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Workshop: Research Data Management

Learn how to ensure reproducibility and transparency of your research project by applying basic practices and tools of research data management.


Feb 27, 2024 from 10:00 to 03:00 (Europe/Berlin / UTC100)


iFZ (Heinrich-Buff-Ring 26), Raum B303

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At a Glance

  • Tuesday, Feb 27, 2024, 10:00-15:00
  • iFZ (Heinrich-Buff-Ring 26)
  • Room B303
  •  Doctoral students, PostDocs, Master Students
  • Dr. Julia Pfarr
  • English




Open and reproducible science entails the use of open software, provenance tracking of the project, quality assurance of code, and proper research data management (RDM). Practices like p-hacking, harking, and the publication bias are diminishing the power of science. Fortunately, efforts over recent years toward establishing open and reproducible science are getting more and more attention. One crucial part of this is to provide researchers education on RDM.

Goal: After this workshop, participants will have an understanding of how to ensure reproducibility and transparency of their research project by applying basic practices and tools of RDM.  


  • General introduction to RDM
  • Research Data Management Plans
  • Pre-registration
  • Project- & Data Organization: Folder Structure, File Naming, Versioning
  • Metadata standards
  • Data Storage and Collaboration
  • Data Sharing

Method: Contents will be taught by both, presentations and exercises. Exercises will mainly concern work on the Open Science Framework (OSF;

Pre-requisites: Participants will need a laptop with internet connection as well as an account on the Open Science Framework (OSF;

Please register via 

Registration for externals

The Trainer

Julia works as a Data Steward in the SFB135 „Cardinal Mechanisms of Perception". Her responsibilities are to consult researchers on RDM questions specific to their own project and give trainings for all kind of data related topics such as version control and data management tools, clean and re-usable code development, open code software such as python, data storage and sharing. She is involved in developing the “Data Hub” at the University Marburg, which offers computing and storage environments for researchers.