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Ideas related to the systematization of educational technologies are of great interest. This is due, among other things, to the principles of symmetry. On the basis of their application, the synthesis of well-established facts and principles in international education will be realized. Practical needs that are directed towards the future will also be realized. This paper is devoted to the study and creation of a methodology that makes it possible to evaluate the resource efficiency of an interethnic digital platform. The developed methodology of resource allocation for the promotion of digital educational programs is unified and can be applied in any region or country. Considering the specific legislative acts on the financial support of higher education and the need for professionals in certain areas, this method allows you to give a qualitative assessment and determine the necessary resources for the development and promotion of an interethnic digital educational platform, identifying the most appropriate areas of education depending on the region or country.

The policy term green infrastructure highlights the need to maintain functional ecosystems as a foundation for sustainable societies. Because forests are the main natural ecosystems in Europe, it is crucial to understand the extent to which forest landscape management delivers functional green infrastructures. We used the steep west-east gradient in forest landscape history, land ownership, and political culture within northern Europe's Baltic Sea Region to assess regional profiles of benefits delivered by forest landscapes. The aim was to support policy-makers and planners with evidence-based knowledge about the current conditions for effective wood production and biodiversity conservation. We developed and modeled four regional-level indicators for sustained yield wood production and four for biodiversity conservation using public spatial data. The western case study regions in Sweden and Latvia had high forest management intensity with balanced forest losses and gains which was spatially correlated, thus indicating an even stand age class distribution at the local scale and therefore long-term sustained yields. In contrast, the eastern case study regions in Belarus and Russia showed spatial segregation of areas with forest losses and gains. Regarding biodiversity conservation indicators, the west-east gradient was reversed. In the Russian, Belarusian, and Latvian case study regions, tree species composition was more natural than in Sweden, and the size of contiguous areas without forest loss was larger. In all four case study regions, 54-85% of the total land base consisted of forest cover, which is above critical fragmentation thresholds for forest landscape fragmentation. The results show that green infrastructures for wood production and biodiversity conservation are inversely related among the four case study regions, and thus rival. While restoration for biodiversity conservation is needed in the west, intensified use of wood and biomass is possible in the east. However, a cautious approach should be applied because intensification of wood production threatens biodiversity. We discuss the barriers and bridges for spatial planning in countries with different types of land ownership and political cultures and stress the need for a landscape approach based on evidence-based collaborative learning processes that include both different academic disciplines and stakeholders that represent different sectors and levels of governance.

In the article, we study the relationship between the information technology component and the tax potential of Russian regions as factors of economic growth and sustainable development. The aim of the research is to develop and test a methodology for assessing the level of information technology development of the Russian regions and its relationship with their tax status. The research methodology involves the use of factor analysis and the method of principal components using the Rstudio integrated development environment and the statistical package IBM SPSS statistics. The indicators traditionally used in international rankings of the information society development are supplemented with data on the assessment of efforts aimed at creating and implementing innovations. The study is based on the following data for the whole Russia, for federal districts, and for regions of the Russian Federation: the number of active fixed and mobile subscribers, the number of fixed and mobile broadband access subscribers, and the number of mobile communication devices. Our calculations made it possible to identify the worst and best regions in terms of the information and technological development of the territory. We have found that the worst regions are Sevastopol, Crimea, Ingushetia, Dagestan, Adygea. The regions with a highly developed information technology component include St. Petersburg, Moscow, Novosibirsk, Karelia, and Murmansk Oblast. The successful experience of the best regions in terms of the level of digitalization should be studied in detail and competently used in other Russian regions. The study showed that the readiness of the territories for digital transformations is determined by the level of their economic development. The tax potential of the regions is the main factor determining the growth of the gross regional product of the subject of the Russian Federation. Territories with highly developed information technology component form significantly higher tax revenues of the budget system per capita. This creates the basis not only for further increasing of the level of informatization, but also for its successful socio-economic development for regions. Thus, the level of the economic development of the region, its gross regional product and tax potential are the basis for effective digitalization. The accumulation of significant tax revenues creates opportunities for financing activities for the digitalization of the region. Further research could be in the following main areas: a competent increase in the number of indicators used and the expansion of time horizons; application of successfully tested research methods for other states, their groups and international associations; supplementing of the applied methods with models that have proven themselves well when working with short series, for example, ARIMA models