Data Steward: FAIR Research Data in the Life Cycle (module 3)

Description

This module introduces the key stages of the research data life cycle and how to manage data effectively throughout a research project. It covers planning, documentation, sharing, preservation, and domain-specific practices. The goal is to help participants develop the skills needed to create a Data Management Plan (DMP) and understand the ethical, legal, and technical aspects of research data management.

The module also focuses on data documentation, covering levels of documentation, FAIR and CARE principles, and reproducibility. Supporting practices such as naming conventions, metadata standards, and persistent identifiers are discussed, along with common challenges and support options.

In the data sharing and preservation section, participants learn about repositories, controlled access services, data curation, and digital preservation. The final part addresses domain-specific characteristics, where students and researchers present examples from their own fields.

Teaching arrangements

This course is one part of the Data Steward training. The teaching arrangements of the training make it possible to combine work and studies. 

The duration of this course is about 5 months. There are about 4 online teaching days in May and August-September, and a break in teaching in the summer. The studies consist of lectures, practical examples, discussion tasks, group work, and homework assignments. To complete the training, you should set aside about 10 hours/week. 

Language of the training will be English, however there is a possibility in flexilingual arrangements, i.e. teaching is given in both Finnish and English according to the needs and strengths of the students. 

Content

Module 3: FAIR Research Data in the Life Cycle (6 ECTS)

By the end of this module, you will be able to:

• Recognise the phases of the research data lifecycle.
• Understand the importance of a data management plan (DMP), evaluate a DMP and provide feedback.
• Understand how ethical and legal issues impact data collection and handling.
• Understand how good documentation supports data reuse.
• Identify appropriate storage and backup solutions.
• Become familiar with open science principles, understand the benefits and risks of data sharing and different levels of openness.
• Recognise the requirements for long-term preservation of research data.

Leading teachers: Mari Elisa Kuusiniemi, University of Helsinki, Lucie Hradecká, Aalto University

Dates will be added in September 2025.

Each section includes practical tasks and assignments to reinforce learning and prepare participants to manage research data responsibly and efficiently.

Target group and entry requirements

The primary target group for this training is doctoral researchers. The training is also suitable for those who have already completed their thesis and/or who have already done some expert work in data management.

The basic education requirement is a higher university degree. 

To successfully engage with Module 3: Research Data Life Cycle, participants are expected to have a basic understanding of the research process and the role of data within it. They should be able to identify the types of data used in their own research and understand the general stages of data handling. Familiarity with fundamental research ethics and data protection principles is required. Participants should also have basic technical skills, such as organising files, naming conventions, and using online tools.

A working knowledge of English is essential, as the module materials, discussions, and assignments are delivered in English. Participants should feel comfortable contributing to group discussions and presenting aspects of their own research or discipline. Participants are expected to be motivated to improve their data management skills and committed to completing the module’s tasks, including preparatory and follow-up assignments.