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Training

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Research Data Lifecycle Graph

Image: UK Data Service

Our team of professionals with backgrounds in various academic disciplines offers trainings in research data management. The central aspects of the successful management of research data are captured in a research data lifecycle model (see right). Knowledge and skills of data management and curation are essential for any researcher who aims to optimize their outputs, increase the impact of their work and support scientific transparency.

Our courses and workshops are available for researchers of all university faculties and at any stage of their academic career. The participants of our trainings can get familiar with the entire research data lifecycle or choose to focus on specific stages of it.

An overview of our training offers is presented in the table below. All courses are offered in  English and German language. Courses offered in the current semester period are listed in the catalogue of the Competence Center Digital Research (zedif)External link in the qualification portal of the university. Further trainings can be requested.

Training Offers

Type of Training Duration and Frequency Content Target Group
Workshops at the Graduate Academy 1-2 days, every term Overview of research data lifecycle PhD students, early career reseachers
Sessions within existing courses 90 mins, once per course Introduction to research data management B.Sc./M.Sc., B.A./M.A. Students
Module "Management of scientific data" 90 mins, weekly, every 2nd term Detailed account of every step of the research data lifecycle M.Sc. Students 
Training sessions upon request min. 90 mins Overview of research data lifecycle with focus on any of the steps most relevant for individual groups Researchers from any backgrounds

Contents and Objectives

  • Overview
    • What is research data and why is research data management necessary?
    • Guidelines for research data at universities and funding agencies
    • What is the Research Data Lifecycle?
    • What is a data management plan?
  • Research data
    • Data, files, and their formats
    • The Fair Data Principles
    • Sustainable data storage
    • Discipline-specific requirements and questions
  • Metadata
    • What is metadata?
    • What are metadata standards?
    • Which discipline-specific standards exist?
    • How does metadata look like?
  • Data Security and Protection
    • Why is it important?
    • Which kinds and options exist?
    • Advice for your particular projects
  • Data archiving
    • Which options exist?
    • What are the costs?
    • Who are your contact points?
  • Data publication
    • How and where can data be published?
    • What is Open Access?
  • Legal and ethical aspects
    • Who owns the data?
    • Potential legal conflicts concerning data protection and ownership
    • Which ethical issues should be considered?
    • Copyright licenses

Six Things You Should Know About Research Data Management Before Starting Your Master's Thesis

This video discusses some of the most common problems you may encounter in research data management (RDM): a number of students have identified what challenges they may encounter while working on their Master's thesis to offer suggestions on how to address them.

Online Trainings of Other Providers

There are certain online tutorials, courses and guides on research data management in English. A selection can be found below, starting with some short videos for introduction up to more extensive courses and courses with more advanced content.

Tutorials and courses in German are also offered. For the HeFDI course, the English version is in progress.

Further online training offers can be found on the page on tutorials, courses and guidesExternal link of forschungsdaten.info (German).