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STEM foundation

STEM foundation of Data and Compute

The science, technology, engineering and mathematics Data and Compute rests on. Each method has a canonical page in the STEM Commons, hosted by GCRI, and a page here on how it is applied in this field.

Open Computing for public knowledge Back to Data and Compute
Data and ComputeRegister
  1. 01MethodComputing for public knowledge
  2. 02MethodData engineering and stewardship
  3. 03MethodEnergy technology for computing
  4. 04MethodOptimization for computing
  5. 05MethodCybersecurity for data and compute
  6. 06MethodPhysics of computing
  7. 07MethodPower engineering for data centres

GCRI · In development · service level R0

01In brief

The short answer.

The Data and Compute STEM foundation is the set of canonical methods its findings depend on, from high-performance, cloud and edge computing to power systems engineering. For the Consortium, Data and Compute stewards high-performance, cloud and edge computing as well as data engineering, interoperability and stewardship. Each method has a canonical STEM Commons page and a page here on its use in the data and compute field.

02Canvas

Methods feeding this platform.

Canvas · methods feeding this platformDesign, not a record
STEM foundation of Data and Compute: build, test and release in Nexus FoundryA request opens a workspace; data are ingested and validated; the model is built and tested on held-out data; an independent gate approves release with limits; the workspace is stood down and the record kept. Design of the process, not a record of a run.

Fig.The methods this platform draws on and what each one feeds. Design, not a record.

03Geography

Connected activity in the contiguous United States.

For STEM foundation of data and compute, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with true colour from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.

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.

For STEM foundation of data and compute, in GCRI's spatial-intelligence reading, the map opens on night lights, true-colour imagery and population density with true colour from NASA GIBS, framed on the contiguous United States; every other NASA layer, live feed and forecast waits in the layer list.Satellite and model products as NASA publishes them, each with its own date; indicators, not assessments of any place; claim ceiling INTEGRATED.

Data: NASA GIBS · ASTER GDEM · Blue Marble · © OpenStreetMap contributors · Natural Earth · Copernicus Sentinel-2 L2A · 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 H3 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 H3 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 H3 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 H3 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 H3 cells where shown (modified). CC BY 4.0
  • 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 H3 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 H3 cells where shown (modified). 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 H3 cells where shown (modified). ODbL
  • Blue Marble, NASA Earth Observatory; imagery via NASA GIBS. Colours redrawn from the published colour map; values averaged into H3 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.
  • Globe: MapLibre GL JS 6.9.1, BSD-3-Clause, © MapLibre contributors.
  • Observed (EO): Copernicus Sentinel-2 L2A (contains modified Copernicus Sentinel data 2026), Microsoft Planetary Computer
  • 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).
  • Optional layers (35 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
  • True colour: VIIRS NOAA-20 corrected reflectance, NASA LANCE · 13 Oct 2026
  • Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
  • 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

04Methods

The methods behind the field.

  1. High-performance, cloud and edge computingWorkload characterisation · Porting codes to new architectures · Hybrid cloud and HPC workflowsSteward · Data and ComputeApplied here
    Canonical · STEM Commons
  2. Data engineering, interoperability and stewardshipFAIR data assessment · Interoperable catalogues · Data quality pipelinesSteward · Data and ComputeApplied here
    Canonical · STEM Commons
  3. Energy generation, storage and grid technologyCooling technology comparison · On-site energy options · Heat reuse feasibilitySteward · Energy NexusApplied here
    Canonical · STEM Commons
  4. Optimization and operations researchJob scheduling policies · Carbon-aware workload shifting · Capacity planningSteward · Systems Science and ModellingApplied here
    Canonical · STEM Commons
  5. Cybersecurity and cryptographySecure research environment design · Federated identity securitySteward · Cybersecurity and Digital ResilienceApplied here
    Canonical · STEM Commons
  6. Physics and quantum scienceEnergy limits of computation · Thermal management physics · Assessing new computing paradigmsSteward · Quantum TechnologiesApplied here
    Canonical · STEM Commons
  7. Power systems engineeringGrid connection studies · Power supply resilience · Demand flexibilitySteward · Energy NexusApplied here
    Canonical · STEM Commons
05Method mix

Why data and compute needs this combination of methods.

Data and compute risk combines computing and data engineering for the systems themselves, energy technology and power engineering for their supply, optimisation for placement, cybersecurity for protection and physics for cooling and hardware limits. Together they answer the platform's recurring question: whether critical analysis can keep running when power, water or providers are constrained.

Data and compute combine computing and data engineering with energy technology and power engineering, optimisation, cybersecurity and physics.

06Why it matters

Grounding makes claims checkable.

When a finding names the methods it depends on, a reader can see its assumptions and limits, and an expert in that method can challenge it.

07Key terms

Terms used on this page.

Each term as this page uses it. Where a standard-setting body defines the term, the wording follows that body.

TermDefinition
STEM CommonsThe shared reference of science, technology, engineering and mathematics methods for the Nexus network, hosted by GCRI, with one canonical page per method and a named steward platform.
Steward platformThe platform that maintains the canonical description of a method in the STEM Commons and reviews how other platforms apply it.
High-performance, cloud and edge computingHigh-performance, cloud and edge computing provide the processing and storage capacity for simulation, analytics and digital services.
Data engineering, interoperability and stewardshipData engineering, interoperability and stewardship cover the pipelines, standards and governance that make data usable and trustworthy.
08Sources

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.

09Pages

Pages in STEM foundation of Data and Compute.

Method

Computing for public knowledge

Method

Data engineering and stewardship

Method

Energy technology for computing

Method

Optimization for computing

Method

Cybersecurity for data and compute

Method

Physics of computing

Method

Power engineering for data centres

10Questions

Questions and answers.

What is a steward platform?
The platform that maintains the canonical description of a method and reviews how it is applied across the Consortium.
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