Introduction to Research Data Management and FAIR Principles

What you will learn

Understand what research data are and why managing them is essential for reliable and open science;
Identify the stages of the research data lifecycle and develop a Data Management Plan (DMP) for your project;
Apply good practices for organising data, naming files, and structuring folders consistently;
Document and describe data using essential metadata;
Prepare and share datasets responsibly, choosing suitable licences and trusted repositories.

Description

Research Data Management (RDM) is an essential skill for anyone who works with data. This course introduces the key concepts, practices and tools that help researchers organise, document, preserve and share their data responsibly. Through short, accessible videos and practical examples, you will explore the full research data lifecycle — from planning and storage to documentation, publication and reuse.

The course explains how the FAIR (Findable, Accessible, Interoperable and Reusable) principles support transparency, reproducibility and long-term scientific impact. You will learn how Data Management Plans, file naming strategies, metadata and repository selection help you put FAIR into practice and make your data easier to find, understand and reuse.

Designed for researchers, PhD students and professionals from all disciplines, this course offers practical steps to improve the quality and value of your research data and to align your work with Open Science practices.

Format

The course is organised into six short modules combining concise video lessons, practical examples and brief quizzes. Learners progress at their own pace and can apply the concepts immediately through simple activities that reinforce the main concepts.

Prerequisites

No prior knowledge is required. The course is suitable for researchers, students and professionals from any discipline who work with research data or wish to improve their data management skills.

Assessment and certification

Learners are assessed through short quizzes at the end of each module and a final quiz that reviews the main concepts. To receive a certificate of completion, participants must achieve a minimum overall score of 70%.

Course plan

Module 1 – Introduction to Research Data Management and FAIR Principles
Module 2 – Data Lifecycle and Data Management Plan
Module 3 – File Naming Strategy
Module 4 – Metadata
Module 5 – Data Publication
Module 6 – Bringing It All Together

Organizations

Instituto de Engenharia de Sistemas e Computadores Tecnologia e Ciência

Course team

The course is developed by the FAIRway project team, dedicated to promoting good practices in Research Data Management and supporting the adoption of FAIR principles across the research community. The team brings together expertise in data stewardship, Open Science, information management and scientific training.

Main responsible: João Aguiar Castro, INESC TEC

Direção: João Aguiar Castro (INESC TEC)
Produção: Davi Furtado (INESC TEC)
Colaboração: Maria Paola Tomasino (CIIMAR), Antonio Muñoz (BIOPOLIS), Nuno Fonseca (BIOPOLIS), Inês Sousa (INESC TEC)

License

License for the course content

Attribution-NonCommercial-NoDerivatives

You are free to:

Share — copy and redistribute the material in any medium or format

Under the following terms:

Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use.
NonCommercial — You may not use the material for commercial purposes.
NoDerivatives — If you remix, transform, or build upon the material, you may not distribute the modified material.