Course Content

You will learn:

• About the differences between and the importance of data & metadata
• How to annotate data with structured metadata
• How to write schemas and validate metadata
• The pro’s and con’s of different database management systems
• How to set up a simple BackEnd for an RDM system
• About dependencies, inventory, and SOP
• How to set up a simple FrontEnd
• workflows to register metadata into the system
• what electronic lab notebooks are and what they are used for
• RDM, and Metadata in research workflows

After participating in this winter school partipants will be able to understand the basic principles and the inner workings of a typical system used for Research data management. When digitizing their scientific workflows, this course will help to empower resarchers to understand and research the implications that a given design decision (i.e. for software x) will have on their data and workflow.

Instructors

Volker Hofmann:

Works at the intersection of research data management and information systems engineering and tries to make bottom-up and top-down meet. He leads a group of metadata stewards, software developers and semantic engineers and collaborates in networks like the Helmholtz Metadata Collaboration, NFDI MatWerk and MecaNano.

Silke Gerlich:

Works as a Metadata Steward and Trainer at Forschungszentrum Jülich and is active in the Helmholtz Metadata Collaboration. She has a special interest in making research (meta)data handling approachable for the scientific community.

Ulrich Kerzel

Works on the intersection of Data Science, Artificial Intelligence and Materials Science. Prerequisite to working with data is to have data - hence, for almost 25 years, he has been involved in developing and building data infrastructure and machine learning tools both on a global scale in scientific applications, as well as in industrial settings.