How to teach good research data management to next generation researchers?

This is a Preprint and has not been peer reviewed. This is version 2 of this Preprint.


Syed Ashfaq Hussain Shah, Frank Petzold


These days research work is subject to comply with FAIR principles. Additionally, it is subject to the practices of Open Science. Different stakeholders e.g. DFG are setting the goals of reproducible research work. This not only requires adequate handling of data but also the record of related information and practices during the research work. In this way, different tools and workflows are being developed and suggested to achieve the goals of good research and its data management. Those tools and workflows facilitate researchers and ease the research management tasks e.g. by means of standardisation, automation of processes and record of corresponding information. The researches of now a days are interdisciplinary and work collaboratively where participants are located at distinct locations, belong to different domains and have different levels of competencies. In such cases, provision of tools and specification of workflows is not enough. Just like other management, good research data management is a skill that need to be taught to the researchers systematically with details. So that they could make right decisions where and when needed. As a result, the contents and the materials for the education of good research data management become important. This paper presents contents and materials, approaches and skills which address the challenges of teaching and guiding good research data management in, in person, digital and hybrid environments. These were prepared for and imparted to the participants of collaborative research centre during the four years’ period. The objectives of the presented case of teaching and guidance of research data management have been applied mostly than classic theory learning.


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  • Published: 2024-04-11
  • Last Updated: 2024-04-11
  • License: Creative Commons Attribution 4.0
  • Subjects: Data Governance, Data Infrastructure, Data Literacy
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