Without any exception, every research activity includes the handling of data. Either you re-use existing data or you create new one. However, what are research data, how do you take care of them, and what are the funder requirements? Good Research Data management ensures replicability and integrity, increases research efficiency, allows for more visibility, enhances collaboration, saves resources over time, guarantees data security, and minimizes data loss. At the end of this course, you will:
• Have an overview of what is Research Data and Data Management;
• Be aware of significant IT, ethical, legal (including commercialization), and funding issues related to Data Management;
• Know different tools to support their Research Data Management (RDMO and ISTA REx) and relevant policies (e.g. Research Data Policy, Research Software Guidelines, etc.) at ISTA;
• Know how to effectively create and implement a Research Data Management Plan, including best practice examples;
• Gain hands-on experience by creating a Research Data Management Plan.
Participants from all disciplines and levels are welcome.
Target group: The course targets PhD students, Post-docs, other researchers, and anyone else interested in gaining knowledge and experience in the topics covered.
Prerequisites: None
Evaluation: Evaluation of a Data Management Plan that the students will create throughout the course (using RDMO platform) + Active participation
Teaching format: Lectures, in-class discussion, hands-on experience.
ECTS: 1 Year: 2023
Track segment(s):
Core curriculum
Teacher(s):
Katharina Majchrzak Doris Ernst Niall O'Brien Svenja Kutnig Verena Seiboth Alexander Baratsits Carla Mazuheli-Chibidziura Patrick Danowski Stephan Stadlbauer
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Alexander Baratsits
- Teacher: Patrick Danowski
- Teacher: Doris Ernst
- Teacher: Svenja Kutnig
- Teacher: Katharina Majchrzak
- Teacher: Carla Mazuheli-Chibidziura
- Teacher: Niall O'Brien
- Teacher: Verena Seiboth