Quality assurance

The quality assurance process ensures that the content and format of the stored data corresponds with the description of the data, in accordance with the specified criteria.

Quality indicators include data

  • flawlessness
  • regulatory compliance
  • consistency
  • comprehensibility
  • unambiguity 
  • updates

Measures forecasting the quality of data are recorded in the data management plan, which includes descriptions of data

  • collection methods
  • structure
  • recording
  • use
  • standards
  • storage

The data management plan shall be written, accepted and applied, during and after research. Particularly after research it must be ensured that the data has been properly stored and adequate data protection has been afforded to sensitive data. Peer review is also part of the quality practices.

Information on quality assurance results is recorded in the metadata.

Please also read through the quality management manual of your university  or institute.