GCRI · Agency
Expert competence
Competence is the demonstrated ability to apply knowledge and skill to a defined task in a given context. Qualifications, titles and years of experience are proxies for it, and in technical assistance they are often self-declared and lightly checked. This page sets out how competence is described, what evidence supports a claim, how weak verification turns into delivery risk, and what the institutions that select and supervise experts need to see.
How the work runs.
Assignment and team board
Expert competence · Assignment pool · Quarter 2
Assignments
Team record
| Team lead | Disaster risk management | None declared | Confirmed |
| Hydrologist | Flood modelling | Declared, managed | Confirmed |
| Data engineer | Pipelines | None declared | Invited |
| Reviewer | Independent | None declared | Confirmed |
Scope
- Requester
- Requesting institution
- Duration
- 12 weeks
- Authority
- stays with the requester
- Fee
- no fee stated
Fig.Assignment and team board: example names and illustrative values, not a record or a live system.
Expert competence: how the risk develops.
Skills, evidence and relevant experience. The dossier below sets out how the risk develops, what is measured, where the data come from, how it is modelled and who decides.
Credentials are proxies
A degree or professional title shows that training was completed at some point. It does not show performance on a comparable task, in a comparable institution, under comparable constraints. Evidence of applied work carries more weight than the credential alone.
Context limits transfer
Experience gained in one legal system, sector or language does not transfer automatically. Procurement law, public finance rules and safeguard regimes differ, and an expert strong in one setting can mislead in another.
Unverified claims compound
Curricula vitae are reused across proposals, and a claimed role on a past project is rarely checked against the project’s own records. Key experts named at award are sometimes replaced after contract signature by less qualified substitutes.
Competence gaps cascade
An error in a feasibility study or a specification passes into tender documents, then into works contracts and safeguard plans. By the time it surfaces, correcting it means variations, delays and sometimes harm to affected people.
People and hazards in East Africa.
Population density, night lights and flood water over East Africa, from NASA GIBS. Each layer carries its own date.
The interactive map needs JavaScript; the layer list and sources are below.
Layers 3
People and hazards, for this page
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 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
- Observed (clouds leave gaps)
- Source
- VIIRS Global Flood Product (NASA LANCE)
- Provider
- NASA LANCE
- Licence
- NASA open data
- Vintage
- daily; Satellite detection; clouds leave gaps
- Newest at build
- 2026-10-14
- Resolution
- about 250 m grid
- Uncertainty
- Satellite detection; clouds leave gaps. 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
- 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
- MODIS Terra EVI (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 vegetation index for the 8 days to the date shown, a habitat condition indicator; not a measure of species or biodiversity.
- 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.
People and hazards, framed on East Africa.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
- 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 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
- 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.
- 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).
- 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
- Population density, 2020: Population: CIESIN, Columbia University, Gridded Population of the World v4.11 (2018), NASA SEDAC, CC BY 4.0 · static
- Night-time lights, daily: VIIRS Black Marble (VNP46A2), NASA LAADS DAAC · 12 Oct 2026
- Flood water, 3-day composite: VIIRS Global Flood Product, NASA LANCE · 14 Oct 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
- Enhanced vegetation index, rolling 8 days: MODIS Terra EVI, NASA LANCE · 13 Oct 2026
Competence is matched to each domain’s needs.
- WaterIn practiceHydrologists with field and modelling experience.What a reader can checkCompetence evidence
- HealthIn practiceEpidemiologists with surveillance experience.What a reader can checkVerified experience
- BiodiversityIn practiceEcologists with monitoring experience.What a reader can checkReferences
Competence records are designed to carry identifiers (ORCID where available) and are used in the Portfolio and Readiness series. A competence record confers no status beyond the engagement.
- Competence evidence.
- Peer references.
Model expert competence as a system. Run the cascade.
Assembled from the Nexus Standards area profile Disaster risk reduction: 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
- Tropical cyclone
- Flash flood
- Heatwave
- Ice-jam flood
- HIV epidemic
- Earthquake
- 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
Controls
NS-0Constitution and principlesNS-1The UNI and the artefact catalogue (grammar v0.2: domain, sector, region and environment segments)NS-3Risk record UNIs (grammar, legacy crosswalk, allocation authority)NS-3bDataset and product metadata profile (STAC, DCAT, PROV-O)NS-9Contextual UNIs (deployments, instances, programme instances)NS-11Verification and monitoring (evidence, attestations, zero-trust conformance observation)NS-14Conformance and crosswalk to external standardsNRS-C15Loss, damage and impact accountingNRS-H114Hazard family: Macroeconomic and fiscal shocks (NHS-1 soc.macro-fiscal)NRS-K20Domain pack profile: Climate adaptation (DOMAIN-020)NRS-H54Hazard family: Signal and platform disruption (NHS-1 cyber.platform)NRS-H65Hazard family: Planetary boundary transgressions (NHS-1 planet.boundary)NRS-H119Hazard family: Cultural heritage loss (NHS-1 soc.heritage)
Observation
- DesInventar disaster loss databases (listed for reference)
- INFORM Risk Index (listed for reference)
- Global SDG Indicators Database (listed for reference)
- EM-DAT international disaster database (listed for reference)
- Number of deaths and missing persons attributed to disasters per 100,000 population
- Number of directly affected people attributed to disasters per 100,000 population
- Direct economic loss attributed to disasters in relation to global GDP
- Damage to critical infrastructure attributed to disasters
- Number of countries that adopt and implement national DRR strategies
- Total public international support for national disaster risk reduction actions (Sendai indicator F-1)
- Number of countries that have multi-hazard early warning systems
- Number of deaths, missing persons and directly affected persons attributed to disasters per 100,000 population
Example geography
- Bangladesh: 134 hexagonal cells
- Rain rate, last half hour (IMERG), NASA GIBS
- Surface water through cloud, 30 m (OPERA DSWx-S1 radar), NASA GIBS
- Surface air temperature, daytime (AIRS), NASA GIBS
- Night lights tonight, outages (VIIRS Day/Night Band), NASA GIBS
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 |
|---|---|---|---|---|
| Competence claims supported by verifiable evidence | percent of claims | per engagement | Reference checks, project records, registers | REPORTED |
| Professional registrations confirmed with the issuing body | percent of registrations claimed | per engagement | Professional and regulatory registers | Published statistics |
| Key expert substitutions after contract award | count per contract | per contract | Procurement and contract records | Published statistics |
| References checked before engagement | percent of engagements | quarterly | Engagement records | REPORTED |
| Prior roles confirmed against completion reports or published activity data | percent of roles claimed | per engagement | Completion reports, IATI records | REPORTED |
| Performance evaluations completed at assignment end | percent of assignments | per assignment | Client and supervisor evaluations | REPORTED |
| Language and context requirements met | percent of requirements | per engagement | Terms of reference against evidence | DECLARED |
How expert competence 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 expert competence 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
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 |
|---|---|---|
| ESCO classification (European Commission) | Multilingual taxonomy of occupations, skills and competences for describing expert profiles | Free and open, attribution under EU reuse policy |
| International Standard Classification of Occupations (ILO) | Occupational groups for consistent description of roles across countries | Free, attribution |
| National professional and regulatory registers | Licensure and registration of engineers, accountants, lawyers and health professionals | Public registers, terms per regulator |
| World Bank and regional development bank completion reports | Project records against which claimed past roles and outputs can be checked | Public documents under each bank’s access to information policy |
| IATI Datastore | Participating organisations and documents of past activities | Open, licence declared per publisher |
| Procurement contract records on national portals | Named key experts, substitutions and contract variations | Public records, terms per procurement authority |
Who decides, and what the evidence serves.
Agency 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 |
|---|---|---|
| Client evaluation committee | Whether an expert’s evidence meets the competence the terms of reference require | Competence profile with each claim labelled verified, declared or unverified |
| Funding agency procurement reviewer | Whether to give no objection to an award or a key expert substitution | Evidence for the proposed and substitute expert against the same criteria |
| Professional regulatory body | Whether a person is licensed to perform a reserved professional act in the jurisdiction | Registration status from the register, not from the curriculum vitae |
| Supervising project manager | Whether performance on the assignment matches the competence claimed | Deliverable acceptance records and structured performance evaluation |
Outputs this topic produces
- Competence profiles that separate evidence, declaration and assessment
- Verification checklists for credentials, registrations and prior roles
- Capacity maps of available expertise by field, language and region
- Substitution rules with equivalent-competence tests
What a reviewer needs to know.
- What exactly does the task require: which methods, tools, contexts and languages?
- What evidence shows that this person has applied those methods successfully?
- Who supervised or reviewed that work and can speak to it?
- Where are the gaps, and can supervision cover them?
Proxies mislead.
Titles and affiliations say little about whether someone can calibrate a hydrological model in a data-poor basin or design a privacy-preserving survey. Reliance on proxies tends to favour people already well connected, and it misses practitioners whose competence was built in operations rather than in publications.
Competence is also contextual. An expert in flood frequency analysis in one climate may need support to work in another; a strong software engineer may lack the domain knowledge to judge whether a model’s output is plausible. Good matching reads the evidence against the specific task and names the support needed.
How competence is assessed.
- 01
Work products
Publications, models, code, datasets or project records the candidate can show and explain.
- 02
References
Named referees who supervised or reviewed the work, contacted only with consent.
- 03
Scoped tasks
Where the work needs it, a short exercise matched to the assignment and assessed against stated criteria.
- 04
Frameworks
Fields and methods are read against the STEM Commons, through systems engineering and decision analysis under uncertainty among others. No framework captures every skill, so reviewer judgement is recorded with its reasons.
How it is studied, and what the methods cannot say.
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.
Questions and answers.
Is a certificate proof of competence?
Why are past roles checked against project records?
What is a key expert substitution?
Does Agency certify experts?
Does Agency issue credentials?
Can early-career people be matched?
Are assessments of individuals published?
Can I correct my record?
Contribute evidence from this page.
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