The assessment of Appropriateness territory has been based on four phases:

  1. the Data Product Specification (DPS);
  2. the Upstream Data (UD) description;
  3. the Targeted Data Product (TPD) description;
  4. the calculation of indicators.

ISO Quality Elements have been selected to describe DPS, TPD and UD, consisting of nine ranks plus one expert evaluation on the usability of the product. These Quality Elements correspond to nine quality measures for appropriateness specifically defined within the MedSea Checkpoint.

Quality Errors have been computed for each Targeted Product component from DPS and TPD quality measures and for each UD associated to the Targeted Product as well. “Errors” for Quality Elements are defined as the differences between what has been realized and what was “expected” or “required”.

The appropriateness indicators are related to “errors” in the Quality Elements just defined. Appropriateness corresponds then to “low” errors in the specific quality element.

In the case of appropriateness, it is less immediate than for availability to provide a simple characterization of the indicators at a high level of aggregation. At present, some simplifying assumptions have been applied, allowing a non-expert to easily assess the appropriateness indicators without looking at the metadata and reports.

Appropriateness indicator values can have negative or positive values. The former score is an under-fitting score, representing lower than expected quality while the latter is an over-fitting score. Both scores have been saturated at ±100%.

In order to associate a range of indicator values to a synthetic indicator score, it is necessary to establish “thresholds” for the values. It was decided that products with ‘errors’ within -10% and +10% with respect to DPS are ‘appropriate’ or at least partly adequate. Values smaller than -10% are under-fitting and not adequate while values large than +10% are over-fitting or totally adequate, no need for further development.

Each Targeted Product is associated with its Upstream Data sets to dynamically perform the data adequacy evaluation