Benefits of managing and sharing data

Implementing good RDM practices takes effort and time. But it also yields significant benefits for yourself, the research community, and society at large. No wonder RDM is increasingly considered an essential part of good research practice!

Good reasons for properly managing and sharing research data range from the more selfish/pragmatic to the more altruistic.

Minimizing your risk of losing valuable data

Your digital research data are secured against incidents such as human errors, malicious attacks, natural disasters, or computer failures.

But they are also protected against loss due to the simple passage of time (e.g. data becoming inaccessible because of soft-/hardware obsolescence, or unusable because the details required to understand them have been forgotten).

Increasing your research efficiency

You waste less time trying to locate, understand, and use the data files you accumulate over time.

Facilitating collaborative research

Good organisation and documentation facilitate you and your colleagues working with each other's data.

Also, publicly sharing data can create opportunities for new collaborations, as it increases the visibility of your research.

Supporting research quality and integrity

Adequately documenting your data collection, processing and analysis procedures, and sharing this documentation along with your data is good research practice improving transparency of your research.

Enhancing the visibility and impact of your research

Some studies point to evidence that papers with shared data are cited more (see for example: Piwowar et al. 2007; Piwowar et al. 2013; Dorch et al. 2015).

In addition, depositing research data in a trusted and publicly accessible data repository increases the chance of them being discovered, reused and cited. This means more credit for your work.

Complying with (external) data requirements

Proper RDM helps you navigate and balance the growing demands and expectations regarding research data:

Accelerating scientific discovery

Your research data can be (re)used for data-intensive scientific discovery, and you enable the integration of data from multiple laboratories/groups and even disciplines.

This allows for new research questions, new kinds of analysis, and new approaches.

Increasing return on investment

Generating research data is expensive, but making and keeping data available for reuse avoids unnecessary data duplication and maximises their value.

Living up to the principle that publicly funded research is a public good

If taxpayers fund the research, it is not unreasonable to expect that (subsets of) the resulting research data are made more widely available for the public benefit (e.g. for teaching, policy-making, innovation etc.).