Том 52, № 5 (2018)

The heuristics of the detection of empirical regularities by the JSM method of automated support of scientific research is considered. This heuristic consists of applying the JSM reasoning for JSM research, which consist of recognizing the preservation of hypotheses about the causes and hypotheses about predictions that form empirical dependencies for embedded database sequences. Mechanisms for detecting empirical regularities are causal forcing (CF), through which the necessity modalities (for empirical laws), the possibility modality (for empirical tendencies) and the modality of weak possibilities (for suspicious tendencies) are determined. The means of approximate detection of empirical regularities are determined and the results of their application for detecting the possibility of diabetes mellitus in patients with chronic pancreatitis are presented.

This article describes the development of recommendations for using the project thinking approach in training and university education of future digital economy specialists. An overview of the key design thinking methodologies is presented. Recommendations for implementing the design thinking approach in academic disciplines are given through an example of a step-by-step description of a specific case. The design thinking approach aims to develop a person’s creative abilities through empirical rules and experience, emotional intelligence and recognizing the value of other people’s opinions. The article describes the methods used in design thinking: visualization tools (empathy, customer journey, and stakeholder maps), Customer Development tools, guerrilla ethnography, POV articulating, and rapid prototyping.

The article also presents the primary tools used in design workshops for developing innovative ideas and adaptive problem solving. A case in formulating design thinking, titled “How can one improve the impression left on the students of professional refresher courses?” is detailed and accompanied by comments on the solutions the participants of presented design workshops.

New methods of integrating scientific data on the properties of substances and materials that apply modern information technologies are analysed. The capabilities of systems created using the Semantic Web and Big Data are explored. Despite some differences in the tasks that are solved, both approaches are oriented towards working with large arrays of web-distributed, structurally heterogeneous data. Several data-integration platforms that have been developed in recent years, including a system designed by the authors, are studied. It is concluded that currently none of the integration systems can fully satisfy specific the requirements of scientific data. Nevertheless, several software elements and technological solutions are of interest and can support the implementation of a project to integrate scientific data on properties of substances and materials.

In this paper, we address the problem of developing a next-generation universal protected trusted digital asset based on a universal data structure and a new trust and security paradigm.