Transformation of the Ackoff's hierarchy in the scientific paradigm of informatics

The DIKW (data, information, knowledge, and wisdom) hierarchy, which was published in 1989 by Russell Ackoff, is considered. In it, wisdom is at the top of the hierarchy followed by knowledge, information, and, at the very bottom, data. It was originally intended that the DIKW hierarchy could be used to describe the relationships between its four components. However, the problem of describing the mutual transformations of two neighboring components, especially for knowledge and information, turned out to be very difficult to solve within the DIKW hierarchy. The complexity of its solution lies in the fact that the DIKW hierarchy implies the generation of knowledge as an outcome of the process of filtering neighboring information but the means of implementing this process were not defined by Ackoff. It is also impossible to describe the semantic interpretation of data, since they are not directly adjacent to knowledge in the DIKW hierarchy which implies the existence of relations between neighboring components only. The aim of the paper is to transform the DIKW hierarchy within the framework of the scientific paradigm of informatics which is based on the medium division of its subject domain into mental, informational, digital, and a number of other media. While Ackoff used the principle of vertical placement of the components, this paper instead proposes to correlate the interfaces and sign systems used in informatics with the relationships between the three components of the hierarchy: data, information, and knowledge. If one uses the principle of vertical placement not of the components but of the media of the subject domain of informatics, then it can be proposed an approach to solving the problem of describing the mutual transformations of the three components of the hierarchy comparing them with informatics interfaces and sign systems. Such a comparison will make it possible to see those pairs of components for which the interfaces are not currently formalized, do not have a computer implementation, and are performed by experts. The paper provides the example of a knowledge discovery technology that combines automatic and expert (nonformalized) technological stages.