Abstract
The development of the general theory of measurement stimulated the expansion of metrological requirements and the nomenclature of data quality indicators, as well as the emergence of new types of measurements, metrological certification and control, in particular, metrological algorithms, models, objects and measurement conditions. As a rule, the practice of modern measurement problems is accompanied by complex experimental conditions associated with the presence of significant a priori uncertainty about the properties of objects and factors affecting the environment of their functioning, the relationship between them, inaccuracies and incompleteness of experimental information, the unavailability of direct observation of many properties of objects or influencing factors, which distinguishes the cognitive function of the methodology for solving them from the fundamental one. Therefore, the formulation of these problems as measurements increases the role of the cognitive function of measurements and requires the results of their solutions in the form of knowledge (analytical expressions for models, as well as conclusions and solutions) based on the entire volume of a priori information and information obtained during the measurement experiment, including nonnumerical information.
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