Big data helps humanitarian organizations identify the scale, location and changing needs of displaced populations by finding patterns across large datasets. However, it provides an incomplete model and requires contextual evidence and ethical safeguards.
Big data refers to datasets whose volume, variety and velocity often require digital systems for collection, processing and analysis. Sources can include border registrations, mobile-phone networks, satellite imagery, online searches, financial transactions, surveys and humanitarian-service records.
| Use of big data | Contribution | Limitation or risk |
|---|---|---|
| Mapping movement | Location and registration data reveal changing routes | Unregistered or disconnected people may be excluded |
| Predicting needs | Patterns indicate where food, shelter or healthcare may be needed | Biased source data can produce misleading predictions |
| Coordinating responses | Shared dashboards support resource allocation | Incompatible systems or inaccurate records weaken coordination |
| Identifying trends | Longitudinal data show whether displacement is growing or prolonged | Aggregation may conceal differences between communities |
System: The UNHCR Operational Data Portal combines and displays population figures, locations and humanitarian-response data.
Example specifics: Following Russia's full-scale invasion of Ukraine in 2022, UNHCR used the portal to publish regularly updated refugee and border-movement data. This postdates the 2022 coursebook and shows how multiple datasets inform an evolving response.
Impacts and implications: The portal helped governments and aid organizations assess displacement and coordinate assistance. Analysis offers faster allocation, but creates risks of surveillance, privacy violations and misleading conclusions when vulnerable people are absent from datasets.
Concepts: Systems thinking reveals interdependence among border agencies, humanitarian organizations and refugees. Power matters because institutions determine what is collected, how people are categorized and who gains access to resources.
This topic is shared data content, but its connection to global well-being and inequalities is HL-only. For HL Paper 1 Section B or Paper 3, evaluate humanitarian benefits against data quality, representation, privacy and security. Avoid the misconception that more data automatically creates better decisions.
