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Research data
management

Welcome to the Research Data Services (RDS) of the Ruhr University Bochum. We support RUB researchers in all aspects of research data management. Here you will find advice, services, tools, information, and first aid.

DMP: Planning the handling of research data in a structured way with the help of a data management plan, on 05 December 2024, 2 pm - 4 pm [...]
It is worth taking a look at today's diverse programme of the state initiative fdm.nrw and the universities of North Rhine-Westphalia .
On 5 November, 1:30pm - 3:00 pm, Dr Bernhard Miller, Coordinator of KonsortSWD - NFDI4Society, will present [...]

Quick start

1. Exploring

Wondering about the importance of research data management but only have five minutes? We recommend this video:

2. Understanding

If you want to learn about research data management in general and have some spare time, take a look at our Moodle course. There you will find the main RDM topics explained in a simple way.

3. Using
  • Filling in the application form and need to provide information about the handling of your research data? We have a guide for you Here .
  • Supervisors or funding institutions set requirements regarding RDM? Find guidelines from DFG, BMBF and the EU here.
  • Already in the middle of your project and unsure where and how to start with RDM? At (almost) any stage of your project or research, a data management plan (DMP) is a good idea.
4. Consulting

Whether you're feeling completely lost in the topic or, conversely, have specific questions, we're here to assist you.

Guidelines

The rectorate of RUB adopted guidelines on research data management on January 23, 2018. Download: guidelines in PDF format (here english version from April 18, 2023)

What is RDM?

Research data management Research Data Management encompasses a range of methods for organizing, documenting, and preserving all data used or generated in a research process. RDM is aimed at all disciplines and covers various types of research data. RDM ensures sustainable access, reuse, reproducibility, and quality of all data that forms the basis of successful research.

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