In our advanced training courses, you will learn about special topics of RDM and how to use (specialized) tools. The events are usually offered online.

Duration: ca. 2 h
Location: online (prerequisite: camera and microphone)
Target group: PhD students, Postdocs, researchers and all interested persons
Language: English / German
Number of participants: min. 10, max. 20

A platform for storing, sharing and archiving research data

 Further information

Coscine is a research data management platform for FAIRe (Findable, Accessible, Interoperable, Reusable) data in research projects. Here you can store, describe with metadata, share and archive your research data. Coscine integrates functions ranging from metadata management to the automatic assignment of persistent identifiers. In collaborative projects, researchers from different institutions can work together on their data in Coscine. In addition, linking of other data sources is possible to display all project-relevant research data at a glance. In the workshop we will give you a hands-on introduction to Coscine.

Save time and gain visibility with reused research data

 Further information

Why should I reuse data and how do I find suitable data? Why should I make my data reusable and what is needed to create reusable and reproducible research data? In the workshop we will address these questions and how you can save time and gain visibility for your research by reusing data and making your own data reusable.

Prepare a data set according to the FAIR principles

 Further information

In this workshop you will learn how to design your qualitative research data along the FAIR principles.  In addition to the theory of the FAIR principles with special consideration of the challenges of qualitative research, alternative approaches (e.g. through codebooks) for particularly sensitive data are also presented. At the heart of the workshop is a practical part in which participants are given the opportunity to prepare a data set themselves.

No prior knowledge is required for this workshop.

The lecture language is German.

Plan the handling of research data in a structured way with the help of a data management plan

 Futher information

The latest call for proposals from a funding body sounds just right, but it asks for statements on the handling of research data? The colleague has left the institution and has not documented his knowledge so that nobody knows exactly which data can be found where? Can’t find the data just collected last week?

Do these examples sound familiar to you and you are looking for a solution? A data management plan (DMP) can help.

In this 2-hour online workshop, you will learn

• how to recognize that the funding body requires statements on the handling of research data.
• how to use checklists and templates, and what information belongs in a data management plan.
• how to work with the tool RDMO (Research Data Management Organizer), which you can use to create DMPs.
• why it is worth preparing a DMP - even if the funding body does not require it, so that the situations described no longer occur.

Basic knowledge of research data management is a prerequisite for participation.

Learn the basic use of the eLabFTW web application for electronic lab books

 Further information

eLabFTW is a web application in which electronic lab books can be maintained collaboratively as a research team or group. Experiments and database elements can be added, commented and saved.

In contrast to the paper lab book, a full text search as well as the insertion and editing of images is also possible. The immutability of completed experiments is guaranteed by time stamps.

In this Hands-on workshop, you will learn the basic use of eLabFTW.

Previous knowledge is not required.

Open data, software and preregistration: making scientific research more transparent and reproducible

 Further information

Are you interested in integrating Open Science into your research but don't know where or how to start? This workshop is designed for researchers at all career stages who want to maximize the validity, credibility, and impact of their research through Open Science practices.

You will gain hands-on experience with practices that make scientific research more transparent and reproducible, focusing on:

• Preregistrations: Understand the added value of preregistrations, learn how to easily create one on the most suitable platform, and publish it to your advantage.
• Open Software: Discover best practices for developing and sharing open-source software, with practical guidance on using RUB’s GitLab.
• Open Data and Materials: Learn where and how to effectively publish your research data and materials, including strategies for finding discipline-specific repositories and using RUB’s research data repository, ReSeeD.

The aim of this course is to help you identify your optimal entry points into Open Science and to equip you with the tools and knowledge needed to take your first steps in implementing Open Science in your research.

There are no prerequisites for participation.

Introduction to the Python programming language and first applications for your research data

Further information

This course provides an introduction to the Python programming language and initial applications for your research data. We will deal with loading and analyzing tabular data, displaying results graphically and saving them as text or Excel files. No knowledge of Python is required; Python beginners are particularly welcome.

In order to participate in the workshop, please install Python and a development environment. Installation instructions (in German):  https://fdm.tu-dortmund.de/informationen/2024-03-05-workshop-einfuehrung-in-python/

Organize, save, preregister and publish projects in one tool

Further information

With the Open Science Framework (OSF) you can organize your whole project on one platform. In the workshop, we will show you how to create projects, upload and manage materials, assign access permissions and licenses, preregister planned studies, and publish data and papers.

In a hands-on exercise, we will put theory into practice together with you.

To prepare for the workshop, please register for free on the platform https://osf.io/

The organization of scientific projects: GitLab without any code

Only for members of UDE

 Further information

As a project management tool, GitLab offers a large selection of tools for project organization. This includes wikis for documentation, a shared and versioned data storage and a ticket system that can be used to structure work packages and manage them, for example, in the form of a Kanban board.

In this workshop we will give an insight into how these functions of GitLab can be used in the organization of scientific projects.

For practical exercises you need a university ID (Uni-Kennung) of the University of Duisburg-Essen.

Requirements for participation in the workshop: none

Open data, software and preregistration: making scientific research more transparent and reproducible

 Further informatione

Effectively publishing and securely archiving research data is a critical challenge for scientists of all disciplines. Selecting the appropriate repository is particularly crucial for data that is not intended or not yet ready for publication. It's essential to use a platform that ensures your data can be managed according to the Guidelines of Good Scientific Practice and eventually be archived or published.

ReSeeD, the central research data repository of Ruhr-Universität Bochum, offers a comprehensive infrastructure for research data management. The repository covers various use cases (e.g. metadata assignment, role and rights management, collaborative work) and is suitable for different types of data.

In this workshop, you will explore

• the basic functionalities of ReSeeD.
• how to manage and store your data in ReSeeD - from the creation of datasets, collaboration and sharing of datasets, to their archiving and publication.
• You will gain hands-on experience with ReSeeD, allowing you to directly apply what you've learned.

Participants without a RUB-LoginID can get access to ReSeeD via a free ORCID-iD.

No prior knowledge is required for this workshop.

Lecturer: Sonja Hendriks (UDE) and Sarah Ann Stock (UDE)

 Further information

When are data protected by copyright? To what extent and in what way may they be passed on to other researchers or published? These are questions that will be addressed in the workshop and explained in more detail using case studies. The focus will be on § 60c of the German Copyright Act (UrhG, Scientific Research) and § 60d UrhG (Text and Data Mining) in particular, but also on other topics such as the level of creation, the scope of the work, and the subsequent use of research data under Creative Commons licenses. In addition to the case studies presented, participants can also contribute and discuss their own examples.

Please note that the contents of the workshop are for information purposes only and do not constitute legally binding information.

The workshop will be held in German.

Lecturers: Sonja Hendriks (UDE) and Dr. Sarah Kritzler (UDE)

Further information

Would you like to document your work with the statistical software R more comprehensibly and clearly? R Notebooks offer an easy way to summarize your code, explanations and results in one document and share it with other people, regardless of their R knowledge. In this hands-on workshop, we will guide you through your first steps with R Notebooks on the way to reproducible analyses in R.

Requirements for participation in the workshop: Basic knowledge of R and computer with installation of the latest versions of R (https://www.r-project.org/) and RStudio (https://www.rstudio.com/products/rstudio/download/).