Standardizing Fragmented African Health Datasets
Why a common schema for public health records unlocks downstream AI applications.
The problem
Across the continent, vital health data lives in PDFs, spreadsheets, and disconnected systems. Each ministry, NGO, and clinic stores information differently — making it almost impossible to compare, combine, or analyze.
Our approach
We collect scattered datasets and map them into a single, consistent schema:
- Normalize column names and units
- Resolve geographic identifiers to a shared gazetteer
- Publish machine-readable, versioned releases
When data speaks the same language, intelligence follows.
Early results
A unified schema reduced the time to build a regional outbreak model from weeks to days.
healthdatasetsstandardization