The German Federal Foreign Office has embraced a nationwide directive requiring all governmental branches to utilize data-driven insights.

In this framework, the FFO’s PREVIEW unit (Prediction, Visualization, Early Warning) takes the lead in forecasting potential crises and global risks. PREVIEW’s sophisticated models and tools aim to identify emerging threats well in advance, enabling informed decision-making at the highest levels.

Conflict Explorer

The Conflict Explorer initiative was launched by the German Federal Foreign Office (FFO) to integrate ACLED (Armed Conflict Location & Event Data) with the ministry’s internal datasets. This platform visually represents global conflict hotspots and provides decision-makers with detailed risk assessments.

By overlaying multiple data streams—ranging from ACLED’s conflict events to diplomatic cables and socio-economic indicators—users gain a dynamic, real-time view of volatile regions.

A major feature is the crisis prediction model, leveraging news data, satellite imagery, and country-level indicators to forecast emerging hotspots. Reducing false positives was a core priority, ensuring that the model’s alerts were both relevant and timely.

I initially joined a small team responsible for designing and developing the Conflict Explorer’s foundational architecture.

Through iterative enhancements and satisfied stakeholders, I helped scale the project into a 12+ person unit, equipped to handle diverse data types and complex analytical tasks.

I coordinated the integration of large-scale news feeds, custom map layers, and robust ML infrastructure to train advanced models.

By continually optimizing the data pipelines and refining the UI, I ensured that the platform remained both user-friendly and analytically powerful.

Keywords:

Prediction, Geo Data, Management, Text Data, Machine Learning, MLOPs, Visualization

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