Assessment of the effectiveness of scientific projects on Arctic subjects using machine learning methods

the presented study is devoted to the development of an approach to assessing the effectiveness of the implementation of scientific projects, the results of which are planned to be implemented in the Russian Arctic zone. The main indicators are proposed that allow obtaining a quantitative characteristic of the activities of organizations conducting scientific activities. The study used open data on reports on the implementation of Arctic projects presented in the Unified State Information System for Accounting of Scientific Research, Experimental and Technological Work for Civil Purposes. A software implementation of the developed methodology was carried out, which will allow not only to obtain current values, but also to carry out annual monitoring of certain indicators of the implementation of scientific projects. The results of the analysis were interpreted to obtain a qualitative assessment of the effectiveness of organizations conducting their scientific activities in the interests of the Russian Arctic zone development.

performance evaluation, scientific projects, scientific organizations, Arctic region, clustering method, k-means algorithm