Pragmatic quality is how well data meet the requirements that come from their use (users must be able to understand them; they must not be used beyond their obsolescence date), and it has to be expressed as dimensions, each a particular angle for validating requirements that the syntactic and semantic categories do not already cover. A pragmatic validation meets this part only when there exist: definitions of the dimensions used; a description of known dependencies between dimensions; definitions of how the data for measuring each dimension are gathered (by formal requirements, questionnaires, interviews or a mix); and a description of the metrics, giving what each metric is and what it is for (with usage examples recommended), how measurements are presented, and the result for each dimension validated. Where different groups of users use the same data for different ends, the purpose and viewpoint of each kind of user is declared; Annex C offers a coherent set of dimensions.
The graph holds this control, the 0 it maps to, and the evidence behind each claim, over MCP and REST.