Course Description:

This course is designed to equip researchers and research support professionals with the knowledge and skills required to develop, manage and evaluate Data Management Plans (DMPs), including their evolution into machine-actionability (maDMPs). Adopting a practical, researcher-oriented approach, the course provides a clear understanding of the role of DMPs within Open Science and their interconnection with other systems in the research ecosystem, while highlighting the added value of OSTrails developments.

Created For / Purpose:

This course is specifically tailored for researchers and does not delve into technical implementation details. Instead, it focuses on presenting the essential concepts of DMPs and maDMPs from a researcher’s perspective, enabling participants to understand what services are available and how they can effectively benefit from them within their research practices.

Primary Audience:

• Researchers
• Open Science trainers
• Data Stewards

Learning Objectives:

Upon successful completion of this course, you will be able to:

• Explain the components of a DMP and its relevance to support the research data life cycle;
• Understand what is a maDMP and know how to benefit from the exchange of information across research tools and systems;  
• Apply best practices when preparing a DMP;  
• Use the tools to create and manage a DMP;
• Evaluate a DMP in different contexts, including funder requirements, institutional and PhD requirements, research infrastructure standards, and domain and FAIR standards.

Prerequisites:

This is an entry-level course on Data Management Plans and machine-actionable Data Management Plan. To fully benefit from the course content, participants are expected to have basic prior knowledge of Research Data Management (RDM) practices. 

If you need to acquire this foundational knowledge, an optional introductory module on RDM practices is provided within the course.

Duration:

Approximately 3 hours.