In this section, information is organised around regular research data management tasks or challenges. You will find:
- Best practices and guidelines for each data management task.
- A list of all the considerations to be taken into account when performing a specific data management task.
- Links to task-specific training materials.
- Links to tool assemblies implemented by others to address specific data management challenges.
- Links to a Data Stewardship Wizard for your DMP and to step-by-step instructions to make your data FAIR.
- A summary table of tools and resources relevant for the specific task and recommended by communities.
How to make data analysis FAIR
Information on brokering data to data repositories on behalf of data producers
Best practices to name and organise research data
Ensure high quality research data
How to use identifiers for research data
How to document and describe your data
How to identify different research data types
- Will you collect any data connected to a person, "personal data"?
- Are personal data sufficiently protected?
- Does this dataset contain personal data?
- How is pseudonymization handled?
- Are there privacy reasons why your data can not be open?
- Could the coupling of data create a danger of re-identification of anonymized privacy sensitive data?
- Does this dataset contain sensitive information?