Data Quality

The GCP strives to produce research data of high quality. In order to actually achieve this, the GCP Data Quality Strategy was formulated.
The GCP Data Quality Strategy specifies the policy supporting the generation and maintenance of high quality data, thus realizing standarisation in data quality practices. The GCP strives for the mandatory application of QA/QC best practices and actively promotes the application of the QA/QC best practices for existing data compiled.

Data quality aspects consist of data quality assurance (QA) and of data quality control (QC). QA is complete documentation of the perceived quality of a given datum. QC is the assessment of QA levels at defined input/output control points, in a data flow stretching from data source to usage point. Whenever possible feedback remedial process efforts are applied to the workflow to increase the data quality.
Of course both QA and QC are supported by norms in standarisation.


More information

• quality assurance and improvement


• quality management in GCP laboratories


• standardisation

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