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These days, there is no way around research data management (RDM) in research. But why is that so? And what advantages does RDM offer?
Why is RDM Important?
RDM is an important part of the research process that relates to the handling of research data. It includes planning and implementing the preparation, storage, archiving as well as publication of the data.
In science, research data is the one important resource. The responsible handling of this resource is a prerequisite for the preservation and dissemination of scientific knowledge and thus an essential basis for scientific progress.
However, RDM not only brings added value for science and society, but also for researchers and those who use the data afterwards, and thus promotes the scientific community as a whole.
Quality and Efficiency
When researchers name, describe and organise their data with the help of common, standardised rules, they maintain an overview not only of their own data, but also of the research data to be processed collaboratively.
With the right documentation and preparation of the data, duplicate work (e.g. renewed time-consuming familiarisation with the data due to staff turnover) and surveys are also avoided. This not only saves time, but also conserves resources.
RDM thus improves the quality of the data and ensures its completeness.
Security and Protection
The risk of data loss is minimised by RDM measures such as data documentation, systematic and regular (at best even automated) data backup, future-proof file formats and appropriate long-term archiving. The research data platform Coscine supports researchers in this.
Visibility and Re-use
The publication and availability of research data can increase the visibility of projects and thus also their citation frequency and reputation. The improved visibility offers researchers the opportunity for collaborations.
At the same time, however, the general transparency of research is ensured, since documented and published research data enable the reproducibility and subsequently also the verifiability of the results. In this way, the publication underlines the reliability of the research.
But that’s not all: reusable file formats and comprehensive descriptions (metadata) facilitate the reuse and further use of the research data in the long term. This lays the foundation for further work and contributes to more efficient science overall. After all, the published research data can be the basis for new findings when further questions are considered.
Integrity and Promotion
With forward-looking RDM, the requirements of good scientific practice are met. These are based on the DFG’s guidelines, the aim of which is to embed a culture of scientific integrity. After all, this forms the basis of trustworthy science.
In addition, a well thought-out RDM increases the chances of receiving funding, since many funding organisations, third-party funders and publishers now require a data management concept as part of the application process. This is to ensure that science and society benefit in the best possible way from the project funds used and that data and results obtained are accessible to the broad masses long after the project has ended.
Learn More
If you have any questions about Research Data Management, simply contact the IT-ServiceDesk. The RDM team looks forward to hearing from you.
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Responsible for the content of this article is Sophia Nosthoff.
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