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 TechTransfer) and funding issues related to Data Management;
• Know different tools to support their Research Data Management at IST Austria (RDMO and IST REx);
• 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 (second year and above), 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 + active participation + quizzes on Moodle. Final grade is pass/fail.
Teaching format: Lectures, in-class discussion, hands-on experience.
ECTS: 2 Year: 2021
Teacher(s):
Alexander Baratsits Patrick Danowski Doris Ernst Ingrid Kelly Spillmann Svenja Kutnig Carla Mazuheli-Chibidziura Niall O'Brien Bernhard Petermeier Nina Pollak Verena Seiboth
Teaching assistant(s):
If you want to enroll to this course, please click: REGISTER
- Teacher: Alexander Baratsits
- Teacher: Patrick Danowski
- Teacher: Doris Ernst
- Teacher: Katharina Majchrzak
- Teacher: Carla Mazuheli-Chibidziura
- Teacher: Niall O'Brien
- Teacher: Verena Seiboth