In this three-part, interactive course, participants will gain knowledge of the rules of good scientific practice (GSP), the fundamentals of research data management, and key aspects of the publication process from the perspective of GSP.

Module 1: Introduction to GSP & the Ombudsman System (19.02.2027)
The course covers the fundamental principles of good scientific practice and highlights where typical gray areas and conflicts can arise in everyday research. It addresses rule violations and research misconduct, as well as ways to prevent them. A key focus is on the ombudsman system and the competent handling of conflicts. Participants will learn to make responsible decisions in a scientific context and gain an overview of (inter)national frameworks:

• The scientific process and the role of self-regulation
• Historical development of GSP
• (Inter)national statutes
• Forms of scientific misconduct
• Dealing with conflicts and misconduct
• Ethical principles, GSP resources, and the ombudsman system
• Case studies

Module 2: Research Data Management (26.02.2027)
This module focuses on the responsible handling of research data. Participants will gain fundamental knowledge of key topics throughout the research data lifecycle. Additionally, institutional guidelines and services, as well as legal aspects and responsibilities, will be addressed:

• Topics Throughout the Research Data Lifecycle
• Planning
• Data Documentation
• Structured Storage and Archiving of Data
• Publication and Reuse of Research Data
• FAIR Data Principles
• (Institutional) Guidelines and Services
• Legal Aspects and Responsibilities

Module 3: The Publication Process, Authorship, Plagiarism, and AI (05.03.2027)
This module addresses the challenges surrounding authorship, publications, and academic integrity. It explores issues such as the order of authors, responsibilities within author teams, and the line between legitimate citation practices and plagiarism. Participants will develop strategies for responsibly managing conflicts and learn to identify risks such as predatory journals. In addition, various forms of plagiarism will be explained, and common detection and verification tools will be introduced. Another focus is on the use of AI tools, their capabilities and limitations, and the associated requirements for transparency and academic integrity:

• Publication Process
• Authorship
• Predatory Journals, Hijacked Journals, Paper Mills
• Plagiarism and Detection Software
• Use of AI
• Case Studies
• GSP Resources

Requirements for the live online course: your own computer with high-speed internet access, a camera, a microphone, and speakers. If possible: a wired LAN connection and a headset.