Consistent research workflows

The strict profile fixes the project structure in deterministic templates. The research declaration chooses domain, data origin and study design independently. The same eleven stages remain visible in every project: protocol, import, validation, cleaning, descriptive analysis, primary analysis, diagnostics, sensitivity analysis, exploration, report and reproducibility. An inapplicable stage requires a reason. A stage name does not prescribe a statistical method.

library(reflowR)
profile <- reflow_profile("clinical", "secondary", "observational", seed = 104L)
profile[c("domain", "data_origin", "design", "scheme", "primary_color", "badge")]

## $domain
## [1] "clinical"
## 
## $data_origin
## [1] "secondary"
## 
## $design
## [1] "observational"
## 
## $scheme
## [1] "clinical"
## 
## $primary_color
## [1] "#D55E00"
## 
## $badge
## [1] "SECONDARY DATA"

The palette follows the CTTIR v5 families: clinical projects use clinical (vermillion) and basic research uses brand (blue). Methods, simulation and software use methods; evidence synthesis uses evidence. Other domains use platform. Primary or secondary data are shown as a separate text badge, so colour is not the sole indicator of the project category. Declarations recorded with the earlier palette keep their scheme, colour and stylesheet and still validate.

Declare access, jurisdiction and the intended legal basis explicitly. These are recorded statements, not a determination that a project is authorized. Unknown values prevent execution readiness.

profile <- reflow_profile("basic", "primary", "simulation", seed = 104L,
  data_access = "synthetic", jurisdiction = "Germany",
  legal_basis = "Generated teaching data without personal records")
lock <- jsonlite::read_json("reviewed-environment/renv.lock")
scaffold <- reflow_scaffold(profile, "Example study", "Research group", lock)
project <- reflow_init_strict("example-study", profile, "Example study",
  "Research group", lock, git = TRUE)

Initialization writes a new directory and, when requested, initializes an empty Git repository. It does not install dependencies, commit, render or publish. Provision the exact locked R and package versions in a reviewed external R library before execution. This profile does not generate a project-local renv activation script or library. The root lock declares the required environment; stage execution checks installed versions and GitHub revision pins.

Preserve scaffold$declaration outside the project. The project cannot approve its own profile, palette, control files or changed code. Pass externally reviewed SHA-256 hashes for the declared stage files to validation:

reflow_validate_strict("example-study", scaffold$declaration)
reviewed <- c(
  "analysis/05_descriptive.Rmd" = "<reviewed SHA-256>",
  "code/stages/05_descriptive.R" = "<reviewed SHA-256>"
)
reflow_validate_strict("example-study", scaffold$declaration, reviewed)

valid means the structure and supplied hashes agree. execution_ready also requires declarations and reviewed implementations for every applicable stage. completed additionally requires externally retained receipt hashes and matching current code, input and output hashes. Rendering an empty scaffold does not complete an analysis. Receipts record the seed, session and stage outputs; unchanged unrelated artifacts do not count as this stage’s outputs.

Render reviewed pages explicitly with workflowr::wflow_build(project = "example-study") from its parent directory. Each build uses workflowr’s fresh R session. Display computed objects explicitly in an Rmd chunk, for example with knitr::kable(summary), after sourcing the calculation helper. Keep raw inputs read-only. Child publications share the root Git repository, dependency lock and site; nested execution roots and unknown code entrypoints fail validation.

Static validation is not a security sandbox, a scientific review or legal approval. Execute reviewed code only within the group’s separately controlled runtime. The existing reflow_init() and preset interfaces remain available for existing projects; adopting the strict profile is an explicit new-project path.

profile <- reflow_profile("clinical", "secondary", "observational",
  profile_version = "strict-cttir-v1", data_access = "synthetic",
  jurisdiction = "Germany", legal_basis = "Generated test observations")
composition <- list(
  schema_version = 1L,
  study = reviewed_study,
  recipe = reviewed_recipe,
  runtime = list(package = "cttiR", version = lock$Packages$cttiR$Version,
    writer = "study_stage", files = installed_cttir_file_hashes)
)
scaffold <- reflow_scaffold(profile, "Clinical example", "Research group",
  lock, composition = composition)
project <- reflow_init_strict("clinical-example", profile, "Clinical example",
  "Research group", lock, composition = composition)
reflow_validate_strict(project$directory, scaffold$declaration,
  execution_receipts = external_stage_receipt_hashes)