Basics of Research Data Management

Without exception, every research activity includes the handling of data. Either you re-use existing data or you create new data. However, what are research data, how do you take care of research data, and what are 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 Research Data and Data Management is;
• Be aware of significant IT, ethical, legal (including commercialization), and funding issues related to Data Management;
• Know different tools to support 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. [This course counts towards the Essential Skills Requirement for PhD Students—2022 cohort and onwards].

Prerequisites: None

Evaluation: Evaluation of a Data Management Plan that students create throughout the course (using RDMO platform) + Active participation

Teaching format: Lectures, in-class discussion, hands-on experience.

ECTS: 1 Year: 2024

Track segment(s):
Core curriculum

Teacher(s):
Ali Rashid Katharina Majchrzak Niall O'Brien Svenja Kutnig Verena Seiboth Patrick Danowski Stephan Stadlbauer

Teaching assistant(s):