What does the pseudonymization utility produce?
Replace selected identifiers using your exact supplied mapping while retaining the approved fields and row order.
The working area above creates a separate transformed dataset in your browser. Review the supplied field rules, inspect the result and keep the original source backup private.
What do you need before you start?
- Authorize the disclosure purpose and review each retained field before transforming.
- Use UTF-8 CSV, text dataset JSON or a single-sheet text-cell XLSX file starting at A1. Each supports 2 MB, 5000 rows, 50 columns and 100000 cells. Expanded XLSX is limited to 10 MB. Formulas and macros are rejected.
- Assign Retain, Remove or Pseudonymize to every field. Map every original exactly to one distinct pseudonym within its field. No incomplete or unused mappings are accepted.
What information do you enter?
Select the actual source dataset and its complete approved field rules. Pseudonymization also requires a separate exact mapping dataset.
- Actual source dataset with distinct nonempty headings and text values.
- Approved field rules using exact Field and Action headings. Include a separate Field, Original and Pseudonym mapping.
- Explicit approval of every field action before creating the transformed copy.
| Field | What to enter | Fictional example |
|---|---|---|
| Source datasetRequired | Use distinct nonempty field headings and text values. Keep identifiers and leading zeros as text. | Record,Name 001,Fictional Alice |
| Approved field rulesRequired | Provide exactly Field and Action headings. Assign Retain, Pseudonymize or Remove to every source field. | Field,Action Record,Retain Name,Pseudonymize |
| Controlled mappingRequired | Provide exactly Field, Original and Pseudonym headings. Cover every selected original with one distinct token in that field. | Field,Original,Pseudonym Name,Fictional Alice,person-001 |
What you can download
Every result must identify its supplied facts, assumptions and unresolved items.
| Free result | Included downloads |
|---|---|
Enter your information, inspect the on-screen result and keep a browser backup. Editing and direct copies of your entered information stay free. |
These supported outputs are free. No checkout is required. |
Fictional transformation review (PDF). Editable review (DOCX). Complete fictional pack (ZIP). Samples use the finalized renderer. Original files and mapping originals are omitted. Retained values still require disclosure review.
How does the pseudonymization utility work?
- 1Select the actual source
Import the dataset and keep the original on this device. Download unchanged original bytes whenever needed.
- 2Approve each field action
Supply one rule per source field and a controlled mapping for selected identifiers. Matching preserves case, whitespace, Unicode and leading zeros. No tokens are generated automatically.
- 3Review the transformed copy
Confirm every action and create a separate copy. Inspect output values, retained fields and row counts. The original files are not changed.
- 4Keep separate copies
Download the complete transformed result JSON and finalized seven-file pack free. Keep the private source backup and mapping separate from the disclosure copy.
Method and sources
Apply the steps above to the supported inputs. Use the listed source sections to review the rule basis, assumptions and limits.
- De-Identifying Government Datasets. Techniques and GovernanceA reference for distinguishing identifier transformations from a complete de-identification and disclosure review. Techniques, disclosure risk and governance.National Institute of Standards and Technology. Reviewed 2026-10-06.
- NIST Privacy Framework 1.0 CoreSelective disclosure and reducing observability, identification and linkability require an organization-approved privacy risk strategy. Control-P. Disassociated Processing CT.DP-P.National Institute of Standards and Technology. Reviewed 2026-10-06.
Common questions
What information does the pseudonymization utility need?
Enter actual source dataset with distinct nonempty headings and text values; approved field rules using exact Field and Action headings. Include a separate Field, Original and Pseudonym mapping; explicit approval of every field action before creating the transformed copy. Authorize the disclosure purpose and review each retained field before transforming.
What does the pseudonymization utility produce?
Formal PDF and editable DOCX transformation review Complete transformed Excel and exact-text JSON Field action CSV, delivered-file hash manifest and instructions Separate private exact-source backup and restoration Review unresolved findings and limitations before use.
Who makes the final decision?
A responsible person reviews the result. Pseudonymized data can remain personal information. Protect the source and mapping separately. Retained fields, linkability and authorization require review.
Is this tool free?
Yes. The on-screen result and listed downloads are free. No checkout is required. Keep local backups and review the stated method and limits.
Can I use the pseudonymization utility for this task?
Replace identifiers using a controlled mapping. Pseudonymized data can remain personal information. Protect the source and mapping separately. Retained fields, linkability and authorization require review.
What still needs review?
Pseudonymized data can remain personal information. Protect the source and mapping separately. Retained fields, linkability and authorization require review.
Finalized files omit original source files and mapping originals. Retained and replacement values may still be sensitive. Browser backups contain originals and must remain private.
A missing rule, incomplete mapping, duplicate original, reused token or unsupported source prevents transformation. No partial output is supplied.