Seminar: Good Scientific Practice in Computer and Data Science
Key information
| Contact | Sascha Safenreider, Julian Kunkel, Lorenz Glissmann | ||
| Location | GWDG Seminar room 0.102 | ||
| Time | block course | ||
| Language | English | ||
| Module | 500132 Good Scientific Practice in Computer and Data Science | ||
| SWS | - | ||
| Credits | 2 |
Participants develop an understanding of the basic principles of good scientific practice. They will be able to place scientific work in a broader context and understand the importance of integrity and responsibility in research. They deal intensively with aspects of quality assurance and learn to critically scrutinize scien-tific statements. They also acquire knowledge about ethical challenges in research and develop strategies to avoid conflicts and misconduct in the scientific environment.
Learning Objectives
After successfully completing the module, students will be able to…
- effectively structure a research paper,
- are familiar with formal and structural norms regarding outlines, formatting, bibliographies, etc.,
- identify the principles of good scientific writing, apply them to their own writing and revise the manu-scripts of others accordingly,
- participate in technical and scientific discussions,
- give constructive feedback to colleagues,
- present a research project they have worked on and lead a technical discussion about it.
Agenda
Day 1 + 2 (23–24 October)
- Organization
- How to PhD
- Good Scientific Practice
- Scientific Writing
Day 3 (23 February) - Online
- Reviewing & Feedback
- Presenting & Discussing
Day 4 (23 March) - Online
- Final Session