init-mona-project

Scaffolding an R project structure for SCB MONA registry data requires generating a standardized directory layout, RStudio configurations, and pipeline settings. This creates a git-ready research environment that mirrors the secure platform's restricted-access requirements before deployment.

The MONA secure environment workflow uses a two-phase approach that enforces strict separation between local synthetic data development and secure aggregate statistics. This ensures researchers can validate pipelines locally while guaranteeing no personal registry data ever leaves the secure environment.

Yes, scaffolding an SCB MONA project requires the mock-data-wizard and reg-meta CLI tools to be installed and configured. These dependencies are essential for resolving metadata and extracting data to generate the local synthetic mock data used during development.

Generating mock data from provided statistics is a core feature of scaffolding a local MONA research environment. The environment automatically creates synthetic datasets based on your registry statistics, allowing you to develop and test R pipelines locally without accessing real personal data.

Ensuring reproducibility when transitioning to secure aggregate analysis requires standardized project scaffolding that enforces a strict two-phase workflow. By separating local synthetic data development from secure MONA platform execution, the pipeline configuration guarantees that only aggregate statistics are produced.

An SCB MONA project fails without proper setup because scaffolding relies on the reg-meta and mock-data-wizard CLI tools for metadata resolution and data extraction. Without these dependencies configured, the environment cannot generate the synthetic mock data required to initialize the R pipeline.