Scope: Are you a researcher in ecology, environmental science, biodiversity science, or related fields? Are you encountering challenges in managing your research data? Join this course and learn about the things you can do now to make your data future-proof.
Data is essential for answering our research questions and advancing our scientific goals, making it a valuable asset that is the core of our work. Despite this, management of research data is critically underappreciated, rendering most data unsuitable for reuse and replication. Addressing this requires researchers to think critically about data management and how to meaningfully apply good practices and tools to increase the transparency and impact of their work.
This four-day course will provide researchers with an opportunity to learn about the theory and practices behind research data management in ecology and environmental sciences. You will leave the course with a hands-on understanding of good research data management practices and how to efficiently implement them in your own work.
Is this workshop for me?
• Are you working with new or existing research data and experiencing barriers with data management?
• Are you new to research data management and looking for a practical start?
• Do you want help with increasing the findability and transparency of your research?
• Do you want help with making your data reusable by others?
• Do you want help with fulfilling the data requirements of your organisation or funding agency?
Then this course is the right fit for you.
Learning outcomes
The main goal of this course is to get you familiar with good practices and easy-to-use tools for data management across the research life cycle. This will help you work towards the FAIR data principles and boost the transparency and impact of your work.
More specifically, you will learn:
• about the FAIR data principles and how to put them into practice
• how to organise your data, and keep track of data versions with version control
• how metadata and documentation can improve the findability, reproducibility and transparency of your work
• about data licenses, and when and where to share your data
• the ins and outs of data and metadata standards, when they are relevant, and when they are not
The course consists of a set of modules that follow the research data life cycle. Each module combines theory with practice, with a strong emphasis on expanding the research data management toolkit via hands-on experience.
To get most out of the course, participants are encouraged to bring a dataset of their own.
| Target Group | The course is aimed at PhD candidates, postdocs, and academic staff. |
| Group Size | Max. 25 participants |
| Course duration | 4 days (09:00-12:30). Participants are expected to be present full time. |
| Number of credits | 0.6 ECTs |
| Lecturers | Stefan Vriend (Netherlands Institute of Ecology, LTER-LIFE) Irene Verhagen (Wageningen University & Research) Sydney Jordan (Wageningen University & Research) |
| Prior knowledge | To get most of out the course, participants are encouraged to bring a dataset of their own. |
| Location | Wageningen University Campus |
| Category | Fees |
| PhD candidates of PE&RC / WIMEK/ VLAG/ WIAS/ WASS/ EPS with approved TSP and WU EngD candidates | € 115,- |
| PE&RC postdocs and staff | € 230,- |
| Other academic participants | € 270,- |
| Non-academic participants | € 500,- |