Climate—Conflict—Vulnerability Index
An interactive index mapping the overlap between climate and conflict risk — built for policymakers and researchers at the German Federal Foreign Office and its partners.
Challenge
Solution
My Contribution
- Client
German Federal Foreign Office
- My RoleUI/UX DesignData VisualizationScience Communication
- Time
2023 – 2025
- Collaboration
Moritz Stefaner (Truth & Beauty, design lead and development), Flavio Gortana (design and development), Jan Johannes (development)
- Awards
Information is Beautiful Awards 2024 – Shortlisted
Results











Process
Impact
Launched by a foreign minister. Used by the people who need it most.
The CCVI was publicly launched by Federal Foreign Minister Annalena Baerbock at the Berlin Climate Security Conference 2024 — who called it the best early warning system for our own security. The accompanying research paper (SocArXiv, 2026) confirmed a key finding the index was designed to reveal: high conflict risk almost never occurs where climate risk is low — but high climate risk spans the full spectrum of conflict risk. The index also demonstrates why aggregate scores alone are insufficient: two grid cells with nearly identical combined risk scores can have entirely opposite drivers, requiring different policy responses. Evaluation workshops were conducted with experts in Kenya, Somalia, and Ethiopia, confirming the index aligns with local realities on the ground. The open-source data and pipeline were released in 2025, with historical coverage back to 2015. The project was shortlisted at the Information is Beautiful Awards and featured at re:publica. For the first time, the German Foreign Office and its partners have a single, quarterly-updated tool that makes the overlap between climate and conflict risk globally visible and navigable — replacing a fragmented, on-demand workflow with an ongoing evidence base for foreign policy decision-making.
The index in numbers
Learnings
Build capability, not just deliverables
The most lasting thing we built wasn't the tool — it was the Data Design Language and the Observable notebooks that let the PREVIEW team take ownership of their own data communication. Looking back, a closer working relationship between the design team and the researchers would have been valuable — not because collaboration was missing, but because the two teams operated at different speeds and with different methods. More overlap earlier might have opened up questions about indicator relationships and index structure that would have been useful to explore together. This project also sharpened a conviction that runs through my current work: making a 42-indicator, three-pillar index legible to non-technical audiences is exactly the kind of explainability challenge that AI systems now face. The design methods transfer directly.

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