Organizations use duplicate data
A health ministry, a statistics office and a relief program each keep their own district names and codes. Their data can't be combined without manual matching.
Open source · LGPL
Make your data time-aware, location-aware, and AI-ready, with provenance built in.
Geoprism Registry is a translation layer that helps organizations bring time-aware data into AI while maintaining high quality, common geographies, common IDs, and provenance. It keeps a shared, authoritative record of geographic places, including their boundaries, relationships, and history, so data from many systems lines up, stays correct as the map changes, and can always be traced back to its source.
Why it matters
Location and time are what bind information together.
Boundaries change, and history breaks
When a district splits or merges, years of trend data are quietly compared against the wrong geography unless the change itself is recorded.
AI doesn't know your geography
Language models have no reliable knowledge of which places exist, how they relate, or how they've changed. They need a trusted, traceable source to draw on.
How it works
From siloed data to shared, trusted knowledge
Each organization keeps curating the data it is mandated to maintain. Geoprism Registry connects that work by enabling common identifiers, common definitions and a record of where every value came from.
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Step 1
Integrate
Bring in place lists, boundaries and related records from each responsible authority, keeping the source of every value.
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Step 2
Enhance
Link places into hierarchies and networks, classify them with shared vocabularies, and track every change through time.
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Step 3
Publish
Share versioned, authoritative geographies and knowledge graphs with information systems, analysts and AI tools.
Where it's used
A common geography for work that crosses sectors
Public health
Align facility and district data across health information systems for microplanning, campaigns and trend analysis, including FHIR export.
National statistics
Publish common geographies for census and survey results so statistics can be compared across agencies and across years.
Spatial data infrastructure
Host and regularly update the core geographic objects a country relies on, while respecting each agency's curation mandate.
AI and knowledge graphs
Give AI systems trusted, time-aware geographic knowledge, while organizations keep sovereignty over their data.
Aligned with
- UN-IGIF
- Global Statistical Geospatial Framework
- Geospatial Knowledge Infrastructure
- HL7 FHIR & IHE mCSD
- UN Sustainable Development Goals
- Common Geo-Registry
New in version 2.0
See all features
More connected, more traceable, ready for AI
Publish knowledge graphs
Share versioned spatial knowledge graphs of places, programs and concepts, synchronized to standard graph databases.
Shared vocabularies
Classify data with controlled vocabularies and taxonomies that can be used across datasets.
Link programs and people to places
Manage non-spatial records like programs, staff or survey results alongside the geography they relate to.
Beyond hierarchies
Model real-world networks, like rivers that flow into each other or areas that share a border.
Know where every value came from
Record which authority is responsible for each dataset and which source supplied each value.
Undo any import
Every import creates a checkpoint you can roll back, so mistakes never become permanent.
Open source
Free to use, adapt and deploy
Released under the GNU LGPL and built entirely from open-source components. Distributed as a Docker image for cloud or on-premises deployment.