---
title: "Sensitive Data Projects"
source: The Turing Way
source_url: https://github.com/the-turing-way/the-turing-way
licence: CC-BY-4.0
domain: data-and-analysis
subdomain: turing-way
date_added: 2026-04-25
---

(pd-sdp)=
# Sensitive Data Projects

(pd-sdp-prerequisites)=
## Prerequisites

| Prerequisite | Importance | Skill Level | Notes |
| -------------|----------|------|----|
| [](#rr-rdm) | Helpful | Beginner |  |

(pd-sdp-summary)=
## Summary

As researchers, we need to learn how to work with sensitive data so that we can tackle challenging research questions related to sensitive data. 
It can often be harder to work with sensitive data due to the regulations and restrictions that are required to protect both the participants and researchers involved in this type of research.
Abiding by these legal requirements can come with added technical steps such as de-identification of the data or the use of trusted research environments. 

There are considerations that need to be taken as to how to work in an inner source[{term}`def`] manner, which builds a closed but transparent research record enabling reproducible research.  
In addition, researchers must also plan how to publish sensitive data projects in a [FAIR](#rr-rdm-fair) and as open as possible way.

In this chapter, we give an overview of [different types of sensitive data](#pd-sd-types). 
We then go on to describe tools and practices that can help you manage, as well as, work reproducibly in these types of research projects. 

(pd-sdp-motivation)=
## Motivation
Researchers who are part of sensitive data projects may think that the nature of their data prohibits them from working in an open and reproducible manner. 
We want to show that, while it may require a bit of extra thinking and management, working openly with sensitive data is possible and should be encouraged.
