Analysis, dashboards, maps and data protection

1Analysing and presenting

• Choose the indicator that answers the question, and the right denominator (a percentage of what?).
• Disaggregate by sex, age, disability and area where relevant.
• One chart per message: bars to compare, lines for a trend, no pie charts with ten slices, no 3D effects.
• Always state the source, date, coverage and limitations of the data.

A useful dashboard fits on one page: a few key figures, the trend, the gaps, and what requires a decision. Tools: Excel, Power BI, Looker Studio, depending on the team's resources.

2Humanitarian mapping

• Tools: QGIS (free) for maps, OpenStreetMap data (roads, buildings), COD boundaries.
• Common types of maps: 4W presence map, needs severity map, access map (cut-off roads, high-risk areas), service location map.
• A good map has: a title that states the message, a legend, a scale, a north arrow, the source, the date, and the boundary disclaimer ("the boundaries shown do not imply official endorsement or acceptance").
• Legible colours (including for people with colour blindness), consistent value classes, little information but the right information.

3Data protection and data responsibility

• Personal data: name, phone number, precise location, biometric data; sensitive data: health, violence, ethnicity, legal status.
• Principles: collect the minimum, with consent, for a specific purpose; restricted access; encryption; a defined retention period; sharing governed by an agreement.
• Even aggregated data can expose a group (for example a map that locates members of a minority or survivors of violence): assess the impact before publishing.
• The IASC Operational Guidance on Data Responsibility in Humanitarian Action (2023) and cluster standards serve as references.