Why do research data management?
The active and responsible management of data is an important aspect of 21st century research, and sharing it is a requirement of many major funders and publishers.
Research Data Management (RDM) is the methodical handling of the information produced or re-used during the course of academic research.
It is a policy requirement of many funders and a legal responsibility. The outcomes of good RDM are that the rights of data subjects/owners are protected and that data is archived towards the end of research so that it remains available for validation of results, and potentially for future re-use.
Together with Open Access publishing and other Open things such as Open Source software, managing and providing access to your research data contributes to the modern goal of Open Research/Scholarship/ Science.
What do we mean by data?
‘Data’ in this context is much broader than the usual dictionary definition. It can be:
- qualitative or quantitative
- factual or non-factual
- numerical, textual or audio-visual
In short, data means whatever is necessary to validate or reproduce your research findings, or to gain a richer understanding of them.
The benefits of active RDM
RDM helps to preserve, protect and proliferate the data behind research discoveries and claims. First and foremost it is about quality and transparency. When research data is managed actively and responsibly, the evidence that underpins research can be made open for anyone to scrutinise and attempt to reproduce findings. This leads to a more robust scholarly record, and helps to discourage and identify academic fraud.
Another primary benefit is protection: the rights and legitimate interests of data subjects and Intellectual Property owners are mindfully protected, and responsible data management reduces the risk of inadvertent data leakage or loss.
Further benefits can be derived from good data management, including:
- Impact: Data linked to publications receive more citations, over longer periods of time;
- Speed: The research process becomes faster, which can be vital in tackling ongoing global challenges;
- Efficiency: Data collection can be funded once, and the data re-used many times for a variety of purposes;
- Accessibility: Interested third parties can (where appropriate) access and build upon publicly-funded research outputs with minimal barriers to access;
- Durability: Simply put, fewer important datasets will be lost or become incomprehensible if they are managed with care.
Learn more about RDM and how you can apply it in your own research projects by choosing an option below.