GCRI · Data and Compute
Dependencies and consequences
Data and compute infrastructure sits in the middle of a web of dependencies. It needs electricity, cooling, hardware, network connectivity, software supply chains and skilled people. In turn, science, public services, finance and other infrastructure need it. This page sets out the causal, physical, economic, social and ecological links and how stress travels along them. It complements the field overview and the topic on compute, energy and water.
- 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
What data and compute need.
Continuous electricity
Data centres and supercomputers draw large, steady loads and need backup power for continuity.
Heat removal
Air or liquid cooling, often using water directly or indirectly, especially in warm climates.
Concentrated supply
Processors, memory and networking equipment from a small number of manufacturers and fabrication plants.
Networks and cables
Terrestrial and submarine fibre that links data centres and users across borders.
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
Keyboard, with the map focused
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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
What depends on data and compute.
- 01
Science and forecasting
Weather, climate, hydrological and epidemiological models need sustained high-performance computing.
- 02
Public services
Digital identity, payments, health records and benefit systems run on data centres and networks.
- 03
Finance
Trading, settlement and risk systems depend on low-latency computing and concentrated cloud services.
- 04
Infrastructure control
Grids, water systems and transport increasingly use data platforms and edge computing for operation.
Field overview.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Patterns of systemic failure.
Concentration is the main pattern: many users depend on a few cloud regions, a few hardware suppliers or a few cables, so one failure has wide reach. Common-mode software faults can disable many systems at once, as a faulty update or shared library flaw propagates through everything that uses it. Heat and drought can stress data centre cooling while also stressing the grid that powers them.
Economic and social links follow. Hardware shortages delay research and raise costs for smaller institutions first. Data centre growth can compete with households and industry for grid connections and water, creating local tension. Ecologically, the energy and water footprint of computing adds to pressures on shared resources, and electronic waste carries its own burden.
How dependencies are analysed.
Analysis uses computing, power systems engineering and optimisation and operations research. Each analysis states its boundaries, data and uncertainty. Data on private infrastructure and supply chains is often incomplete, so maps describe patterns rather than specific facilities.
Questions and answers.
Is a dependency map a forecast?
Are specific data centres or cables identified?
Who acts on these dependencies?
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