Industry 5.0 is an integral driving force for industrial development to overcome a resurgent strategic drift. This solution is a perfect tool to ensure a sustainable, human-centered, and resilient industry and encourage man-machine collaboration within intelligent cyber-social systems. A complete shift to Industry 5.0 is only feasible when industrial systems apply digital strategizing to enhance digital development. That would invite technologies and humans to facilitate all operational and customer dealings, significantly increasing the rate of innovation. This research aims to articulate a multi-perspective conceptual framework based on the premises of digital development of industrial systems in the strategic drift to Industry 5.0. The methodology implied in this research rests on an interview with industry experts, a case study of digitalization leaders in 2021, extensive and systematic literature review and scientometric analytical tools, content analysis and foresight. In this paper, the authors reframe the concept of digital strategy and consider it as a notion independent of digitalization strategy and digital transformation strategy that is traditionally based on the formation of digital thinking, implementation of digital behavior patterns, the transformation of mindset, and strategic wisdom. As a result, a brand-new perspective on Industry 5.0 is suggested -Nooindustry 5.0. This digital development framework provides grounds for a digital business strategy to advance and shapes a platform-operating model to nurture the digital maturity of industrial systems. This research identifies key strategies for the transformation of an industrial system into a bionic one to sail through the current strategic drift. Further scientific work has to be carried out in order to assess the impact and effects of digital development of industrial systems while shifting to Industry 5.0.

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Information support for decision making for planning activities in the Arctic and management of the Arctic territories of the Russian Federation using spatial information visualization tools is an important and urgent task. To effectively address this challenge, it is necessary to develop specialized information tools that focus on the analysis, processing, and visualization of large amounts of information to support decision-making. Such tools include methods and technologies for extracting spatial data from texts in natural language for their further visualization. This paper describes the first part of a large complex of research works aimed at creating methods, technologies, algorithms and software for visualization of spatial data extracted from texts in natural language. At this stage of the work the technology of geodata extraction from the Arctic texts written in Russian is being developed. The paper also substantiates the prospects of application of the created methods and tools to support decision making in the field of territory planning and regional management. The review of named entities recognition problems on the basis of the analysis of scientific works executed in various areas of processing and the analysis of texts is resulted. The main approaches to text analysis and the most significant results achieved so far in this area are considered. The technology developed by the authors to extract spatial data from texts to support decision-making in planning and management of territories is part of a larger system to support socio-economic development of the region. This system is primarily focused on the Arctic territories of the Russian Federation and includes modules for analysis and visualization of geodata identified in the text analysis. The paper describes the research problem, the methods and tools used for text analysis, as well as the main results.

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