This paper presents the application of modeling toolkits for optimizing the integration of national scientific and technical documentation archiving systems, assessing the value of document corpora, applying cognitive semantic classification, and defining the subject matter of scientific and technical documents within the CIS and for the Federal Abstract Database of the All-Russian Institute for Scientific and Technical Information of the Russian Academy of Sciences (VINITI Database of the RAS). Models are analyzed for improving the information support of integrating national scientific and technical documentation archiving systems and technology transfer based on interstate exchange and the international scientific and technical information network of the CIS countries within multilateral interstate CIS agreements and the Strategy for Scientific and Technological Development of the CIS for 2026—2035 in order to standardize and digitalize archival acquisition using artificial intelligence, preserve scientific and technological heritage, and provide access to R&D project archives. scientific and technical documentation, archive acquisition, modeling of archive acquisition optimization, document value assessment, cognitive semantic classification of documents, definition of document subject matter, CIS, VINITI RAS, Federal Abstract Database of VINITI RAS, Strategy for Scientific and Technological Development of the CIS for 2026–2035, archive digitalization, archive standardization, technology transfer, use of artificial intelligence
I. N. Sukhoruchkina (Wed,) studied this question.