Humanitarian information systems and responsible data

1Designing an information system

An information system starts from the decisions it must inform: who decides what, when, with what information? From there come the indicators, sources (assessments, 4W, monitoring, secondary data), frequency and products (dashboards, maps, analysis notes). Shared standards (P-codes, HXL to tag tables, common operational datasets on HDX) make it possible to combine data from several organisations.

The golden rule: every piece of data collected must be used. Overlong forms tire respondents and degrade quality.

2Quality, bias and limitations

Humanitarian data are often incomplete: inaccessible areas, convenience samples, hard-to-reach groups (people with disabilities, minorities). Quality is assessed in terms of validity, reliability, precision, timeliness and integrity, and biases are documented.

Communicating limitations does not weaken the analysis: it prevents decisions based on false certainty. A half-page methodological note accompanies every important product.

3Responsible data

The IASC Operational Guidance on Data Responsibility (2023) and the ICRC Handbook on Data Protection in Humanitarian Action set the principles: defined purpose, minimisation, informed consent or another legitimate basis, security, controlled sharing and limited retention.

• Impact assessment before any risky processing.
• Information-sharing protocols at country and cluster level, classifying data by sensitivity.
• Aggregation and thresholds for public products, so that nobody can be identified.