GCRI · Foundry
Supporting methods
The research behind Foundry: the questions it asks, the models and measurements it uses, how uncertainty is stated and how a result is reviewed and reproduced before it is published.
Supporting methods on the record.
- 01FieldsData and compute, Methods and modelling
- 02STEM methods6 canonical methods applied
- 03Topics8 subject pages
- 04Counterparts1 platforms in shared fields
- 05PublisherThe Global Centre for Risk and Innovation
What the research asks.
- 01
Project workstations
Project onboarding, persistent context and permissions.
- 02
Twenty technical systems
Canonical Foundry system inventory.
- 03
Maps and GIS
Approved geospatial public views.
- 04
Grix evidence
Data, ontology, Chronotopes and lineage.
- 05
Modelling and simulation
Workloads, reproducibility and limits.
- 06
Agents and automation
AI tools, authority and risk controls.
What Foundry research cannot yet answer well enough for decisions.
Foundry research concerns the engineering of trustworthy analytical infrastructure: how builds stay reproducible, how agents stay within scope and how access stays lawful across institutions.
- How can project workstations give analysts power without bypassing review? See project workstations.
- What assurance should an agent carry before it may act on Foundry data? See agents and automation.
- How should modelling and simulation runs be recorded so that they can be rerun years later? See modelling and simulation.
- How should compute be placed across cloud and edge under residency rules? See compute and edge.
Every result keeps its label.
Results are labelled as observed, published statistics, estimated, modelled, forecast, scenario or expert judgement. Missing data is shown as missing, never filled silently.
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Questions and answers.
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