Research data & Research data management

In a project, the handling of data and its planning is visible in many aspects:

• Research proposal: depending on the funding agency, the creation of a data management plan is sometimes required.
• Data collection and processing: In most cases, raw data are created in the project, which are further processed. Data processing may be done by different people at different locations.
• Documentation and metadata: In order to reuse the data later, documentation of the data is necessary. This is usually done through metadata about the project itself, project participants, data collection and measurement parameters, and much more.
• Long-term archiving: When archiving data, the data to be backed up must be selected and backed up using a suitable procedure. The data formats used also play a role here if this data is to be reused in the future.
• Publication: Reusable data should be made available to the community in a suitable form. With information on the resulting publications, the link between data and articles can be established.
• Search: Already existing data can be searched for, e.g. to process them further or to compare them with the own results.

Comparison with other data or additional analysis are possibilities for the subsequent use of research data. Here, new results are obtained from the original data. Type and scope of this use are legally regulated in each individual case.

Added value of published research data:

• Better citability and greater visibility of one's own data. According to Piwowar & Vision (2013), publications are cited more frequently if the associated research data have been published.
• Better findability and accessibility to research data.
• Increased transparency of research

When acquiring public research funding (third-party funding, e.g. DFG or EU), it is necessary to make statements about resulting research data and their publication.