PhD course: Personal Data & Human Subjects in Research

Course Description

This course will provide you with the essential knowledge and the core skills to handle and think ethically about your research participants and their personal data. The knowledge acquired in this course is essential if you work with personal data or human subjects in your PhD project, but it also prepares you for your future work as a researcher and/or as a citizen responsible for the good handling of your own personal data.

Target Audience

This course is aimed at PhD candidates that collect personal data and work with human subjects within their research projects.This course should be taken before starting the collection of personal data in a project.

Learning Objectives

After this course, learners:

  • identify what personal data and their special categories are
  • apply the principles of the GDPR to their research project and recognize the exceptions of the GDPR for researchers
  • identify risks for human research subjects and take appropriate measures to reduce these risks
  • identify research data management practices to be implemented when working with personal data
  • plan for preparing the relevant documents when working with personal data and human subjects in their research following the legal and institutional workflows
  • recognize the relevance of informed consent when working with personal data and doing research with human subjects; 
  • explain the benefits, limitations and implications of using different personal data protection techniques in research data management workflows

Course setup

This is a blended course, which consists of three weeks of self-study online modules with a total workload of approximately 7 hours (including the final self-assessment plus the preparation for class) and one face-to-face class meeting of four hours to finalise the course. 

The total workload of the course is approximately 11 hours, equivalent to 1 GS credits in the Research Skills category of the GS Education program.

Course Programme

Structure of the Self-paced Online Part

  • Module 1: Personal Data (1h and 30 min)
  • Module 2: Ethics in Research ( 2h)
  • Module 3: How to Do It (2h)
  • Final Self-assessment (30 min)
  • Preparation before class ( 1h)

Structure of the In-Person Class Session

  • Part 1 - Personal Data - Risks and mitigation measures (2h and 30 min)
  • Part 2 - Techniques for the safe handling of personal data (1h and 30 min)

Prerequisites

Having some basic knowledge about Research Data Management (RDM) before taking this course can facilitate the understanding of certain concepts (e.g. DMP, data licence, data repository, etc.).

If you are not able to join the RDM 101 course offered by the Graduate School you can learn about these concepts in the following self-learning resource: https://tu-delft-library.github.io/rdm101-book/intro  (without provision of GS credits)

Registration

The registration to the course for PhD candidates is via Coachview, the course registration application of the Graduate School Doctoral Education (GS DE) programme.

Next training session

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About this course

  • GS credits: 1
  • Total workload: 11 hours
  • Format: Blended
  • Runs per academic year: 3

 

Questions?

If you have any questions about the course, please contact: RDMtraining-lib@tudelft.nl.

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