GCRI · Food Nexus
Food security and access
Food security exists when all people, at all times, have physical, social and economic access to sufficient, safe and nutritious food. A country can have enough food in aggregate while households go hungry, because access depends on incomes, prices, markets, social protection and conflict as much as on harvests. This page sets out the four dimensions of food security, how each is measured, and what the evidence serves for those who must respond.
Food security and access in seven parts.
- 01The questionFood security and access: how the risk develops
- 02CouplingsAccess to food is where shocks in every domain converge on households
- 03Reports, standards and contributionsAccess evidence, its limits and who decides
- 04IndicatorsWhat is measured, and how well
- 05SourcesWhere the evidence comes from
- 06DecisionsWho decides, and what the evidence serves
- 07Core questionsWhat experts ask
Food security and access: how the risk develops.
Availability, affordability and nutrition. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Availability is necessary, not sufficient
National supply from production, stocks, imports and aid sets an upper bound. Hunger occurs inside adequate national supply when food cannot reach a place or people cannot pay for it.
Access runs through prices and incomes
Most poor households buy most of their food. A rise in staple prices, or a fall in wages, remittances or livestock prices, cuts what they can buy, and diet quality is cut first.
Coping strategies deplete assets
Households skip meals, sell livestock and tools, take children out of school and borrow. Each strategy buys time and leaves the household less able to absorb the next shock.
Malnutrition follows with a lag
Poorer diets, disease and inadequate water and sanitation combine into acute malnutrition, often months after the shock that started it. Mortality rises where malnutrition meets outbreaks and displacement.
Growing conditions in the Black Sea region.
Crop greenness, root-zone soil moisture and population density over the Black Sea region, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
Growing conditions, for this page
About this layer
- Evidence
- Observed (clouds leave gaps)
- Source
- MODIS Terra NDVI (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite index; clouds leave gaps
- Newest at build
- 2026-10-13
- Resolution
- about 250 m grid
- Uncertainty
- Satellite greenness index over the 8 days to the date shown; an indicator of crop and pasture condition, not a yield estimate or a food security warning.
- Reached through
- gibs.earthdata.nasa.gov, only after you allow the live map
About this layer
- Evidence
- Modelled
- Source
- SMAP Level 4 (NASA NSIDC DAAC)
- Provider
- NASA NSIDC DAAC
- Licence
- NASA open data
- Vintage
- daily; Model with satellite data assimilated
- Newest at build
- 2026-10-11
- Resolution
- about 2 km grid
- Uncertainty
- Model with satellite data assimilated. 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
- 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
- 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
- Modelled (latest 8-day period GIBS publishes)
- Source
- MODIS Aqua GPP (MYD17) (NASA LP DAAC)
- Provider
- NASA LP DAAC
- Licence
- NASA open data
- Vintage
- 8-day; Satellite-driven model; latest 8-day period GIBS publishes
- Newest at build
- 2026-09-30
- Resolution
- about 500 m grid
- Uncertainty
- Model estimate of carbon taken up by plants over the 8-day period shown; an indicator of growth, not harvest or production.
- 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.
Growing conditions, framed on the Black Sea region.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 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
- 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
- SMAP Level 4 soil moisture and snow mass, NASA Global Modeling and Assimilation Office; distributed by the NASA National Snow and Ice Data Center 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
- 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.
- Live: NASA EONET Events are indicative, not authority warnings.
- 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).
- River discharge forecast, 30 days with range (GloFAS via Open-Meteo): Contains modified Copernicus Emergency Management Service information 2026; not a flood warning.
- 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 (13 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
- Vegetation greenness (NDVI), rolling 8 days: MODIS Terra NDVI, NASA LANCE · 13 Oct 2026
- Root-zone soil moisture, 0 to 100 cm: SMAP Level 4, NASA NSIDC DAAC · 11 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
- Gross primary production, 8-day total: MODIS Aqua GPP (MYD17), NASA LP DAAC · 30 Sep 2026
Access to food is where shocks in every domain converge on households.
| Domain | How it couples here | What to watch |
|---|---|---|
| Water | Drought cuts both harvests and rural incomes at once. See drought and flood. | Seasonal rainfall against livelihood calendars |
| Energy | Fuel and electricity prices raise transport, milling and cooking costs. | Share of household spending on food and fuel |
| Health | Undernutrition weakens immunity, and illness reduces the use of food the body can make; the two feed each other. See health equity. | Wasting and stunting prevalence from nutrition surveys |
| Biodiversity | Wild foods, fisheries and forest products are a buffer for poorer households. | Reliance on wild foods in lean seasons |
Food insecurity is measured in two complementary ways: experience-based scales such as FAO’s Food Insecurity Experience Scale, and the IPC acute food insecurity phases (Technical Manual 3.1, 2021), which classify areas by convergence of evidence. The annual State of Food Security and Nutrition in the World and the Global Report on Food Crises draw on both.
Market and harvest early warning.
The screen a team would use to follow this subject: its measures, states and decisions. Names are examples and values are illustrative.
Access evidence, its limits and who decides.
Analyses of access and its drivers are designed for the Country Systems Risk and Resilience series. IPC classifications are made by national analysis teams under the IPC protocols; the Global Centre for Risk and Innovation (GCRI) does not classify or declare famine and does not substitute for those processes. Survey-based datasets would carry NS-3b metadata under the proposed Nexus Standards, with household data never released.
- Market price series from local markets.
- Nutrition survey results with methods.
- Community accounts of coping in lean seasons, with consent.
A shock through an input-output economy.
A loss of output in one sector propagates through the technical coefficients to its suppliers and customers, and recovers at the rate you set; the coefficients are teaching values, not national accounts. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Black Sea region; the model itself is not tied to a place.
Controls
- Sector hit first (position in the list)
- 0
- Size of the shock
- 30% of its output
- Duration of the shock
- 30 days
- Recovery rate
- 0.08 per day
- Days simulated
- 180 days
Readouts
- Output lost over the run
- 0.65% of a year’s output
- Total over direct (multiplier)
- 1.82 times
- Most affected other sector
- Fertiliser and inputs
- Its peak inoperability
- 3.5%
Numbers, methods and sources
| Sector | Peak inoperability (%) | Output weight (%) |
|---|---|---|
| Farming | 31.53 | 12.8 |
| Fertiliser and inputs | 3.49 | 25.9 |
| Food processing | 0.54 | 16.1 |
| Transport | 2.26 | 12.9 |
| Wholesale and retail | 1.30 | 21.4 |
| Energy | 2.24 | 10.9 |
Methods
- Input-output analysis Leontief (1936); Miller and Blair (2009), Input-Output Analysis, Cambridge University Press
- Inoperability input-output model Haimes and Jiang (2001), Journal of Infrastructure Systems 7
- Dynamic inoperability and recovery Lian and Haimes (2006), Systems Engineering 9
- 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:
- Seaports Natural Earth
- Maritime chokepoints Nexus (named straits and canals at their published coordinates)
- Railways Natural Earth
- Major roads Natural Earth
Across the six pillars, led by Nexus Consortium
- Experiments Labs
- Built in Food Nexus in Foundry
- Tested at Food Nexus in Universe
- Codified in Water and Food Systems in Standards
- Published in Food Nexus in Reports
- Taught in Faculty of Earth and Environmental Sciences in Academy
What is measured, and how well.
Each indicator carries its unit, its cadence, the kind of source behind it and the evidence label a value would carry. No values are shown: a programme supplies them under its own authority.
| Indicator | Unit | Cadence | Source type | Label |
|---|---|---|---|---|
| Prevalence of undernourishment (SDG 2.1.1) | percent of population | annual | Modelled from food supply and survey data | MODELLED |
| Prevalence of moderate or severe food insecurity (SDG 2.1.2) | percent of population on the Food Insecurity Experience Scale | annual | Individual and household surveys | ESTIMATED |
| Population by acute food insecurity phase | persons per IPC or Cadre Harmonisé phase | per analysis | Consensus analysis | Published statistics |
| Food consumption score | weighted score with standard thresholds | monthly to quarterly | Household surveys, remote monitoring | REPORTED |
| Cost of a healthy diet | purchasing power parity dollars per person per day | annual | Retail prices against dietary guidelines | ESTIMATED |
| Global acute malnutrition among children under five | percent of children | per survey | Anthropometric surveys (SMART, DHS, MICS) | OBSERVED |
| Minimum dietary diversity for women | percent of women of reproductive age | per survey | Household surveys | OBSERVED |
| Food share of household expenditure | percent of total expenditure | per survey | Household budget surveys | Published statistics |
Model food security and access as a system. Run the cascade.
Assembled from the Nexus Standards area profile FAO and food security: 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
- Famine
- Ice-jam flood
- Tropical cyclone
- Heatwave
- HIV epidemic
- Flash flood
- Storm surge (set off downstream)
- Intense rainfall (set off downstream)
- River flood (set off downstream)
- Dangerous surf (set off downstream)
- Widespread power outage (set off downstream)
- Mass displacement (set off downstream)
- Coastal flood (set off downstream)
- Extreme fire weather (set off downstream)
- Wildfire (set off downstream)
- Heat-driven grid stress (set off downstream)
- Agricultural drought (set off downstream)
- Flash drought (set off downstream)
Systems and couplings
- FAO and food security
- Food security and nutrition risk Coupling
- Early warning and anticipatory action Coupling
- OCHA and humanitarian data Coupling
- Water risk standards Coupling
Controls
NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-10Policies and clauses (machine-readable obligations: definition, binding, evaluation and enforcement)NRS-N3Food and agriculture risk and resilienceNRS-C7Early warning, triggers and anticipatory actionNRS-H61Hazard family: Cascading failure (NHS-1 sys.cascade)NRS-K40Domain pack profile: Islands small states (DOMAIN-040)NRS-S9System profile: NXS-AAP (Anticipatory action and triggers)NRS-H57Hazard family: Humanitarian crises (NHS-1 soc.humanitarian)
Observation
- FAOSTAT API (listed for reference)
- GIEWS FPMA food price monitoring tool (listed for reference)
- FEWS NET data (listed for reference)
- Prevalence of undernourishment
- Prevalence of moderate or severe food insecurity in the population, based on the Food Insecurity Experience Scale (FIES)
- Indicator of food price anomalies
Example geography
- The Ganges and Brahmaputra Basin: 178 hexagonal cells
- Surface soil moisture (SMAP), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
Where the evidence comes from.
Named public datasets and institutional records, each with its licence class. Sources by agreement are used only under their terms and never republished.
| Source | What it gives | Licence class |
|---|---|---|
| FAO Suite of Food Security Indicators | Undernourishment, food insecurity experience and related indicators by country | Free and open, attribution |
| IPC and Cadre Harmonisé analyses | Area classifications and population estimates by acute food insecurity phase | Public, attribution |
| FEWS NET | Food security outlooks, livelihood zones, seasonal calendars and market monitoring | Public, attribution |
| WFP HungerMap LIVE and VAM data | Near-real-time food consumption and coping indicators from remote surveys | Public, terms per WFP |
| UNICEF, WHO and World Bank Joint Child Malnutrition Estimates | Stunting, wasting and overweight among children by country | Free and open, attribution |
| Demographic and Health Surveys and MICS | Household diets, child anthropometry and living conditions | Free on registration, terms per programme |
| Food Prices for Nutrition (World Bank and FAO) | Cost and affordability of a healthy diet by country | Free and open, attribution |
The sector signature of food security and access.
The sectors food security and access touches and how strongly they depend on each other: what a study has to observe and model together.
Signature
Food and its partners
Food gives nutrition to health (0.7), land conversion to biodiversity (0.6) and withdrawals and runoff to water (0.3).
W · E · I · F · H · B
- Sectors
- 4 of 6
- Relations
- 6 of 15
- Coupling
- 0.46 share of total
Strongest relations in play
- Food → Biodiversity · land conversion0.6
- Water → Food · irrigation0.8
- Water → Biodiversity · environmental flows0.6
- Food → Health · nutrition0.7
Who decides, and what the evidence serves.
Food Nexus prepares evidence. The decisions below are taken by the authorities named, under their own rules, and never by the platform.
| Who decides | The question | Evidence this page serves |
|---|---|---|
| Ministries of agriculture, health and social protection | Which areas and groups need targeted support, and whether cash, food or nutrition programmes fit best | Population by phase, market functioning and diet affordability by area |
| Humanitarian coordinators and food assistance agencies | Where to scale assistance before the lean season and how much to preposition | Outlooks with projected phases, seasonal calendars, pipeline and access constraints |
| Finance and social protection ministries | When to trigger shock-responsive transfers and how to finance them | Trigger indicators with their historical record of hits and false alarms |
| Nutrition and public health agencies | Where acute malnutrition is likely to rise and what treatment capacity is needed | Survey anthropometry, disease surveillance and diet indicators read together |
Outputs this topic produces
- Food-system vulnerability briefs covering availability, access, utilisation and stability
- Small-area estimates of food insecurity with uncertainty maps
- Affordability traces linking staple prices and incomes to diet cost
- Early-warning indicator sets with lead time and skill stated
How food security and access 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.
System model
The couplings between the systems in food security and access: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
What experts ask.
Access is where food-system failures become human harm. A shortfall that markets absorb for wealthier households can mean fewer meals, poorer diets and lasting damage to child growth for poorer ones, so the distribution of exposure matters as much as its national average. Experts therefore look past totals to the households and places that carry the burden.
- Who cannot afford a nutritionally adequate diet, where do they live and how does that change with prices and incomes?
- How do households cope with a shock, and when do coping strategies start to damage health, education or future livelihoods?
- How quickly do world and national price changes reach local markets, and why does this differ between places?
- Which social protection, school meal or reserve arrangements reduce harm, and what limits their reach?
Drivers and processes.
Access depends on income, prices, markets and public support acting together.
Purchasing power
Wage labour, farm income, remittances and transfers determine what households can spend. Seasonal income gaps create predictable hunger periods.
Affordability
Nutritious foods such as vegetables, fruit, pulses and animal-source foods often cost more per calorie than staples, so price rises push diets toward lower quality.
Diet and health
Undernutrition, micronutrient deficiency and diet-related disease can coexist in the same country and even the same household.
How the evidence is built, and its limits.
- 01
Household surveys
Consumption, expenditure and dietary diversity surveys give rich detail but are costly and infrequent.
- 02
Market monitoring
Retail price series show affordability trends; coverage of remote and informal markets is often thin.
- 03
Food security classifications
Consensus-based classification systems combine indicators to describe severity. They depend on data quality and access, and their phase definitions should be read on their own terms.
- 04
Modelling
Cost-of-diet and price transmission models, built with econometrics, estimate affordability under scenarios, with uncertainty that grows with the shock size.
How it is studied, and what the methods cannot say.
- 01EconometricsPrice transmission and market integration · Effects of trade policyApplied here
- 02Spatial statistics and geostatisticsSmall-area estimation of food insecurity · Digital soil mappingApplied here
- 03Forecasting and time-series analysisSeasonal production outlooks · Staple price forecasting · Anticipatory action triggersApplied here
- 04Agricultural, soil and food scienceCrop simulation for seasonal yield risk · Yield gap and nutrient limitation analysisApplied here
- 05Earth observation and remote sensingCrop condition monitoring · Crop type and area mapping · Irrigation and water productivityApplied here
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.
- The State of Food Security and Nutrition in the World 2025 (FAO, IFAD, UNICEF, WFP and WHO, 2025)
- IPC Technical Manual version 3.1 (IPC Global Partnership, 2021)
- Global Report on Food Crises 2025 (Global Network Against Food Crises and FSIN, 2025)
- Food Insecurity Experience Scale (FAO Voices of the Hungry)
- NS-3b, Dataset and product metadata profile, a proposed standard
Where this page leads across the Consortium.
Questions and answers.
What are the four dimensions of food security?
What does IPC Phase 5 mean?
Why can hunger rise when harvests are good?
How does undernourishment differ from food insecurity experience?
Why focus on access rather than supply?
Does the platform classify food crises?
Is nutrition within scope?
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.
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.