Privacy checks before publishing data
This page is for data publishers and their managers. Publishing a dataset is permanent in practice: once downloaded, a file cannot be called back. This routine helps catch personal data before it leaves. Exponential stores and serves the file you upload; it does not inspect its contents, so these checks are a human step.
Note This page describes features and common practice; it is not legal advice. Check the law that applies to your organization with your legal counsel.
Contents
- The rules that usually apply
- The check routine
- Metadata inside files
- What Exponential records when you publish
- If personal data was published
The rules that usually apply
In the EU the GDPR, Regulation (EU) 2016/679 governs personal data, and the Open Data Directive (EU) 2019/1024 applies to re-use of public sector information without affecting the protection of personal data. Other jurisdictions have their own privacy laws. Your data protection officer decides; this page gives the practical checks.
The check routine
Run it for every new dataset and every new file of an existing one.
| # | Check | How |
|---|---|---|
| 1 | No direct identifiers | Look for columns with names, e-mail addresses, phone numbers, street addresses of individuals, ID numbers, account names |
| 2 | No identifiers in free text | Read or search comment and description columns; people write names into them |
| 3 | No small counts | In tables of counts, cells with very small numbers can identify people; aggregate or suppress them according to your body's rule |
| 4 | No rare combinations | Age, district and date together can single out one person; coarsen them (age bands, months) |
| 5 | No hidden data | Hidden spreadsheet columns or sheets, comments, tracked changes, previous values |
| 6 | Correct file | The file name and the content match the dataset page; not a draft or the internal full version |
| 7 | Second pair of eyes | A steward approves (see "Who may publish datasets") |
Record the check (who, when, which file) in your internal system or in a field of the dataset that is not shown publicly, such as an internal note that your template does not print.
Metadata inside files
Office documents and PDFs carry properties: author, organization, comments, sometimes the path on the author's computer. Remove them with the program that made the file, or export to a format without them (CSV has none). Exponential stores the file unchanged; it does not strip properties.
What Exponential records when you publish
| What | Where | Visible to the public |
|---|---|---|
| The version and its creator | the object's version history | no, staff with content/versionread |
| Publish and remove events | the audit trail, content channel | no, staff with audit/read |
| The original file name | the file field and the download address | yes, the file name appears in the address |
| The owner of the object | object information | depends on your templates; do not print it on public pages |
Choose file names without personal data, because they appear in the download address (Files and downloads).
If personal data was published
- Remove the file from the distribution at once and publish; then remove the older versions that still hold it on the object's Versions page (Content history).
- Clear the caches in front of the site so copies stop being served (Caches).
- Tell your data protection officer; they decide on notification duties.
- Find out where it went: the request logs and, if reads are switched on, the audit trail's
readchannel can show downloads (Request logs, Audit trail). - Publish the corrected file and a notice on the dataset page.
Related pages
- Privacy standards
- Versioning and updating datasets
- Who may publish datasets
- Free documentation: this page is free to copy, translate and improve under the GNU FDL 1.3.
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