Modules

Dive into the world of research data management with the HeFDI Data School! Our introductory course provides crucial foundations to make your scientific work more efficient and sustainable. Discover how smart data management can maximise the quality, discoverability, and reusability of your research data. Join a movement towards greater transparency and integrity in science!

Discover how to comply with legal and ethical standards when handling personal research data. This course covers practical solutions from the GDPR and obtaining informed consent to anonymisation and creating data use agreements. Obtain the skills needed to organise your research in a legally compliant and responsible manner!

Planning well is half the battle won! A data management plan (DMP) describes data handling during and after a project and serves as a living document, adjusted throughout the project’s lifecycle. It helps not only to meet funder requirements but also optimises workflow and collaboration. Learn how a DMP can structure your research projects and manage your data effectively!

Documenting means understanding! Whether for data reuse, team collaboration, or personal orientation, excellent organisation and documentation of your research data is essential. In this course, learn various tools and techniques to manage your data effectively and increase its traceability, including insights into metadata and versioning.

Learn about the copyright situation surrounding research data and how you can achieve openness in its publication. Find out when and how licensing with Creative Commons licences makes sense. You will also gain insights into current legal issues regarding the use of generative AI in research.

Data is the new gold—or perhaps even more valuable! For others to benefit from your research data, it must be made known! In this module, learn what you can achieve with your data even after the project ends. Discover how to publish and archive data effectively to maximise their value.

Getting started with good research data management (RDM) is difficult—but what if RDM became a “by-product” of analysis and the barriers to entry for researchers were lowered for both digital analysis and fair RDM? Then perhaps the open-source platform Galaxy could be the answer.