and Compute does.
Data infrastructure is the set of systems, standards and institutions that collect, store, describe, govern and share data, together with the computing that processes it. Data and Compute covers public data systems, HPC, cloud and edge, chips, data rights, reproducible pipelines, energy and water, and research access. Research infrastructures, statistics offices and governments decide.
Its community
Data engineers; HPC specialists; cloud architects; university compute teams.
Its methods
Data provenance; compute capacity planning; interoperable pipelines.
Its outputs
Data governance engineering briefs; compute readiness maps; reproducible workflows.
How Data and Compute 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 and Compute and what is recorded about each before it is used.
| Data class | Provenance recorded | Resolution stated | Licence checked |
|---|---|---|---|
| Satellite imagery, optical and radar | sensor, processing level, acquisition date | pixel size and revisit | per scene |
| Reanalysis and climate model output | model, experiment, member, version | grid and time step | per release |
| In-situ sensors and gauges | station, instrument, calibration record | point and sampling rate | per network |
| Population and asset exposure | method, vintage, input sources | cell size and unit | per release |
| Boundaries and reference geography | producer, edition, date | scale | per edition |
- Lineage
- W3C PROV record from source to figure
- Principles
- FAIR: findable, accessible, interoperable, reusable
- Gaps
- shown as missing, never filled silently
Model, equations and assumptions
The model structure used for Data and Compute, the assumptions it makes and how each is tested.
Ri = f(Hi, Ei, Vi, Ci)hazard, exposure, vulnerability and coping capacityEAL = ∑k pk · Lkover events k with annual probability pkxt+1 = A xt + B ut + εtA carries the couplings, u the shock, ε the error| Assumption | Why it is made | How it is tested |
|---|---|---|
| Hazard and exposure are independent within an event | Keeps the loss integral tractable | Compare with a copula fit on joint records |
| Couplings are linear near the operating point | Lets shocks propagate through A | Perturb beyond the linear range and compare |
| Vulnerability curves transfer between places | Local curves are rarely available | Validate 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
What Data and Compute studies, and who governs data and infrastructure.
Data and Compute, studies the infrastructure behind public knowledge: public-interest data systems, high-performance and cloud computing, chips, data rights, reproducible pipelines and the energy and water computing uses. Research infrastructures, statistics offices, regulators and governments decide; the platform prepares evidence.
Capacity and energy figures shown here are illustrations unless sourced on the page. No hardware specifications are summed into performance claims.
Energy now in the contiguous United States.
Night lights, population density and land cover 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
Energy now, for this page
About this layer
- Evidence
- Observed
- Source
- VIIRS Black Marble (VNP46A2) (NASA LAADS DAAC)
- Provider
- NASA LAADS DAAC
- Licence
- NASA open data
- Vintage
- daily; Satellite radiance, corrected for moonlight and atmosphere
- Newest at build
- 2026-10-12
- Resolution
- about 500 m grid
- Uncertainty
- Satellite night-time radiance for the date shown; lights are a proxy for electricity use and outages, not a measurement of supply or access.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Estimated
- Source
- Gridded Population of the World v4.11 (NASA SEDAC (CIESIN, Columbia University))
- Provider
- NASA SEDAC (CIESIN, Columbia University)
- Licence
- CC BY 4.0
- Vintage
- null; Census-based estimate, static (2020)
- Resolution
- about 1 km grid
- Uncertainty
- Census-based estimate of people per square kilometre in 2020, shown as exposure context; not a count of people affected by any hazard.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest month GIBS publishes)
- Source
- MERRA-2 (NASA GMAO / GES DISC)
- Provider
- NASA GMAO / GES DISC
- Licence
- NASA open data
- Vintage
- monthly; Reanalysis model; latest month GIBS publishes
- Newest at build
- 2026-07-01
- Resolution
- about 2 km grid
- Uncertainty
- Reanalysis model estimate of monthly mean incoming sunlight over land; an indicator of solar resource, not a site yield assessment.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed
- Source
- VIIRS NOAA-20 corrected reflectance (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite image
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite image. Satellite or model raster as the provider publishes it. Clouds, swath gaps and retrieval error leave gaps and noise; values are indicators, not measurements at a place.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled (latest year GIBS publishes)
- Source
- MODIS Terra and Aqua land cover (MCD12Q1) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- yearly; Satellite classification; latest year GIBS publishes
- Newest at build
- 2024-01-01
- Resolution
- about 500 m grid
- Uncertainty
- Satellite land cover classes for the year shown, including croplands; a classification with known errors, not a farm register.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- VIIRS NOAA-20 (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite retrieval; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 1 km grid
- Uncertainty
- Satellite skin temperature of the ground on the day shown, an indicator of cooling demand; not air temperature or a heat warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
Keyboard, with the map focused
Hold Ctrl or ⌘ and scroll to zoom
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.
Energy now, 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/NOAA VIIRS · NASA JPL OPERA DIST-ALERTSources 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
- MERRA-2 reanalysis, NASA Global Modeling and Assimilation Office; distributed by the NASA GES DISC; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into hexagonal cells where shown (modified). NASA open data
- 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/NOAA VIIRS (Suomi NPP). 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).
- Observed (EO): NASA JPL OPERA DIST-ALERT (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).
- Past year, daily temperature (ERA5 via Open-Meteo): Contains modified Copernicus Climate Change Service information 2026.
- Past year, daily temperature and sunshine (NASA POWER): These data were obtained from the NASA Langley Research Center (LaRC) POWER Project funded through the NASA Earth Science/Applied Science Program..
- Weather data by Open-Meteo.com (https://open-meteo.com/), licensed under CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/).
- Optional layers (10 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
- Incoming sunlight at the surface over land, monthly mean: MERRA-2, NASA GMAO / GES DISC · July 2026
- 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
- Land surface temperature, day: VIIRS NOAA-20, NASA LANCE · 13 Oct 2026
Data and compute serve every domain, and draw on two of them.
- WaterHow this field couples to itData centres need cooling water in some designs and locations.
- EnergyHow this field couples to itComputing load is a growing share of electricity demand on some grids.
- FoodHow this field couples to itAgricultural statistics and Earth observation pipelines feed food monitoring.
- HealthHow this field couples to itHealth data infrastructure must protect privacy while enabling surveillance and research.
- BiodiversityHow this field couples to itBiodiversity data aggregators depend on open standards and long-term funding.
Where data and compute evidence goes.
Infrastructure studies are designed for the Strategic Systems series and pipeline methods for the Methods and Technical series. Datasets would carry metadata under NS-3b of the proposed Nexus Standards.
- Research infrastructures can share access and usage policies.
- Statistics offices can propose data stewardship collaborations.
- Engineers can contribute reproducibility reviews.
Public knowledge now runs on infrastructure few people see.
Weather forecasts, climate projections, epidemiological models, satellite analysis and much of modern science depend on large datasets and serious computing. So do the risk models that governments and institutions use to make decisions. That infrastructure is concentrated, energy-hungry and fragile in ways that are rarely discussed outside specialist circles.
Advanced computing depends on a short chain of specialised hardware. The most capable processors and accelerators are designed by a few firms and manufactured in a handful of fabrication plants, using equipment and materials from an equally concentrated set of suppliers. Disruption anywhere in that chain, from a natural hazard near a fabrication cluster to export restrictions, can delay research and public services for years.
Computing also depends on energy and water. Large data centres and supercomputers draw substantial, continuous power and need cooling, often with water. As demand for AI training and inference grows, data centres become significant loads on local grids and on water resources, and siting decisions start to shape energy planning. Meanwhile, much public-interest data is locked in incompatible formats, unclear licences or systems that cannot share it securely, so the same evidence is collected several times and still cannot be combined when it matters.
When these weaknesses combine, the result is a quiet systemic risk: a country or research community that cannot run its own models in a crisis, cannot reproduce the analysis behind a decision or cannot share data across borders and institutions fast enough to act.
Engineering evidence for data and compute capacity.
Data and Compute studies data and computing as infrastructure for public knowledge. It is distinct from the Foundry product portal: it does the engineering science, not the product delivery.
Data governance engineering briefs
How provenance, licensing, access control and interoperability can be built into data systems rather than added afterwards.
Compute readiness maps
Methods for describing what computing capacity a country or research community has, needs and depends on.
Reproducible workflows
Patterns for pipelines whose results can be rerun, checked and corrected.
Methods include data provenance, compute capacity planning and interoperable pipelines. The platform does not allocate compute, host data for third parties or sell cloud services.
Grounded in named methods and linked across the Consortium.
Data and Compute stewards two STEM methods for the Consortium: high-performance, cloud and edge computing and data engineering, interoperability and stewardship. It also applies cybersecurity and cryptography, optimisation and operations research, physics and quantum science, energy generation, storage and grid technology and power systems engineering. Foundry systems serving the field include NXS-COR (compute, nodes and runtimes), the secure compute and edge backbone, and NXS-NET (network topology and continuity) for connectivity and continuity.
Within GCRI it works closely with Energy Nexus on the electricity demand of computing. Counterparts at the other institutions are added as their platforms in this field are mapped; the governance of data and digital systems is convened by The Global Risks Forum (GRF) at AI and Digital Governance. See counterparts and the Data and compute field gateway.
Built on named science, technology, engineering and mathematics.
Every claim on Data and Compute rests on methods with a canonical page in the STEM Commons, so readers can see what a finding depends on and where its limits lie.
How work moves in this field.
A question becomes evidence, a governed build, an organised community, a controlled test, a reviewed publication and, finally, a decision taken by the competent authority under its own rules.
- Question Universe National, regional or institutional priority. Question in Data and Compute
- Evidence Foundry STEM foundation of the platform. Evidence in Data and Compute
- Build Foundry Foundry. Build in Data and Compute
- Organise Universe Nexus ecosystem. Organise in Data and Compute
- Test Universe Universe (independent site). Test in Data and Compute
- Publish Reports Reports. Publish in Data and Compute
- Decide Competent authority Competent authorities and institutions, through NXS-RLS (participants, agreements and handoffs). Decide in Data and Compute
- Renew Universe Corrections and the next annual agenda. Renew in Data and Compute
Each step of the cycle in the pillar it runs in; the decision stays with the competent authority, outside the programme.
- Labs
- Foundry
- Universe
- Nexus Standards
- Reports
- Risk Academy
- Competent authority (outside the programme)
How this works across the six pillars.
Data and Compute works through six pillars of one annual programme, led by the Nexus Consortium, with GCRI, GRF and the Global Risks Alliance (GRA) each contributing in its role: explore, experiment and prototype in Labs, build, simulate and prepare in Foundry, convene and test in Universe, codify, correct and apply in Nexus Standards, publish in every format in Reports, teach in the open in Risk Academy.
handoff in playrecorded handoffno direct handoff
Programme yearAll phases
Route
The whole programme
Every pillar hands its work to another; together they close the year’s feedback loops.
L · F · U · S · R · A
- Pillars
- 6 of 6
- Handoffs
- 18 of 18
- Loops
- 17 closed
Handoffs in play
- F01Universe → Foundry · Admitted mission becomes a cycle project with a decision caseReadiness preparation
- F02Foundry → Universe · Core Build Report and go or no-go evidenceControlled build
- F03Foundry → Reports · Sealed observations and indicator series behind a profileCloseout
- F04Universe → Reports · After-action and scenario findings for chapters 10 and 13After-action review
and 14 more
- LabsWhere questions become experiments and prototypes: new methods, data and tools are tried in the open, with their limits on record, before the Foundry builds them, under the Nexus Consortium.Labs
- FoundryWhere methods, data and models become reproducible builds, each run with its inputs, version and limits on record.Data and Compute in FoundryFoundry
- UniverseWhere a build is tested under controlled conditions with independent evaluators, so a method’s skill is measured, not assumed.Data and Compute in Universeuniverse.nexus
- Nexus StandardsWhere methods, identifiers and data schemas are codified in the open and corrected when a test finds a fault.Data and Evidence in Standardsnexustandards.com
- ReportsWhere findings are published with their method, uncertainty and evidence class, and corrected as new versions.Data and Compute in ReportsReports
- Risk AcademyWhere methods and systems are taught on real data and real places, by working the case, on Risk Academy.Faculty of Technology and Digital Systems in Academyrisksacademy.com
The same field, seen three ways.
GCRI studies a field as science, GRF governs it and GRA builds shared financial understanding of it. Data and Compute links to its counterparts so that work on one side is visible on the others.
Counterparts are added as the other institutions’ platforms in this field are mapped.
Where this page’s references lead.
The bodies and documents this page is read against. Status and editions change; each link goes to the issuing body.
Pages in Data and Compute.
Mandate and publisher
PageField overview
PageResearch and evidence
PageInnovation and practical technology
PageProgrammes and projects
PageData and technical methods
PageSpecialist community
PageLearning and professional development
PageEvents and technical dialogues
PageResearch and publications
PageParticipation paths
PageContact the specialist team
PageTrust, rights and status
PageSTEM foundation of Data and Compute
PageHow work moves in this field
PageBuild in Foundry
PageTest in Universe
PagePublish in Reports
PageThe same field across the Consortium
PageTopics
Where this page leads across the Consortium.
Questions and answers.
Who publishes Data and Compute?
Is Data and Compute active?
How can I contribute?
Where are findings published?
Which values on this platform are real?
How do I report an error?
Can I get compute time or data hosting through the platform?
How is it different from Foundry?
Contribute evidence from this page.
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.
- EmailGateway GW-GCRISend it from this pageEvidence, a correction, a case, a method, a review, a translation or profile input. It arrives tagged with this page, so the editor who owns it receives it.
- ZenodoOpen depositDeposit it and submit to the communityPublish your own record on Zenodo with your ORCID iD, then submit it to the Reports community there. Curators review it; the DOI stays yours.
- ReportsGCRISee every way to contributeThe contribution types, how each is reviewed, what credit you receive, the licence and what is never accepted.
Never send personal data, sensitive infrastructure detail or anything you have no right to share. A contribution is reviewed before use; sending it confers no authorship or editorial rights, and sponsorship never buys a finding.
How Data and Compute works.
Choose a view and press Play to follow the platform’s process, its programme year, the standards it applies and how its findings are published. The outline shows how the work is designed to run, not the status of any decision.
Data and Compute
How Data and Compute works
Platforms · Programme year · Standards · Reports
A platform joins a field to named methods, labelled evidence and the outputs it publishes, without becoming the authority it serves.
01 Scope
- 01Field and familiesStart · The platform leadThe home states the field, its families and who it serves.
- 02Topic dossiersRecord · Platform authorsTopics explain the subject with labelled evidence.
02 Evidence
- 03Evidence labelsRecord · GCRIEach value is labelled: observed, published statistics, estimated, modelled, scenario or unknown.
- 04MethodsStep · Method ownersMethods come from the STEM Commons, each with one canonical page.
03 Work
- 05Scenarios on the systemsModel · Foundry pillarScenarios run on the Nexus systems, labelled as scenario.
- 06Standards that applyRecord · Nexus StandardsThe platform names the standards that apply. A validator report is evidence for review.
04 Publish
- 07EditionsRecord · ReportsFindings are published through Reports with their limits.
- 08Authority decidesOutcome · The competent authorityDecisions and execution stay with the government, operator or licensed institution.
Data and Compute home · Platforms · Shared methodsAn outline of how the work is designed to run; it does not report the status of any decision or record.
Take part in Data and Compute.
Start from who you are. Answer an open call. Or form and lead a competence cell on the Data and Compute platform.
National institutions
Ministries, statistics offices and agencies: a national desk and chapter, and a seat in the working groups. National chapters
Sectors and professions
Operators, regulators, banks, insurers and professional bodies whose work touches Data and Compute. Participate
Learning
Courses and practice, with a record of every course completed. Free to study. Open learning
Standards
Draft, review and adopt the methods and data standards with the working groups. Working groups
Communities and research
Universities, civil society and individual experts: projects, data and review. Write to the team
| Open call | Seeks | Closes |
|---|---|---|
| Founding call for experts to the working groups CALL-FOUNDING-EXPERTS | expert, editor, chair | 2026-12-15 |
| Open nomination for the three independent expert seats of the Global Standards Council CALL-GSC-IND | council-member | 2026-12-01 |
| Nominations of interim regional members (applies only if the transitional provision is decided) CALL-GSC-REG | council-member | 2026-12-15 |
| Review of the wave-1 risk core outlines (C1, C2, C3, C4, C8, C10, C11) CALL-REVIEW-WAVE1 | contributor | 2027-01-31 |
| Experts for the core standards of risk science: uncertainty and evidence grading, scales, structured expert judgement, tolerability, extremes and compound events, catastrophic and existential risk, ethics and equity, units and measurement (NRS-C17 to NRS-C24) CALL-CORE-SCIENCE | expert, editor, chair | 2027-01-31 |
| Independent reviewers for the families of the hazard atlas, three from at least two regions for each family (NHS2-R19), priority families first CALL-ATLAS-REVIEW | expert | 2027-03-31 |
| Members of the interim Frontier Safety Review Panel and red-team reviewers (biosafety and biosecurity, AI safety and security, critical-infrastructure security); applications treated in confidence CALL-FRONTIER-SAFETY-REVIEW | expert | 2026-11-30 |
| Experts in ontology, metrology, software verification and conformity assessment for the requirement register, the NHS-2 machine representation, the conformance test suites and the conformity assessment scheme CALL-CONFORMANCE-ONTOLOGY | expert, editor | 2027-01-31 |
Calls past their closing date are hidden automatically. Every call, proposal and route: open areas and calls.
Gather the cell
Bring together three to seven people with complementary skills: data, field practice, policy and communication.
Register it
Write to the team with the cell’s name, members, area and region. You receive a reference and a contact. Write to the team
Choose a charter
Pick one focus: research and evidence, data and maps, standards review, or community preparedness.
Learn together
Follow shared study paths at Risk Academy, with practice and a record of every course completed. Hazards and resilience
Lead and report
Hold regular sessions. Publish what the cell learns through Reports. Bring findings to the working groups. Working groups
What a national team or a local community can do on The Global Risks Index (NXS-GRX) today.
Your country’s profile
Open risk profiles for 195 countries, with sources and licences on every value. Open the Index
Correct or reply
Correct a value or reply for your country. The change is logged with its effect. Open the Index
Offer data
Offer a dataset. It enters through the licence gate, with your credit. Open the Index
Every figure on this page is indexed: energy, infrastructure, technology, The contiguous United States.
The Index is the Consortium’s indexing system for risk data. Every indicator, hazard, series and country profile carries its Nexus Standards identifier, its source and its licence, so what this page shows can be traced, corrected and reused.
- 01 · Sources205 registered sourcesEvery value keeps its source and licence; withheld values are counted.Data and licences
- 02 · Nexus StandardsNIS-1 and NHS-1451 indicators, 905 hazards; every record carries a UNI.Nexus Standards
- 03 · The Index54 series, 195 country profilesComputed on the standards; no value is published until an edition is released.The Global Risks Index
- 04 · This pageData and ComputeMaps, figures and feeds read the Index in the context of energy, infrastructure, technology and The contiguous United States.Public API
Series in this context energy, infrastructure, technology
- GLBGlobal SystemsThe state of interdependent global risk: the twenty domain indices aggregated to the world, the five core systems (water, energy, food, health, biodiversity) and their couplings, the global tail register and the gap…NXS-GRX-AR-000002Climate · Energy · Infrastructure
- XTEnergy transition technologiesBatteries, hydrogen, grid storage, renewables and their supply chains, failure modes and transition risk.NXS-GRX-AR-000100Energy · Technology · Climate
- GSGlobal EnergySupply adequacy, import dependency, grid reliability, affordability, extreme-weather exposure, critical minerals and transition pathways.NXS-GRX-AR-000060Energy · Infrastructure · Climate
- SRSupply chains, trade and chokepointsTrade concentration, maritime and overland chokepoints, input–output exposure and the propagation of supply shocks.NXS-GRX-AR-000076Infrastructure · Energy · Technology
Country profiles The contiguous United States
Every country profile carries the source and licence of each value. Correct a value or reply
Hazard domains NHS-1
- Built systemsNXS-GRX-AR-000144
- Frontier and exponential technologyNXS-GRX-AR-000146
Geodata and API open
Open layers on an equal-area hexagon grid, shown as densities per km² or as symbols: People · GHSL 2025People · WorldPop 2025Built-up areaPortsAirportsRoadsRailwaysRivers and lake centrelines
/api/v1/public/grix · https://nexustandards.com/uni/{uni}
Developers · Data · Made with Natural Earth, Public domain; GHSL and WorldPop, CC BY 4.0
Snapshot of the Index registries pinned 2026-10-23 · 22c6eed. Research and risk-analytics information: not a rating, an official classification, a warning, a benchmark or advice.
Bring a method, a dataset or a question.
Information and enquiries are open today. An enquiry receives a reference and names the next step; applications, payments, compute allocations and registrations open only when their team, terms and review capacity exist.
Legal documents.
Maps, data and figures on this site are shown for context and general information. They are not advice, forecasts or warnings; the limits of the information are set out in the Disclaimers and Data Notices.