BioNT Learning Path 3: FAIR Data Management and Stewardship Created byRosemary Sheridan|UpdatedagoThe Bio Network for Training (BioNT) is an international consortium of nine partners, including six academic institutions and three small and medium enterprises (SMEs), dedicated to advancing digital skills in the biotechnology and biomedical sectors. The aim of the BioNT consortium is to provide a high-quality training program and community for digital skills relevant to the biotechnology industry and biomedical sector.The goals of the project's training model are to:Provide high-quality courses in two coherently designed curricula: for basic digital skills of staff and job seekers in healthcare and biotechnology, and empowering technological leaders and innovators.Positively impact course participants and their communities, supporting digital skills in SMEs and larger businesses in these sectors.Ensure sustainability beyond the project's duration, empowering individuals as well as their business-specific, sector-specific, language-specific, etc. communities. Learning Path 3: FAIR Data Management and StewardshipThis learning path introduces the principles and practices of responsible, FAIR data management for research and industry. It is aimed at data stewards, data managers, and professionals responsible for research outputs. Learners establish a foundation in data-management awareness before progressing to collaborative and FAIR software-development practice.Introductory learning materialsBasicAwareness in Data Management and Analysis for Industry and ResearchDigital skillsShow lessGood 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.The 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.See less materialsAdvanced learning materialsIntermediateCode & Collaborate: The FAIRytale of Software Development (BioNT)Digital skillsShow lessModern research and data science rarely happen in isolation. Whether you are working on scripts, analysis pipelines, or full software projects: collaboration, version control, and reproducibility are essential for producing reliable and reusable results. Good software practices not only make your code easier to share and maintain, but also ensure that others, including your future self, can understand and build on your work.The course introduces practical approaches to collaborative and FAIR software development. Through hands-on exercises, you will learn how to manage code using distributed version control, collaborate effectively with others, and structure projects in a clear and reproducible way. The course also covers testing, documentation, and environment management, helping you move from individual scripts to well-organised, shareable software projects.See less materialsLearning path DetailsWebsite link BioNT consortiumDigital skill levelBasicIntermediateAdvancedDigital technology / specialisationDigital skillsDigital transformationLog in to comment
