  The most valuable asset of a space mission like Euclid are the data. Due to
their huge volume, the automatic quality control becomes a crucial aspect over
the entire lifetime of the experiment. Here we focus on the design strategy for
the Science Ground Segment (SGS) Data Quality Common Tools (DQCT), which has
the main role to provide software solutions to gather, evaluate, and record
quality information about the raw and derived data products from a primarily
scientific perspective. The SGS DQCT will provide a quantitative basis for
evaluating the application of reduction and calibration reference data, as well
as diagnostic tools for quality parameters, flags, trend analysis diagrams and
any other metadata parameter produced by the pipeline. In a large programme
like Euclid, it is prohibitively expensive to process large amount of data at
the pixel level just for the purpose of quality evaluation. Thus, all measures
of quality at the pixel level are implemented in the individual pipeline
stages, and passed along as metadata in the production. In this sense most of
the tasks related to science data quality are delegated to the pipeline stages,
even though the responsibility for science data quality is managed at a higher
level. The DQCT subsystem of the SGS is currently under development, but its
path to full realization will likely be different than that of other
subsystems. Primarily because, due to a high level of parallelism and to the
wide pipeline processing redundancy, for instance the mechanism of double
Science Data Center for each processing function, the data quality tools have
not only to be widely spread over all pipeline segments and data levels, but
also to minimize the occurrences of potential diversity of solutions
implemented for similar functions, ensuring the maximum of coherency and
standardization for quality evaluation and reporting in the SGS.
