Proper research data management is very important to SDU, which is why it is highlighted in the SDU Open Science Policy (internal link to RDM Open Science Policy page). The following are some of the components necessary for solid data management practices. Visit the linked pages for detailed information that will help you keep your data well-organized.
- Use descriptive and informative file names.
- Choose file formats that will ensure long-term access.
- Track different versions of your documents.
- Create metadata for every experiment or analysis you run.
- Find helpful tools for analyzing your data.
- Handle sensitive data in an appropriate manner.
Watch this 20 minute e-Learning video for more about the importance of good Research Data Management (in English with subtitles).
This video e-Learning module is the result of a collaboration of the Danish universities, Rigsarkivet and the Danish e-Infrastructure Centre (DeiC). Holmstrand, K.F., den Boer, S.P.A., Vlachos, E., Martínez-Lavanchy, P.M., Hansen, K.K. (Eds.) (2019). Research Data Management (e-Learning course). DOI:10.11581/dtu:00000047
For more information on managing data, check out the article "Nine simple ways to make it easier to (re)use your data" by White, et al. or the book: “Data Management for Researchers” by Kristin Briney.
Document your plan
Once you have started to implement best practices for yourself and your research group, make an effort to document these plans. Include your and your group's procedures for the following:
- Naming files
- Saving and backing up files
- Describing data files
- Tracking versions
You might consider using a OneDrive or Google doc that everyone in your group can access when needed. Be sure to define who is responsible for each task and for setting the overall policies.
Plan for knowledge transfer
As a last step, don't forget to create and implement a plan for how to transfer knowledge about a project when it changes hands or when someone leaves the group. This will help prevent valuable information from getting lost!
This text is adapted from the Stanford University Library Data Management Services website.
Research data alliance (RDA)
What is the RDA?
The Research Data Alliance (RDA) is a grassroots initiative supported financially by the EU, US and Australia with the aim of building the social and technical bridges for sharing and reusing research data - specifically in the form of working groups where researchers and professionals develop, for example, technical standards, guides and domain specific best practices in research data management (RDA outputs).
The Research Data Alliance (RDA) was launched as a community-driven initiative in 2013 by the European Commission, the United States Government's National Science Foundation and National Institute of Standards and Technology, and the Australian Government’s Department of Innovation with the goal of building the social and technical infrastructure to enable open sharing and re-use of data.
The RDA community includes researchers, scientists, IT specialists, data professionals, and other experts. All data lifecycle stages are covered - topics include i.a. data publication, data citation, data management planning, data processing, data interoperability.
What can the RDA do for you?
RDA recommendations (formally endorsed) enable data sharing, exchange and interoperability - they include i.a. specifications, taxonomies, ontologies, workflows, data models. RDA recommendations and outputs contribute to tackle real-world challenges.
To get an understanding of how recommendations are applied by different disciplines such as climate research and agricultural sciences, read more here.
The Danish RDA node
Join the Danish RDA community here. Membership is free!
Frequently asked questions