Awareness in Data Management and Analysis for Industry and Research

Beginner

Introduction

Good data management is more than simply organising files. It helps keep research transparent, reproducible, and secure while preventing data loss and saving time and resources. Whether you work with experimental data, computational results, or shared datasets, knowing how to organise, document, and manage your data properly is an essential skill. It also supports collaboration, clarifies data ownership, and helps meet legal, ethical, and funding requirements.

This workshop introduces practical approaches to managing research data effectively. Based on training materials from FAIRsFAIR, ZB MED - Information Centre for Life Sciences, The Carpentries, and CodeRefinery, the course explores good research practices, data management plans, and the FAIR Data Principles. You will also learn practical strategies for organising data, using electronic lab notebooks, and making computational analyses more reproducible so that your research remains transparent, reusable, and well documented.

Learning outcomes

Understand good data management practices in research and industry, including governance, policies, and organisational roles
Plan and organise your data using Data Management Plans (DMPs) and electronic lab notebooks (ELNs)
Apply FAIR principles to make your data findable, accessible, interoperable, and reusable
Ensure reproducibility and transparency in analyses by using practical tools and workflows

Target audience

Interested in learning about data management
Interested in learning how to manage data in a good practice in both academia and industry
Anyone interested in learning about how to make your data reusable and analysis reproducible

Requirements

Just a PC/Laptop with an up-to-date browser Chrome, Safari and Firefox browsers are all supported (some older browsers, including Internet Explorer version 9, may not be)
- Ideally a two-screen setup so you can follow the workshop while trying on your own