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Data management describes the set of methodical, conceptual, organisational and technical measures and procedures around the resource “data”. Data should be integrated into business and research processes with its potential for use and optimally utilised in the respective context. Good data management is therefore an indispensable cornerstone of innovative digital research
The documentation of research data encompasses many facets. Data such as measurement series, analyses, surveys with the associated metadata, as well as instruments used, software, scripts, etc. are systematically documented. In addition, rights and role management (who is allowed to do what?) plays a central role in cooperative and interdisciplinary research.
The life cycle of research data extends from the planned creation, collection or request of data, through its processing (organisation, storage) and analysis, to publication and archiving. In between, the documentation of the data and its discoverability for subsequent use are important.
The research data life cycle thus contains various areas that fall within the scope of activities of data centres. These include documentation, analysis, publication and archiving. Our own research in the area complements our existing service offerings. The results flow into our teaching activities, as it were.
As a data centre, we take into account the requirements of digital scientific research data management. Our services and offers support you in designing your data management - simply do sustainable and FAIR research.
In the field of analysis, we research and work on interfaces between different infrastructures and applications to make the data flow as simple and secure as possible for you - whether it is data from experiments, simulations or text collections. Our research interest lies in the feasibility, further development and improvement of applications.
The publication of research results of any kind - classical publications, underlying data and software - is the foundation of new knowledge. We get involved in research when it comes to questions of implementing best practices as standards in our services. Data descriptions (metadata), unique as well as permanent IDs for texts, data, devices and software beyond specific applications increase the visibility of research results.
After the completion of a research project comes the step of archiving the associated data and results. Data is no longer used on a day-to-day basis, but must be preserved for future use according to the specifications of your own organization, your specialist community and the funding organisation. Our long-term archiving infrastructure can support you in this.
