Data Management Training Leiden Law School
This course aims to familiarize PhD candidates with the basic concepts of research data management (RDM). It will also focus on the most important aspects of RDM specifically related to qualitative and quantitative data, and on dealing with sensitive data. It will help participants draft the first version of their data management plan (DMP).
- Target group
- PhD candidate
- Mareike Boom (Data Steward) Hannah DeLacey (External Phd candidate) Linda Geven (Assistant Professor) Eric van Hoof (Privacy Officer) Joanne Yeomans (Digital Scholarship Librarian)
This course is organized for all new PhD candidates of Leiden Law School. The training course will be offered in collaboration with the Centre for Digital Scholarship (CDS) at Leiden University Libraries. The course touches upon all aspects of research data management, with examples drawn from the research practice at Leiden Law School. Participants select up to three additional modules depending on the type of research that they plan to undertake. During the course, participants will write their own data management plan, present it during the last session, and receive feedback from their peers and the trainers.
Mode of instruction
This course has two different routes for participants depending on the type of research that they are conducting, a standard route for researchers conducting empirical research and a shorter route for participants who do not work with data.
All participants get a short preparatory assignment and follow the introductory workshop at the start of the training day which introduces the principles and best practices of responsible data management. The session touches especially upon the question of research data in law and on working with data provided by third parties (such as commercial partners or governmental organisations). It will help to answer the question “Do I collect (personal) data in my research project?”. For those participants not working with data, all additional workshops after the introduction are optional.
Depending on the type of research being carried out, participants will follow up to three extra workshops. Afterwards, participants will have several weeks to work on the first version of their data management plan (DMP). The group of participants will be divided into smaller groups to present their DMP in the final workshop.
Leiden University Library
Witte Singel 27
2311 BG Leiden
20 March 2023 – 1st Introduction
10.00 – 12.00
23 March 2023 – 2nd Training day
10.00 – 12.00
Data management aspects of quantitative and qualitative research
27 March 2023 – 3nd Training day
10.00 – 12.00
Data storage, security & privacy.
Includes extra time to ask questions about the DMP assignment
10 & 11 May 2023 – Data Management Plan (DMP) presentation
Kamerlingh Onnes Building
2311 ES Leiden
Schedule with timeslots of one hour per group follows.
All participants who write a full DMP will present their research, and data management choices and challenges.
PhD candidates are welcome to join all of the additional modules.
All participants will receive a short introductory assignment.
Participants conducting empirical research might receive short assignments for the additional modules. They will also draft the first version of their DMP (deadline 24 April 2023) and present it in the final workshop. The DMP must be ready before the start of data collection, and it is also needed for the PhD evaluation meeting held at the end of the first year.
Please register via e-mail and let us know what kind of research you will carry out:
- I do not think I manage any data
- I believe I will use quantitative methods in my research
- I believe I will use qualitative methods in my research
- I believe I will use both quantitative and qualitative methods in my research
Please indicate when registering in case you have a problem attending in person one of the sessions.
Participation in this course is obligatory for PhD candidates, PhD fellows, and contract PhDs. PhDs who have already attended a shorter DMP-workshop and think that they will benefit from attending the longer training are also welcome to join.
It is recommended that external (non-funded) PhD candidates attend the course. However, it is not mandatory.
Please contact the PhD Dean if you cannot complete the course before your evaluation meeting and/or the start of your data collection.