Export and repatriation

GDPR, output control and what may leave DST

Published

June 6, 2026

You have built your dataset and run your analysis (Phases 0–14). What remains is the final step: getting your results safely out of DST.

Data from Statistics Denmark is microdata subject to GDPR and special rules for research data. You cannot copy raw data out — everything must go through DST’s repatriation process.

READ AND RE-READ DST — Rules for repatriation of analysis results →

What may you export?

Yes: - Aggregated tables - Graphs and figures - Model output — coefficients, confidence intervals, p-values

No: - Individual-level data in any form - Cells with fewer than 3 observations (some registers require a minimum of 5) - Results that could identify individuals — directly or indirectly

Note

Scripts are also exported via the repatriation process — not freely. Code/scripts can be repatriated, but go through the same process as result files.

The process — “Hjemtag Filer” in the DDV app

  1. Save files in your project folder with precise, descriptive filenames — see below
  2. Upload in the DDV app via “Hjemtag Filer”
  3. The system automatically scans for potential microdata and flags risks
  4. Add a comment if a file is flagged — describe precisely what the file contains and why it is aggregated
  5. Confirm compliance with DST’s confidentiality policy (checkbox)
  6. Download under “Mit overblik” → your project → “Hjemtagelser”
Important

Use precise filenames and paths — not generic names like output.csv. When the system flags a file, your best defence is a descriptive filename (table1_descriptive_n500.csv) and a clear comment about what the file is. No README is required — describe in the comment field in the DDV app.

Save files to the output folder

When you do not specify a full path in your save command, R saves the file in your working directory — check it with:

getwd()   # shows your current working directory, e.g. "E:/workdata/708421/myproject"

Save with a full path to make sure the file ends up in the right place:

library(readr)   # write_csv

# Replace the path with your project folder:
output_path <- "E:/workdata/[projectnumber]/workspaces/[your-folder]/[project-name]/output/"

# Aggregated table as CSV file:
write_csv(my_table, paste0(output_path, "table1_descriptive.csv"))

# Figure as PNG file (width/height in inches, dpi = resolution):
ggsave(paste0(output_path, "figure1_km.png"),
       plot = my_figure, width = 8, height = 6, dpi = 300)

# Model output as text file:
sink(paste0(output_path, "cox_results.txt"))   # all subsequent output is written to the file
print(summary(cox_model))                       # write results
sink()                                          # stop — output goes back to the console

Rounding

DST requires that counts are sufficiently aggregated. Manual rounding to the nearest 5:

round(count / 5) * 5   # 23 → 25, 12 → 10

Checklist before uploading

You have completed the full process

When your results have been repatriated, you have gone all the way — from research question and cohort to analysis-ready dataset and publication-ready results.

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