A Research project without effective Research Data Management is like constructing a house without a solid foundation (Kanza et al., 2022).
Imagine your research data as a thriving ecosystem. Just like a garden, it needs regular care and attention to flourish. By focusing on prevention, conducting regular checks, and addressing issues promptly, you can ensure your data remains in best condition.
Why is this important?
- Prevention: Safeguarding your data from potential threats is crucial. Implementing preventive measures helps avoid data loss and corruption.
- Regular Checks: Regularly reviewing your data ensures everything is in order and functioning as it should.
- Prompt Fixes: Addressing problems as soon as they arise, prevents small issues from becoming major obstacles
Research Data Management (RDM) refers to the organisation, storage, preservation, and sharing of data collected and used in a research project.
Effective RDM ensures several key benefits:
What to think about?
Planning for the Future:
- Consider not just the current moment, but how you will look back on your information in several years.
- Plan for sharing information with others, possibly across multiple disciplines, in a form they can easily understand.
Benefits of a Sensible Organisational System:
- The first person likely to benefit from a well-organised system is your future self.
- Good RDM practices ensure data is accessible, understandable, and reusable.
Risks of Poor Data Management:
- Poor data management can lead to data breaches.
- It can result in unsuccessful and potentially harmful research projects.
There are several key components of research data management that shape the final outcome of your research.
