Today, the government pays special attention to science and science popularization. This includes legal regulation, in particular, and makes the focus of the humanities scholars. However, the issues of the origins of science education of the community, including via the librarianship, are understudied. The goal of this s tudy i s t o r eveal a nd a nalyze t he l egislative a cts o n n on-formal education regulation adopted in 1725–1917. The study focused on the documents comprising definitions related to the science popularization in its modern sense. In Part 1, the author discusses the results of content analysis of the legal documents regulating operations of the Academy of Sciences, libraries, museums and exhibitions. It was found that the first legal regulations of the science education date back to the early 18th century and were addressed to the Academy members. The public lectures delivered by scholars, museum displays, excursions, translations of the popular science reviews and publications were the earliest legally regulated science popularization forms in Russian history

The author proposes an approach to study special interest communities based on the graph of researchers carrying up studies within the same discipline. The co-authorship graphs are the constructs of scientific collaborations popular owing the initial apparent “acquaintance” of the researchers documented in their articles. Many real networks are characterized by the clusterization, which means that the graph topology, as a real network model, is organized in communities, i. e. subgraphs with more internal connections than external ones. The analysis of communities resulted from co-authorship graph breakdown enables to identify the basic characteristics of the communities, e. g. their type (research thematic lines), number of researchers in the community and their interconnections. In the case of several communities of the same special interest, their consolidation determines the main lines of studies within the scientific discipline and generalized data like the total number of communities and researchers in each consolidated community. In their turn, these data can be used for administrative decisions on stimulating relevant and actionable studies. The author discusses the results of testing of the proposed approach on the basis of Math-Net.Ru portal data. Practically, the testing results prove the need to stimulate the studies in robotics and robotic systems, combustion and explosion, information protection methods and systems. The testing results evidence on the adequacy of the used mathematic models and potentiality of the approach direct transfer to other disciplines. The key is to have the complete and reliable basic bibliographic information on co-authorship within the scientific discipline under the study for the large enough time period.

The subject classification of research publications enhances navigation in the flow of science literature, enables bibliometric analysis, multitier assessment of research performance. The universal character of the UN agenda of sustainable development and importance of sustainable development goals (SDGs) and scientific research to achieve them, and the complex and multiaspect SDGs stir high interest of bibliographers, scientometrics community, international science databases, in the problem of correlating science publications and SDGs. The Web of Science, Scopus, Dimensions, as well as the individual researchers apply various approaches to classifying the articles on SDGs, and these classifications have their strengths and weaknesses. The differences in the resulting classifications calls for the analysis and improvement of methods and approaches. The evolving generative artificial intelligence technologies and big language models open up new possibilities for the subject classification of science texts including those related to the UN SDGs. The authors analyze the methods used to classify publications as SDG-related, and demonstrate the applicability of big language models as exemplified by ChatGPT

What the library in the future will look like? What the modern library has to be to have a future? To answer these questions, we are to imagine the library of the future based on modern realty and prospects for social advancement. Today, the concept of “green libraries” as the libraries of the future has become increasingly popular in the world. The researchers discuss enthusiastically and conceptualize the key ideas and characteristics of “green libraries”.
The article logically breaks up into two parts. In Part 2, the authors discuss the findings of monitoring of the library websites and available through them thematic information resources on ecology and sustainable development, and analyze the survey results. Through monitoring accessible materials (library websites and subject-related digital resources in ecology and sustainable development), and survey analysis, the authors conclude on the need for the list of “green libraries”, e-libraries and digital information resources on ecology and sustainable development, and, in the long run, the national standard for “green libraries, and professional development educational course

The institutional repositories (IR) with the open access to research and educational collections play significant role in the open science infrastructure. The metadata provide IR content discoverability and repository effectiveness. The author analyzed 25 repositories of Russian educational organization to specify the metadata detail level and correctness. The educational organizations under the study are the members of “The Priority-2030” Program. It was found that the metadata comprised mainly the basic elements: title, publication data, document language and type while the data on co-authors, editors, research teams and sources are much more rare. The structural data, i.e. data on contents, formats, volume are often not included, too. Very rarely, the metadata comprise links, subject scope, and accessibility informationHowever, the metadata are important for information retrieval efficiency, search capabilities, search results refinement, sorting. The more elements the metadata comprise, the more details of repository objects are provided, the higher information discoverability is.

The author discusses the key concepts of the artificial intelligence, computerized analysis and machine learning. The chatbots СhatGPT, GigaChat, Alisa can be used in the libraries and information centers to assist in translations of foreign publications, article reviewing, etc. The author examines the possibility of integrating chatbot into the websites to render the first assistance to the users, in particular beyond office hours. The author reviews using AI for literature system reviewing and argues that the selection process is more efficient, and time is saved. He demonstrates the AI capabilities to improve the relevance of response to the search queries in the library computerized systems and to develop user personal account services. The latter would enable to generate personalized recommendations for articles, patents and reviews within the subject scope of studies and to select the most relevant materials for publication. For the system proper operation, the author suggests to develop the system for evaluation of the produced materials and services quality. Based on this system and requested materials, the personalized analytical and recommendation system can be generated to identify the lines of further research and development. Despite underdeveloped technologies, impossibility of total replacement of the humans, high implementation costs, etc., the AI methods and algorithms of learning and analysis enable to computerize several information processing operations, to reveal patterns and trends, t o p redict u ser n eeds, w hich l ays t he w ay f or d eveloping a nd i mproving services in the libraries and information centers

In the context of librarians’ continuing education, the distance learning technologies have become increasingly demanded. New organizational and methodological solutions are needed and need themselves continuous updating in a fast-paced information and technological environment. The authors suggest using learners' preferences as a criterion of method efficiency. They discuss the findings of the survey of librarians who received training in 2023 within the professional development programs under the federal project “The creative people”. The 2023 survey findings were compared to that held in 2017. The dynamics of the preferences in the learning organization is discussed.