Research Data Management 2: Data Management and Analysis for reproducible research
In collaboration with Scientific IT Services, ETH Library conducts four consecutive workshops, each building upon the knowledge of the previous, which focus on the various elements of research data management along the research data life cycle. Register for individual workshops or for the whole series.
- a discussion on rules and regulations by research institutions and research funders
- basics of data management planning and DMP writing
- principles of long-term preservation of research data
- introduction of best practices and tools for daily data management
- options for secure data storage and backup
- strategies and workflows for managing large data sets
- an introduction to open access publishing
- a discussion on copyright and Creative Commons licenses
- an introduction to the Research Collection
- guidance on how to find a suitable data repository
- Research on confidential data (sensitive personal data),
- Data privacy and protection: legislation and cybersecurity awareness,
- Data classification: confidential data vs. public data,
- Leonhard Med, ETH Zurich: Swiss secure, powerful and versatile Scientific IT Platform for research on and with confidential data,
- “Good practices” for secure handling of confidential research data along the entire data life-cycle, from data collection, data management and analysis to publication in repositories and long-term preservation.
We also hold workshops from this series for groups of five people or more.
Please arrange a date with us.
This workshop series is comprised of four individual workshops, each building upon the knowledge acquired in the previous one. Participation in all four workshops is highly recommended, but not mandatory.
Please indicate in your application, if you would like to participate in the entire workshop series or only in one or two individual workshops.
- Best practices and tools for daily management of data
- Electronic laboratory notebooks
- Safe data storage and backup
- Ensuring reproducibility and reusability
- Working with Big Data: strategies and workflows for management of very large datasets
At the end of the course, you are able to
- develop and implement best practices for daily management of research data during the lifetime of a research project
- identify relevant tools and support available at ETH Zurich
- Doctoral students
- Scientific staff
- other members of ETH Zurich
- Please note: for workshop 2, participants should have at least some experience in conducting a research project.