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Data management

Data management can be defined as the creation, storage, maintenance, disclosure, archiving and sustainable preservation of research data.

A framework for a University research data management policy is available (data management regulations). The regulations have been elaborated at disciplinary level.
 
Do you have any questions about data management? Please contact the Centre for Digital Scholarship (CDS).

A data management plan (DMP) must be drawn up before data collection for a research project begins. It is not mandatory for all research projects yet. The DMP elaborates upon the data management policy of the faculty/institute for the specific research project in question.

Some of the questions that are commonly addressed in a DMP:

  • What kind of data will you be collecting?
  • Where will you store your data?
  • With whom and how will you share your data?
  • How will others be able to understand the data?
  • How will you preserve your data for the long term?

A University's data management plan template is available for filling out. 

During the research, research data must be securely preserved. This means that the integrity, availability and – if required – confidentiality of the data must be guaranteed.

Please note, once the research has been completed, the research data must be preserved for the long term together with the metadata, software and other documentation required for reuse. This must also be borne in mind during the research, for instance because it will generally be impossible to provide satisfactory metadata for all the data once the research has been completed.

Research data must be managed in such a way that, at the latest, 

  • at the point in time of the last publication arising from the research, 
  • or at the point in time of the formal completion of the research project

it is preserved so that it is at least findable, accessible, comprehensible and reusable in the long term.

Findable

The data must be findable for other researchers and involved parties. Its findability improves if it is deposited in a (discipline-specific) data archive or repository. The information about the data (metadata) is then registered in a standardised manner and is findable, also for search engines. Future findability is guaranteed by assigning a persistent identifier to the data. A commonly used identifier for data is DOI (digital object identifier). A DOI is assigned by a data archive or data publisher and is a unique number for a digital object, in this case a dataset. The DOI remains the same even if the location of the dataset (URL) changes. A DOI or other persistent identifier is used in citations or references to the dataset.

Accessible

Data accessibility does not necessarily mean that the data must immediately be made fully open. The data will have to be made accessible in some instances, for example for verification by a grant provider or journal but will remain inaccessible to the wider public. With sensitive data, full publication will never be an option. Research data can be retained under embargo; then only those who have deposited the data have access to it. The duration of the embargo is determined in consultation with the data archive. A further option is only to grant access if a request for access is submitted to the researcher. The researcher then knows who is consulting the data and can reach agreements about its use and reuse. NB: if the decision is made to limit access to the data, it is essential that the metadata (description of the data) is findable.

Comprehensible

Metadata and any supplementary documentation must describe the data in such a way that other researchers will also be able to understand and use it.

Reusable

Research data must be stored together with the metadata, other documentation and possibly the software and version of the software required for its potential reuse. 
Research data must be stored in such a way that it is independent of the underlying equipment/hardware, such as microscopes, scanners or recording equipment. Long-term data formats that are supported by data archives should be used if possible. Retention of hardware can be considered in certain cases, for instance in the case of software that is only compatible with an obsolete computer operating system. 
 

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