Who shares the household?
Follow the resident reference into household membership and housing context.
Explore household context →How FCTE works
One city.
Connected through time.
Striped Donkey is the marketplace. FCTE™ is the engine behind the connected synthetic cities. Both are Fidelra products. A persistent synthetic resident connects available household, education, employment and health records. Inspect a working example and the evidence behind each association.
Try a connected example.
32 Nairobi residents. Seven joined tables. Run Python and SQL, compare expected results, and trace records to their original profiles.
From evidence to release
Build around persistent relationships.
Follow the path from reference evidence to a documented synthetic city.
01Reference the city
City, national and global evidence informs the published targets and historical context.
02Generate connected state
Synthetic entities share documented identities and relationships across the chosen city scope.
03Retain the event context
Dated lifecycle events carry their supplied time and source context into the connected record.
04Validate the release
Structural, temporal and realism checks accompany the data. Review their scope and disclosed findings.
05Publish with evidence
A versioned release brings the records, documentation and release identity together.
Follow a question
Start with one resident. Look wider.
Use the same synthetic reference to inspect the available records in context.
How do education and work connect?
Read the sequence of learning and employment events around the same synthetic person.
Explore a timeline →The public interface exposes representative records and relationships. Available coverage varies by city and domain; field guides and domain documentation describe the published scope.
The release package
The data travels with its context.
Use these three resources together when reviewing a release.
Field definitions
Friendly explanations and examples make samples readable. Original field names remain available for integration.
Read a field guide ↗
Quality evidence
Inspect the checks, reference evidence and disclosed findings.
Review assurance ↗Release identity
Match covered artifacts to a dated release record and inspect verification.
Verify an artifact ↗Using model outputs
Keep the question within the scope.
Scenario outputs depend on assumptions, calibration, time range and selected mechanisms.
Conditional results need context.
Consequential use needs validation against the intended real-world context. Assess the model against the question and the decision it is meant to support.
Read use & governance →Explore the release
Choose a city. Follow the records.
Inspect domain coverage, resident journeys and the evidence behind the available samples.
See the records for yourself.
Rows, distributions and field definitions are available in the sample workspace.