Information Space Research Articles

Adaptive Space-Aware Infotaxis II as a Strategy for Odor Source Localization.

Mobile robot olfaction of toxic and hazardous odor sources is of great significance in anti-terrorism, disaster prevention, and control scenarios. Aiming at the problems of low search efficiency and easily falling into a local optimum of the current odor source localization strategies, the paper proposes the adaptive space-aware Infotaxis II algorithm. To improve the tracking efficiency of robots, a new reward function is designed by considering the space information and emphasizing the exploration behavior of robots. Considering the enhancement in exploratory behavior, an adaptive navigation-updated mechanism is proposed to adjust the movement range of robots in real time through information entropy to avoid an excessive exploration behavior during the search process, which may lead the robot to fall into a local optimum. Subsequently, an improved adaptive cosine salp swarm algorithm is applied to confirm the optimal information adaptive parameter. Comparative simulation experiments between ASAInfotaxis II and the classical search strategies are carried out in 2D and 3D scenarios regarding the search efficiency and search behavior, which show that ASAInfotaxis II is competent to improve the search efficiency to a larger extent and achieves a better balance between exploration and exploitation behaviors.

TRANSFORMATION OF THE VALUE FOUNDATIONS OF CULTURE INFORMATION NETWORK SOCIETY

In Russian humanitarian thought, the problems of preserving and further developing the spiritual, value component of human activity in the context of a developing information and network society are widely discussed. Informatization, digitalization, expanding the boundaries of the information and network space, constructively transforms human existence. Screen, network culture demonstrates qualitatively new approaches to understanding the phenomena of "culture", "values", "norms". The ideas propagated by virtual countercultures and subcultures aimed at the formation of utilitarian, hedonistic attitudes contribute to the leveling of ethical, moral principles, and the de-formation of a value system. This indicates that the dynamics of value bases is shifting from the highest to the lowest pole: from spiritual to material, from traditional to universal, from socially significant to individual values. The focus of this problem is to create a humanistically oriented environment filled with ethical imperatives and fundamental values.

REVIEW AND ANALYSIS OF PREVIOUS RESEARCH IN THE FIELD OF CYBER PROTECTION OF THE INFORMATION SPACE OF EDUCATIONAL INSTITUTIONS

The article considers the prerequisites for the formation of a secure information and educational environment of a modern university. Publications of domestic and leading foreign studies were analyzed. An overview and analysis of previous research in the field of cybersecurity of the information space of educational institutions was carried out. The analysis of publications published on this topic was carried out. The analysis confirmed the relevance of the problem of further development of models for VHS in the tasks of continuous mutual investment of the system of higher education institutions. Analysis of publications based on the results of research on the use of Petri nets to describe the model of cyber threats of informatization objects was carried out. Although these works make a significant theoretical contribution to this task, in our opinion, the programmatic implementation of the models proposed by the authors, in particular, The an in the ICIS and ICS on ICS, is somewhat difficult. This, in turn, requires additional research.

Research of the optimization problem of structure hierarchical communication network with changing its parameters

The article is devoted to the study of the problem of optimizing the hierarchical structure of a multicommodity communication network with discrete flows when changing its important parameters, such as the capacity of network arcs in transport blocks and the size of the transport block for transportation of the discrete small-lot cargo or of the data transmission in a digital communication network. The network has three levels of hierarchy – a backbone, a zonal and an internal and four types of nodes - backbone nodes of the first, second and third types, forming the backbone and zonal levels of the network, and nodes of the fourth type, which subordinate to each backbone node and forming the internal levels of the network. Types of nodes differ from each other in terms of functionality. The main task of the study is to establish how the structure of the backbone network changes (the number and location of backbone nodes of the first, second, and third types), the flow processing and distribution scheme, and the technical and economic indicators of the network's functioning for different values of its parameters. The principles of organization of sorting and distribution of flows in a three-level network and its mathematical model are given. A mathematical model of the optimization problem of the backbone network structure and flow sorting and distribution scheme is formulated. Algorithms for solving the problem are based on the discrete analogue of the local descent method proposed by the authors earlier, when the neighborhoods of the metric space of possible solutions are chosen based on heuristic considerations, taking into account the specifics of the problem being solved. Computer modeling of the problem on a network containing 10 nodes at the specified change in the both parameters is carried out. The modeling was carried out on the example of the transport network of cargo transportation using a computer program that is part of the instrumental software of the Information and Analytical Decision Support System (IA DSS), which is being developed at the Institute of Telecommunications and Global Information Space of the National Academy of Sciences of Ukraine. An experimental study of solution the problem showed that the structure of the network is weakly dependent on the change in the carrying capacity of the arcs and the size of the transport block. The proposed computer technology for solving problem when the network parameters are changed allows you to interactively modeling various options of a network, changing the topology, hierarchical structure, flows, parameters and constraints of the model and from the set of the obtained solutions to choose a best option, taking into account the selected a goal function and the accepted constraints; calculate preliminary technical and economic indicators of the network's functioning, estimate the cost of additional resources and plan the amount of investment required for the modernization and construction of its structural elements, which ultimately makes it possible to increase the efficiency functioning of the network by optimizing use of its resources and reducing the operating costs for the processing and transportation of flows.

A Walk on the Retrograde Side (WRS) project

Relics of ancient accretion events experienced by the Milky Way are predominantly located within the stellar halo of our Galaxy. However, debris from different objects display overlapping distributions in dynamical spaces, making it extremely challenging to properly disentangle their contribution to the build-up of the Galaxy. To shed light on this chaotic context, we initiated a program aimed at the homogeneous chemical tagging of the local halo of the Milky Way, focusing on the component in retrograde motion, since this is expected to host a large fraction of stars accreted from past mergers. The A Walk on the Retrograde Side (WRS) project targets retrograde halo stars in the solar neighborhood with accurate 6D phase space information available, measuring the precise chemical abundance of several chemical elements from high-resolution spectroscopy. In this first paper, we present the project and the analysis of high-resolution spectra obtained with UVES at VLT and at LBT for 186 stars. We obtained accurate radial velocity and chemical abundances for several elements for all the target stars. In particular, we focus on the chemical composition of a specific subset of substructures that have been dynamically identified in the literature. Our study reveals that two among the more recently discovered structures in the retrograde halo, namely, Antaeus/L-RL64 and ED-3, have identical chemical patterns and similar integrals of motion, suggesting a common origin. In turn, the abundance patterns of this unified system differ from that of Gaia-Enceladus, confirming that it is an independent structure. Finally, Sequoia exhibits a different chemistry with respect to that of Gaia-Enceladus at [Fe/H] < −1.5 dex, showcasing an excess of stars with lower Mg and Ca in the common metallicity range.

Ведущие профессиональные компетенции преподавателей образовательных организаций МВД России с различным стажем педагогической деятельности

Introduction. The article describes theoretical and empirical data of the analysis of professional competences of experienced lecturers and newcomers in educational organisations of the Ministry of Internal Affairs of Russia. The relevance of the scientific issue consists in the need to substantiate the system of professional competences of a lecturer of a higher educational organisation. The novelty of the research is in the study of the professional competencies of lecturers of educational organisations of the Ministry of Internal Affairs of Russia as a system that reveals the content of his/her professional activity. The authors draw particular attention to the transformation of educational goals, requiring the skills of competent interaction in the information and multicultural space; as well as to the increasing significance of the upbringing function of the pedagogue, and the need to gain experience in pedagogical activities by employees recruited to educational organisations as lecturers from territorial departments of internal affairs bodies. The authors present the professional competences: self-organisational, informational, interactive and multicultural competences as the most essential in modern realities, which are formed in the context of professional pedagogical culture and determine the professional success of a higher education lecturer. The purpose of the research: to identify the expression and nature of the relationship between selforganisational, informational, interactive and multicultural competences, based on pedagogical activity experience. Methods. The research involved 117 lecturers of educational organisations of the Ministry of Internal Affairs of Russia from 23 to 52 years old, including 62 newcomers with up to one year of pedagogical experience and 55 experienced lecturers with 6 to 25 years of pedagogical experience. Methods aimed at the analysis of the professional competences were applied: “Professional competences of a lecturer of a higher educational organisation” (S. A. Pavlova, N. A. Deeva); “Technological Readiness Index (TRI)” by A. Parasuraman, K. Colby (adapted by Y. V. Khlopovskikh); “Integrative questionnaire of intercultural competence” (O. E. Khukhlaev, V. V. Gritsenko, A. V. Makarchuk, O. S. Pavlova, N. V. Tkachenko, Sh. A. Usubyan, V. A. Shorokhova); “Diagnostics of pedagogical communication styles” (N. P. Fetiskin, V. V. Kozlov, G. M. Manuilov); “Diagnostics of self-organisation features” (A. D. Ishkov). Data collection was carried out by means of a survey using electronic forms, sending e-mails and face-to-face questionnaires. Results. The results confirmed the hypothesis that the expression and nature of the relationship between the professional competences of a present-day lecturer are related to pedagogical activity experience. The results revealed a greater number of links between the competences in the group of experienced lecturers in comparison with the group of newcomers; the presence of significant correlations with personality characteristics in experienced lecturers; the greatest structuring of classification attributes of the studied professional competences with differentiation by gender, age and pedagogical activity experience in the group of experienced lecturers.

Functions of the scientific and methodological activities of the Vernadsky National Library of Ukraine

The article substantiates the basic functions of the scientific and methodical activity of the Vernadsky National Library of Ukraine in modern conditions. It is argued that in the realities of wartime, the scientific-methodical activity of the Department of Scientific-Methodical Work of the Institute of Library Science of the Vernadsky National Library of Ukraine is aimed at optimizing the activities of the main scientific and information complex of the state, improving the work of the libraries of scientific institutions of the National Academy of Sciences of Ukraine, and is implemented at the national level levels for the effective development of the Ukrainian library and information sphere and the successful integration of the assets of national science, education and culture into the global information space. It is emphasized that scientific and methodological work is an inseparable component of the scientific activity of the Vernadsky National Library of Ukraine and has a decisive influence on the scientific and methodological support and development of the libraries of scientific institutions of the National Academy of Sciences of Ukraine. It is concluded that the scientific-communication model of scientific-methodical activity makes it possible to effectively implement such essential functions as innovative, scientific-analytical, scientific-research, scientific-informa­tional, scientific-educational, scientific-consulting, scientific-communication, managerial and scientific-monitoring.

Introduction: Where Next for Public Service Broadcasting?

AbstractGood quality information is a public utility: the rich and powerful will always have access to what they need to know, but poor people do not. Indeed, increasing inequalities in access to decent information underlie other more obvious inequalities. Bad information does not respect borders and yet democracy depends on informed citizens. The case for public intervention in what used to be called broadcasting, now including digital media—but which needs to be thought of as a public information space—is at a tipping point. This collection of essays sets out these vital challenges and offers some innovative solutions.

Scaling the wall: overcoming barriers to STEM knowledge mobilization

Improving science literacy is crucial amidst global challenges like climate change, emerging diseases, AI, and rampant disinformation. This is vital not only for future STEM generations but for all, to make informed decisions. Informal science communication efforts such as podcasts, popular science articles, and museum events are an essential part of the infrastructure for mobilizing knowledge and nurturing science literacy. However, in this Perspective, we emphasize the need to grow our capacity for STEM outreach in the formal K-12 classroom. While the majority of informal outreach mechanisms require audience members to seek out content, classrooms include those hard-to-reach target audiences that are not already STEM-engaged. We contrast the multitude of resources that have been developed to support informal outreach in recent decades with a relative paucity of such efforts in the K-12 formal classroom realm. We advocate for a more balanced deployment of resources and efforts between these two vital components of our knowledge mobilization and STEM engagement infrastructure. In particular, we highlight the key role of K-12 teachers as conduits for knowledge dissemination and the need for greater collaboration between scientists and teachers at individual and organizational levels. We also advocate for greater collaboration across programs in both the informal and formal outreach space, and dedicated effort to construct dissemination networks to share outreach materials at scale across disparate programs. The aim of our piece is to generate discussion about how we might refocus goals, funding mechanisms, and policies to grow the science-engaged society necessary to confront future challenges.

Legal communication of state authorities as a means of interaction in the informational and legal space

In the article, the authors conducted a scientific study of communication as a legal phenomenon, analyzed the national legislation on legal communication in Ukraine, and made a comparative analysis of the features of legal communication in Estonia, Norway, and Sweden. The concept of «legal communication» is also directly clarified, the problems of legal communication in Ukraine are highlighted. The groups of communication in the field of jurisprudence are distinguished into legislative, judicial, and advocacy, foreign experience of legal communication of the specified types is given. It was emphasized that effective legal communication between state authorities and civil society is an important manifestation of the country’s democratic development. It is through such a phenomenon as legal communication that a feedback occurs, when the government can not only better inform the society about its activities, but also learns about the evaluation of these activities by active segments of the population, representing institutions of civil society. The authors conclude that modern legal communication is one of the necessary conditions for successful management and functioning of the state. The result of communicative interaction is the creation of the main administrative-political and management institutions, the formation of interaction between the authorities and the population. Communication between state authorities and society, the introduction of communication standards in the process of information exchange in society, which is based on fundamentally new principles of equal, mutually responsible dialogue - an integral condition for the democratic development of the state, the formation of civil society. It was determined that high-quality and effective legal communication carried out by the state depends on the current legal framework and its compliance with modern challenges and problematic aspects of social life, which such communication is aimed at. It is the state legal communication that is the regulatory and coordinating mechanism in the relations between the state and society, ensuring the stability and efficiency of the functioning of the social organism as a whole.

Orthogonal graph regularized non-negative matrix factorization under sparse constraints for clustering

The standard NMF algorithm is not suitable for sampling data from low-dimensional manifolds embedded in high-dimensional environmental spaces, as the geometric information hidden in feature manifolds and sample manifolds is rarely learned. In order to obtain better clustering performance based on NMF, manifold and orthogonal constraint, a new type of model named Orthogonal Graph regularized Non-negative Matrix Factorization model under Sparse Constraints (OGNMFSC) is proposed. Firstly, this type of model constructs a nearest neighbor graph to encode the geometric information of the data space, in order to obtain more discriminative ability by preserving the structure of the graph. Secondly, this type of model adds orthogonal constraints to achieve better local representation and significantly reduce the inconsistency between the original matrix and the basis vectors. Thirdly, by adding sparse constraints to obtain a sparser representation matrix, the clustering performance of the model can be improved. The main conclusion of this paper is that two effective algorithms have been generated to solve the model, which not only provides theoretical convergence proof for these two algorithms, but also demonstrates significant clustering performance in experiments compared to classical models such as K-means, PCA, NMF, Semi-NMF, NMFSC, ONMF, GNMF, NeNMF.

A new approach to computing the distances between research disciplines based on researcher collaborations and similarity measurement techniques

The measurement of distance between research disciplines involves various approaches, with a focus on publication citation analysis. However, calculating discipline distance requires more than just selecting relevant information; it also involves choosing suitable quantification methods and similarity measures. In this paper, we introduce a novel approach to measuring the distance between research disciplines, referred to as a distance matrix. This approach is particularly useful when there is limited availability of citation data, providing an alternative method for quantifying the distance between disciplines. Our method counts co-occurrences of disciplines based on researcher collaborations in projects and evaluates various similarity measures to convert the co-occurrence matrix into a similarity matrix. We analyze the behavior of different similarity measures and propose functions to transform the similarity matrix into a distance matrix, capturing research discipline dissimilarity effectively. Additionally, we establish evaluation criteria for distance matrix quality. We implement our approach on the Flanders Research Information Space dataset, showing promising results. The distance matrix demonstrates satisfactory density scores, outperforming traditional approaches in skewness and deviation. The probability density functions of distances remain consistent over time, indicating stability. Furthermore, the distance matrix proves valuable for visualizing discipline profiles associated with the dataset, providing valuable insights.

Label enhancement via manifold approximation and projection with graph convolutional network

Label enhancement (LE) aims to enrich logical labels into their corresponding label distributions. But existing LE algorithms fail to fully leverage the structural information in the feature space to improve LE learning. To address this key issue, we first apply manifold learning to map the relatedness between low-dimensional feature samples to the label space. Based on the smoothness assumption of manifolds, the implicit correlation between low-dimensional feature and label spaces effectively promotes the LE process, enabling the learning model to accurately capture the mapping relationship between feature and label manifolds. This leads to an LE based on feature representation (LEFR) algorithm. We also propose an LE algorithm based on graph convolutional network (GCN), called LE-GCN. Inspired by the relationship between threshold connections and label connections, we extend GCN to the LE field for the first time to fully exploit the hidden relationships between nodes and labels. By enhancing node information with threshold connections and label connections, the label learning accuracy reaches a new level. Experiments on real-world datasets show that our LEFR and LE-GCN outperform several state-of-the-art LE algorithms.

Mixed Geometry Message and Trainable Convolutional Attention Network for Knowledge Graph Completion

Knowledge graph completion (KGC) aims to study the embedding representation to solve the incompleteness of knowledge graphs (KGs). Recently, graph convolutional networks (GCNs) and graph attention networks (GATs) have been widely used in KGC tasks by capturing neighbor information of entities. However, Both GCNs and GATs based KGC models have their limitations, and the best method is to analyze the neighbors of each entity (pre-validating), while this process is prohibitively expensive. Furthermore, the representation quality of the embeddings can affect the aggregation of neighbor information (message passing). To address the above limitations, we propose a novel knowledge graph completion model with mixed geometry message and trainable convolutional attention network named MGTCA. Concretely, the mixed geometry message function generates rich neighbor message by integrating spatially information in the hyperbolic space, hypersphere space and Euclidean space jointly. To complete the autonomous switching of graph neural networks (GNNs) and eliminate the necessity of pre-validating the local structure of KGs, a trainable convolutional attention network is proposed by comprising three types of GNNs in one trainable formulation. Furthermore, a mixed geometry scoring function is proposed, which calculates scores of triples by novel prediction function and similarity function based on different geometric spaces. Extensive experiments on three standard datasets confirm the effectiveness of our innovations, and the performance of MGTCA is significantly improved compared to the state-of-the-art approaches.

Trash to Treasure: Low-Light Object Detection via Decomposition-and-Aggregation

Object detection in low-light scenarios has attracted much attention in the past few years. A mainstream and representative scheme introduces enhancers as the pre-processing for regular detectors. However, because of the disparity in task objectives between the enhancer and detector, this paradigm cannot shine at its best ability. In this work, we try to arouse the potential of enhancer + detector. Different from existing works, we extend the illumination-based enhancers (our newly designed or existing) as a scene decomposition module, whose removed illumination is exploited as the auxiliary in the detector for extracting detection-friendly features. A semantic aggregation module is further established for integrating multi-scale scene-related semantic information in the context space. Actually, our built scheme successfully transforms the "trash" (i.e., the ignored illumination in the detector) into the "treasure" for the detector. Plenty of experiments are conducted to reveal our superiority against other state-of-the-art methods. The code will be public if it is accepted.

GSDD: Generative Space Dataset Distillation for Image Super-resolution

Single image super-resolution (SISR), especially in the real world, usually builds a large amount of LR-HR image pairs to learn representations that contain rich textural and structural information. However, relying on massive data for model training not only reduces training efficiency, but also causes heavy data storage burdens. In this paper, we attempt a pioneering study on dataset distillation (DD) for SISR problems to explore how data could be slimmed and compressed for the task. Unlike previous coreset selection methods which select a few typical examples directly from the original data, we remove the limitation that the selected data cannot be further edited, and propose to synthesize and optimize samples to preserve more task-useful representations. Concretely, by utilizing pre-trained GANs as a suitable approximation of realistic data distribution, we propose GSDD, which distills data in a latent generative space based on GAN-inversion techniques. By optimizing them to match with the practical data distribution in an informative feature space, the distilled data could then be synthesized. Experimental results demonstrate that when trained with our distilled data, GSDD can achieve comparable performance to the state-of-the-art (SOTA) SISR algorithms, while a nearly ×8 increase in training efficiency and a saving of almost 93.2% data storage space can be realized. Further experiments on challenging real-world data also demonstrate the promising generalization ability of GSDD.

Foundations of Autonomous Vehicles: A Curriculum Model for Developing Competencies in Artificial Intelligence and the Internet of Things for Grades 7–10

A few states (e.g., Maryland, Georgia, and Florida) have initiated efforts to incorporate artificial intelligence outcomes in K-12 education but others are still relying on informal spaces for learning and literacy in this area. In this manuscript, we share the curriculum and content of an informal effort focused on students in grades 7-10. We combined artificial intelligence competencies with Internet of Things skills to enable meaningful learning covering all Five Big Ideas in AI. In our one-week summer camp, students experimented with perceptions by working with vision, infrared, and ultrasonic sensors. They learned about representation through work with neural network playgrounds. Students engaged in supervised learning of an image processing model and used the model to control the actions of a robot car. Natural interactions and societal impacts were assessed as students observed the robot car's behavior. Results demonstrate that our curriculum was successful in achieving its objectives. Excluding the robot car kit, the curriculum was created using free platforms and tools. This program could be replicated in informal settings by any educator or collaborator with a computer science background. This paper describes our summer camp curriculum, its components and their implementation, the lessons learned, and potential future enhancements.

Introduction to the Special Track on Artificial Intelligence and COVID-19 (Abstract Reprint)

The human race is facing one of the most meaningful public health emergencies in the modern era caused by the COVID-19 pandemic. This pandemic introduced various challenges, from lock-downs with significant economic costs to fundamentally altering the way of life for many people around the world. The battle to understand and control the virus is still at its early stages yet meaningful insights have already been made. The uncertainty of why some patients are infected and experience severe symptoms, while others are infected but asymptomatic, and others are not infected at all, makes managing this pandemic very challenging. Furthermore, the development of treatments and vaccines relies on knowledge generated from an ever evolving and expanding information space. Given the availability of digital data in the modern era, artificial intelligence (AI) is a meaningful tool for addressing the various challenges introduced by this unexpected pandemic. Some of the challenges include: outbreak prediction, risk modeling including infection and symptom development, testing strategy optimization, drug development, treatment repurposing, vaccine development, and others.

ЦИФРОВЫЕ РЕШЕНИЯ В АГРОБИЗНЕСЕ: ФОРМИРОВАНИЕ МЕТОДОЛОГИИ МОНИТОРИНГА ЗЕРНОВОГО ПРОИЗВОДСТВА В УСЛОВИЯХ ТЕХНОЛОГИЧЕСКИХ ИННОВАЦИЙ

The active penetration of digital technologies into human economic activity objectively poses the task of forming an informational space and a new technological base across the entire economic space of society. The appearance of key sectors of the national economy is changing, with an increasing portion of business processes moving into the digital environment, thereby forming a barrier-free character of exchange and consumption relationships. Among the sectors of the domestic economy, the agricultural sector (AIC) has the highest rates of digital activity growth in recent years, with its indicator in 2023 amounting to 200% relative to the average level across the economy – 131% (compared with 2016), indicating the beginning of fundamental transformations within the mode of production. The leader of the AIC is the production of grain and its processing products, collectively accounting for more than a third of the total volume of the agri-food market, hence the processes of digital solutions penetration into grain production require close attention. The key business process of grain production is the monitoring of all its elements, ensuring the quality and timeliness of management decisions at each level of added value production. The spread of business models based on digital technologies requires a new methodology of platform solutions not only at the level of technological adaptation but also restructuring, modification of established ways of conducting agribusiness, and significant organizational changes. Systematization of digital solutions approaches shows that the use of artificial intelligence significantly accelerates the digital transformation of grain production; however, for a widespread transition to intelligent monitoring methods of grain production, a number of objective conditions must be met, among them: data handling, the ability to choose a computer vision model, creation of neural network architecture, organization of training for personnel capable of making decisions on digital platforms, and the formation of corresponding psychological-behavioral client content. The implementation of these conditions, based on ongoing institutional transformations, is capable of ensuring stable growth of grain production, reducing its energy intensity, and preparing personnel with digital economy competencies.

CIS Cross-Border Libraries: Updating the Concept Paper to Strengthen Co-Operation

The experience of the Russian State Library in cooperation with the libraries of the Commonwealth of Independent States (CIS) member states in developing a document regulating cross-border co-operation is presented. It shows the stages of updating the “Concept of Information and Library Space Formation on the Basis of Cross-border Libraries of the CIS Member States” (2009) within the framework of the long-term interstate project of the Eurasia Library Assembly on creation of the normative and conceptual basis of interlibrary cooperation in the CIS. The “Concept...” is harmonised with the universally recognised principles and norms of international law. It reflects the process of inclusion of libraries of border regions of CIS member states in co-operation with libraries of neighbouring countries. Specialists of CIS libraries took an active part in the development of the document. The Concept of Development of Library and Information Space on the Basis of Cross-Border Libraries of CIS Member States (2023) clarifies the purpose and some basic concepts related to the activities of libraries in cross-border cooperation. The definition of “library and information space on the basis of cross-border libraries of the CIS member states” was developed, which is considered as a system of interacting subjects — libraries, library networks, library associations, library staff. The aim of library and information space development is to provide conditions for strengthening interregional and cross-border co-operation. Libraries create and promote various information resources, organise library and information services for the multinational population of border areas to enhance intercultural and professional communication. In the document 2023 the possibilities of subjects of interlibrary cooperation are expanded at the expense of interregional cooperation. The following are defined as subjects of the library and information space: publicly accessible border libraries of the CIS member states, central universal libraries of the border regions, national libraries of the CIS member states. The updated “Concept...” shows the tasks and principles of development, mechanisms and expected results of its implementation. The role of the CIS coordinating bodies in the formation of legislative and regulatory framework for the libraries of the CIS member states is important. Prospects for improving this base lie in the regulation of interregional and cross-border co-operation. To strengthen cooperation it is necessary to reveal the intercultural potential of the CIS member states, to provide scientific and methodological support to cross-border libraries, etc.