Common Information Research Articles

The interoperability of crystallographic data and databases.

Interoperability of crystallographic data with other disciplines is essential for the smooth and rapid progress of structure-based science in the computer age. Within crystallography and closely related subject areas, there is already a high level of conformance to the generally accepted FAIR principles (that data be findable, accessible, interoperable and reusable) through the adoption of common information exchange protocols by databases, publishers, instrument vendors, experimental facilities and software authors. Driven by the success within these domains, the IUCr has worked closely with CODATA (the Committee on Data of the International Science Council) to help develop the latter's commitment to cross-domain integration of discipline-specific data. The IUCr has, in particular, emphasized the need for standards relating to data quality and completeness as an adjunct to the FAIR data landscape. This can ensure definitive reusable data, which in turn can aid interoperability across domains. A microsymposium at the IUCr 2023 Congress provided an up-to-date survey of data interoperability within and outside of crystallography, expounded using a broad range of examples.

Subgraph Propagation and Contrastive Calibration for Incomplete Multiview Data Clustering.

The success of multiview raw data mining relies on the integrity of attributes. However, each view faces various noises and collection failures, which leads to a condition that attributes are only partially available. To make matters worse, the attributes in multiview raw data are composed of multiple forms, which makes it more difficult to explore the structure of the data especially in multiview clustering task. Due to the missing data in some views, the clustering task on incomplete multiview data confronts the following challenges, namely: 1) mining the topology of missing data in multiview is an urgent problem to be solved; 2) most approaches do not calibrate the complemented representations with common information of multiple views; and 3) we discover that the cluster distributions obtained from incomplete views have a cluster distribution unaligned problem (CDUP) in the latent space. To solve the above issues, we propose a deep clustering framework based on subgraph propagation and contrastive calibration (SPCC) for incomplete multiview raw data. First, the global structural graph is reconstructed by propagating the subgraphs generated by the complete data of each view. Then, the missing views are completed and calibrated under the guidance of the global structural graph and contrast learning between views. In the latent space, we assume that different views have a common cluster representation in the same dimension. However, in the unsupervised condition, the fact that the cluster distributions of different views do not correspond affects the information completion process to use information from other views. Finally, the complemented cluster distributions for different views are aligned by contrastive learning (CL), thus solving the CDUP in the latent space. Our method achieves advanced performance on six benchmarks, which validates the effectiveness and superiority of our SPCC.

Towards simulation of artificial societies of agents with a universal coordination instrument

Developing the models of artificial societies with simulation of agents’ joint socio-economic activity a challenging task is to endow the agents with properties allowing them to mutually take into account each other's intentions and activities. The presence of such properties in agents creates conditions for the emergence of social organization in the modeled system, including processes of coordination and governance. In the proposed study, agents obtain the required properties due to their natural ability to create and use shared (collective) mental models under various modes of communication between them. On this basis, the concept of an agent with a universal coordination instrument (UCI) is substantiated. Agents optimize UCI settings to take full account of each other's activities and maximize the benefits of joint activities. UCI with settings is a common information environment for participants in joint activities, as well as a means of determining the optimal content of their joint activities. The main components and functions of UCI as a special type of agent-based simulation model are discussed. The necessary conditions for using the UCI are considered. From the results obtained it follows that individuals with UCI have both substantive and procedural rationality, which leads to the emergence of two types of equilibrium in the socio-economic system.

Integrating systems of systems with a federation of rule engines

Systems of Systems (SoSs) integrate many critical systems our society relies on. In designing individual systems, stakeholders use bespoke protocols, custom information models, and proprietary components with limited computational resources from various vendors. We present a reference architecture that allows multiple stakeholders to carry out a flexible integration without giving up control to a single entity in the presence of the aforementioned limitations. Our architecture relies on rule engines and graph data model to integrated systems flexibly even when black-box components are used. At the same time, a federation of the rule engines allows each stakeholder to retain control over the rules that reflect their policies. We also rely on a common information model based on ontologies to account for the information model mismatch and reduce the duplication of integration efforts. Moving rule execution to the standalone rule engines allows deployment in resource-constrained and proprietary environments. A uniform application programming interface (API) is used to integrate rule engines across systems as well as components within each system with a respective rule engine. We also present a novel algorithm to determine dependencies across rules deployed in different rule engines within the federation. This allows domain experts to develop rules as usual without having to deal with the distributed aspect of the system. We also present a proof of the sufficient condition to ensure all necessary notifications will be sent to ensure correct rule activation across different rule engines. Compared to other systems involving distributed rules, the proposed architecture is well-suited for the integration of transactional workloads commonly found in enterprises. The qualitative evaluation based on the Architecture Tradeoff Analysis Method (ATAM), applied to a telecommunications use case, shows that the architecture possesses the “interoperability”, “modifiability”, and the “functional completeness” quality attributes with a trade-off around rule expressiveness. The quantitative evaluation demonstrates speedup over the single-node setup in most scenarios except in case of highly optimized rules and a poor network performance simultaneously (tr<10ms, tn=100ms).

주요 국가 자치경찰제도 사례연구와 최신동향 분석

This study analyzed the background and characteristics of the self-governing police system, the status of self-governing police operations (organization, budget, office work, etc.), the composition and role of the police committee, cases of self-governing police, and recent trends, and presented policy implications and directions for the development and efficient operation of the self-governing police system. In Korea, above all, there is a lack of organizations, manpower, office work, and financial research that can implement autonomy and accountability, so it is necessary to derive practical application plans through more detailed consideration of how the autonomous police operate in the future. However, the recent common information related to autonomous police in each country suggested that it is important to operate scientific security and civic participation in the development of information and communication technology, that is, to operate a linkage program with the community, and to establish various governance systems for crime prevention and security activities.

Extending 3D geometric file formats for geospatial applications

This study addresses the representation and exchange of geospatial geometric 3D models, which is a common requirement in various applications like outdoor mixed reality, urban planning, and disaster risk management. Over the years, multiple file formats have been developed to cater to diverse needs, offering a wide range of supported features and target areas of application. However, classic exchange formats like the JavaScript Object Notation and the Extensible Markup Language have been predominantly favored as a basis for exchanging geospatial information, leaving out common geometric information exchange formats such as Wavefront’s OBJ, Stanford’s PLY, and OFF. To bridge this gap, our research proposes three novel extensions for the mentioned geometric file formats, with a primary focus on minimizing storage requirements while effectively representing geospatial data and also allowing to store semantic meta-information. The extensions, named GeoOBJ, GeoOFF, and GeoPLY, offer significant reductions in storage needs, ranging from 14 to 823% less compared to standard file formats, while retaining support for an adequate number of semantic features. Through extensive evaluations, we demonstrate the suitability of these proposed extensions for geospatial information representation, showcasing their efficacy in delivering low storage overheads and seamless incorporation of critical semantic features. The findings underscore the potential of GeoOBJ, GeoOFF, and GeoPLY as viable solutions for efficient geospatial data representation, empowering various applications to operate optimally with minimal storage constraints.

Local structure-aware graph contrastive representation learning

Traditional Graph Neural Network (GNN), as a graph representation learning method, is constrained by label information. However, Graph Contrastive Learning (GCL) methods, which tackles the label problem effectively, mainly focus on the feature information of the global graph or small subgraph structure (e.g., the first-order neighborhood). In this paper, we propose a Local Structure-aware Graph Contrastive representation Learning method (LS-GCL) to model the structural information of nodes from multiple views. Specifically, we construct the semantic subgraphs that are not limited to the first-order neighbors. For the local view, the semantic subgraph of each target node is input into a shared GNN encoder to obtain the target node embeddings at the subgraph-level. Then, we use a pooling function to generate the subgraph-level graph embeddings. For the global view, considering the original graph preserves indispensable semantic information of nodes, we leverage the shared GNN encoder to learn the target node embeddings at the global graph-level. The proposed LS-GCL model is optimized to maximize the common information among similar instances at three various perspectives through a multi-level contrastive loss function. Experimental results on six datasets illustrate that our method outperforms state-of-the-art graph representation learning approaches for both node classification and link prediction tasks.

SELF CARE TRAININGS FOR NCD MANAGEMENT IN OLD AGE IN INDIA

Abstract With over 100 million older people, India has the second largest elderly population in the world. Older people in many parts of India, especially in the rural settings live in vulnerable conditions with limited facilities and with an overall poor health status. GRAVIS has been working actively in the Thar Desert of India to address older people’s health. It has multi-layered health intervention combining medical services, public health activities and research component. Self-care training is integral part of our work with older people. With help of locally designed contents, GRAVIS team trains older people on healthy ageing. The curriculum includes 10 modules focusing on basics of human body and biology of ageing, Common diseases in old age, prevention of common diseases, management of common diseases and useful information on Government health programmes. Older people in groups of 12-15 attend trainings once in 15 days. To provide service to older people and to take self care education further, GRAVIS also works with a cadre of Village based Health Workers (VHWs). The impact of our self-care training interventions has been quite positive. The trainings are well received within the community. Over 1,500 older people have been trained and over 85% report a significant increase in their knowledge levels. GRAVIS has been able to draw the attention of local health authorities and hopes that the trainings could be scaled up further. Self care and improved health knowledge are critically important for older people to stay healthy, particularly in remote and resource scarce settings.

Partially observed optimal control of local and remote controllers

AbstractThe article investigates a networked optimal control problem with one remote controller and local controllers, where each local controller partially observes the local state and sends the observed information to remote controller through an unreliable channel and yet the channels from remote controller to local controllers are perfect. The objective of all the controllers is to cooperate to minimize a common cost function. In order to overcome the difficulties caused by partial observation of state, sufficient statistic of historical data is firstly investigated for a nonlinear non‐Gaussian partial observation model, which takes the same role as that of state in the full observation model. Then, a dynamic programming framework is given for solving the optimal control problem based on the sufficient statistic and common information approach. Furthermore, the explicit closed‐form solution is obtained for a linear‐quadratic‐Gaussian optimal control problem. Finally, a numerical example is given to show the effectiveness of the obtained results of this article.

A MODEL OF THE TWO-LEVEL SYSTEM FOR FORMING INFORMATION AND COMMUNICATION COMPETENCE OF STUDENTS IN GENERAL SECONDARY EDUCATION INSTITUTIONS

The work systematizes the authors’ experience of using information technologies in the educational process of a general secondary education institution and presents the authors’ model of effective development of students' information and communication competence based on it. A model of a two-level system of formation of information and communication competence of students in the educational process has been developed. At the first level of the model, teachers use information tools during lessons to form students' basic knowledge and skills. At the second level, information technologies are used by teachers in extracurricular activities as a tool for creating creative products of students (in particular, scientific research works, educational projects, posters, presentations, video demonstrations), as well as their own developments (pedagogical technologies, teaching aids, etc.), which contributes to the formation of students' comprehensive ability to apply acquired knowledge and skills in practice, and, therefore, information and communication competence. To implement the first level of the proposed model, a comparative analysis of the most common information tools was conducted, the results of which are presented using original schemes. Information tools that ensure high-quality educational process at the "Cossack Lyceum" were subject to analysis: learning management systems – Google Classroom and NZ.UA; video conferencing platforms - Zoom and Google Meet; online boards – Jamboard, IDroo and Flinga; tools for creating information content – Google Presentations, Canva, Prezi and Microsoft Sway; software for simulating natural processes – Phet and Mozaik Education; tools for creating interactive exercises – Mentimeter, Kahoot, Wordwall, Live Worksheets and Learning Apps. The implementation of the second level of the model is shown on the example of a student's creative product created by participating in the competition of the Small Academy of Sciences of Ukraine. We associate promising directions for further research with the development of methodological recommendations for the use of information and communication technologies at various stages of students' creative activity.

Understanding information sensitivity perceptions and its impact on information privacy concerns in e-commerce services: Insights from China

Although research topics related to information privacy in e-commerce services have been extensively studied, we still lack knowledge about consumers' information sensitivity perceptions to the disclosure of different personal information types and its impact on information privacy concerns in this context. To bridge the research gap, we identified 28 common personal information types requested by e-commerce services and investigated (n=1225) Chinese consumers based on an online questionnaire about their information sensitivity to disclosing these personal information types to e-commerce platforms and their concerns for information privacy when accessing e-commerce services. Rooted in information sensitivity literature and multidimensional development theory, we further explored the impacts of consumer individual factors and e-commerce situational factors on information sensitivity, as well as the impact of information sensitivity on e-commerce privacy concerns. Results suggest that personal information types related to personal identity and digital payments are considered the most sensitive in e-commerce services, and consumers have a consensus on which personal information types are more sensitive. Results suggest that both individual factors, such as privacy experience, and situational factors, such as website social presence and perceived privacy control, affect information sensitivity perceptions. Perceived information sensitivity of medium-sensitive and high-sensitive personal information types affect e-commerce privacy concerns, and information sensitivity can mediate the impacts of individual factors and situational factors on e-commerce privacy concerns. Our research helps deepen the understanding of information sensitivity and information privacy concerns and provides practical insights for privacy policymakers and e-commerce service managers.

Development of a Common Information System to Create a Digital Career Center Together with Partner Higher Schools

The purpose of the report presented by the authors is to present a methodical development of a software product and the sequence of its implementation to create a common information system of career centers in Technical University of Sofia and the partner organizations. In fulfillment of the contract BG05M2OP001-2.016-0008-С02 “Innovations, Science and Education for high quality and compliance with the labor market” at the Technical University of Sofia and Partnership (INNOTECH PRO), the goal is to create a single Digital Career Center (DCC), to create a single network by upgrading and modernizing the electronic platforms used so far by the partner higher schools. Through career counseling and guidance and the creation of a Digital Career Exchange (DCE) to give students, graduates, alumni and doctoral students more detailed information and opportunities to find the right job position for each.

AS-Parser: Log Parsing Based on Adaptive Segmentation

System logs have long been recognized as valuable data for analyzing and diagnosing system failures. One fundamental task of log processing is to convert unstructured logs into structured logs through log parsing. All previous log parsing approaches follow a general framework that first segments each log into a token sequence and then computes similarity between two sequences. However, all existing approaches share the common drawback: the flat segmentation with fixed delimiters fails to understand the structural information of logs, which causes low parsing accuracy. To address this problem, we propose a novel log parsing approach, AS-Parser. Our approach introduces a hierarchical log segmentation mechanism that can adaptively segment logs into a tree structure. It can automatically recognize the appropriate delimiters and capture the common structural information. Moreover, we propose three improvements that enhance both the effectiveness and efficiency of our approach. On the public benchmark, AS-Parser performs best on 14 out of 16 datasets, with an average parsing accuracy of 0.943, far exceeding existing approaches.

Perceptions of data journalism and its impact on democratising Arab news media

This study explores the perceptions of data journalism among specialised Arab audiences in the context of declining trust in media and government institutions. Through interviews with respondents from data-processing fields and NGOs, this study examines the perceived effectiveness of data journalism in informing audiences, its credibility compared to existing forms of journalism, and its potential and limitations in democratising the regional media environment. The findings revealed that the perceived effectiveness of data journalism lies in its ability to validate misleading information, provide direction for decision-making, and distinguish itself from common information found on social media or other public sites. This was achieved by offering context, presenting evidence, and supporting claims. However, data journalism is also viewed sceptically, as its perceived ability to inform audiences depends on context and audience. Moreover, the potential for data journalism to democratise the region’s media environment faces constraints beyond the structural and individual limits highlighted in previous studies. It encompasses matters related to journalistic practice and integrity, impacting other forms of journalism in the region.

Building Cyber-Resilient Smart Grids with Digital Twins and Data Spaces

The rapid expansion of digital twin technology has revolutionized management and testing across various sectors, particularly in safeguarding critical infrastructure like smart grids. Aligned with the NIS2 Directive, Directive (EU) 2022/2555 of the European Parliament and of the Council of 14 December 2022, digital twins play a critical role in bolstering cybersecurity measures by enabling advanced simulation and real-time monitoring, key aspects emphasized in the directive for enhancing the security of networks and information systems. Concurrently, Europe’s shift towards communal data spaces amplifies the need for robust cyber defences. This paper aims to bolster cybersecurity defences in critical infrastructure, with a particular focus on the energy sector and smart grids. It proposes an innovative architecture for cybersecurity monitoring, converting a Common Information Model-compliant system into a digital twin via the FIWARE platform and incorporating an open-source Security Information and Event Management solution. Validated by a real-world case study, our approach demonstrates significant advancements in protecting smart grids against cyber threats.

Diplomatic archives: the Polish segment (1918–1991) in the Ukrainian archives

The purpose of the article is to comprehend the essence of the concept of “diplomatic archive” and to review documents, which were created in the activities of Polish diplomatic and consular institutions and/or are related to the development of Polish-Ukrainian interstate relations, preserved in state archives in Ukraine. The research methodology is based on the principles of historicism, determinism, and special scientific methods of scientific heuristics, information analysis, and source criticism. The scientific novelty of the study is determined by a comprehensive analysis of the composition and content of the Polish segment in “the Ukrainian diplomatic archive” – documents generated in the activities of Polish diplomatic missions and consulates in UNR/UkrSSR and materials on surveillance of Polish diplomats in the UkrSSR during 1918–1991. Conclusions. The Polish segment in the Ukrainian diplomatic archive is not a complete set. These are documents related to contacts of the Polish mission with the authorities and institutions of the host country: drafts and texts of treaties and conventions; authorization documents of the heads of Polish diplomatic missions and consulates; official correspondence of the highest state level; documents generated in the course of activities of Polish diplomatic missions and consulates in the host country; documents related to the implementation of consular functions; audiovisual documents; materials of special services’ supervision and materials of party control over the activities of Polish diplomatic missions and consulates. It seems important to create a common archival and information base on the composition and content of Polish and Ukrainian diplomatic archives.

Diplomatic archives: the Polish segment (1918–1991) in the Ukrainian archives

The purpose of the article is to comprehend the essence of the concept of “diplomatic archive” and to review documents, which were created in the activities of Polish diplomatic and consular institutions and/or are related to the development of Polish-Ukrainian interstate relations, preserved in state archives in Ukraine. The research methodology is based on the principles of historicism, determinism, and special scientific methods of scientific heuristics, information analysis, and source criticism. The scientific novelty of the study is determined by a comprehensive analysis of the composition and content of the Polish segment in “the Ukrainian diplomatic archive” – documents generated in the activities of Polish diplomatic missions and consulates in UNR/UkrSSR and materials on surveillance of Polish diplomats in the UkrSSR during 1918–1991. Conclusions. The Polish segment in the Ukrainian diplomatic archive is not a complete set. These are documents related to contacts of the Polish mission with the authorities and institutions of the host country: drafts and texts of treaties and conventions; authorization documents of the heads of Polish diplomatic missions and consulates; official correspondence of the highest state level; documents generated in the course of activities of Polish diplomatic missions and consulates in the host country; documents related to the implementation of consular functions; audiovisual documents; materials of special services’ supervision and materials of party control over the activities of Polish diplomatic missions and consulates. It seems important to create a common archival and information base on the composition and content of Polish and Ukrainian diplomatic archives.

Model-Free Reinforcement Learning for Mean Field Games

In this paper, we have proposed a model-free algorithm, based on sequential decomposition, to obtain optimal policies for. We consider finite horizon with a large population of homogeneous players, sequentially making strategic decisions. Each player observes a private state and a mean-field population state representing the empirical distribution of other players' states. The mean-field state is <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">common information</i> among all the players in the game. Authors in [1] provided a sequential decomposition algorithm to compute for such games in linear time than exponential as in prior literature. We extended the idea of sequential decomposition to propose a model-free algorithm for these games using Expected Sarsa in[2]. In this paper, we provide detailed convergence proofs for our algorithm. In addition, we propose an algorithm for with unknown reward functions. The proposed algorithm learns the reward function by studying an expert's behavior and then computes the optimal policy. We illustrate our results using a cyber-physical security example.

Multiplex Graph Representation Learning Via Dual Correlation Reduction

Recently, with the superior capacity for analyzing the multiplex graph data, self-supervised multiplex graph representation learning (SMGRL) has received much interest. However, existing SMGRL methods are still limited by the following issues: (i) they generally ignore the noisy information within each graph and the common information among different graphs, thus weakening the effectiveness of SMGRL, and (ii) they conduct negative sample encoding and complex pretext tasks for contrastive learning, thus weakening the efficiency of SMGRL. To solve these issues, in this work, we propose a new framework to conduct effective and efficient SMGRL. Specifically, the proposed method investigates the intra-graph and inter-graph decorrelation losses, respectively, for reducing the impact of noisy information within each graph and capturing the common information among different graphs, to achieve the effectiveness. Moreover, the proposed method does not need negative samples for the SMGRL and designs a simple pretext task, to achieve the efficiency. We further theoretically justify that our method achieves the maximal mutual information instead of directly conducting contrastive learning and theoretically justify that our method actually minimizes the multiplex graph information bottleneck, which guarantees the effectiveness. In addition, an extension for semi-supervised scenarios is proposed to fit the case that a few labels are provided in reality. Extensive experimental results verify the effectiveness and efficiency of the proposed method with respect to various downstream tasks.

Межведомственное взаимодействие при организации телемедицинских консультаций по схеме «врач – врач» с участием медицинских специалистов лечебных медицинских организаций Федерального медико-биологического агентства

Summary. The data are considered on conducting telemedicine consultations in 2021-2022 under “doctor – doctor” scheme with participation of attending physicians and consulting physicians of medical organizations (MO) of the Federal Medical and Biological Agency (FMBA of Russia). The division of telemedicine consultations by medical profiles, forms and types is given. The conclusion is made: ensuring the availability and quality of medical care with the use of telemedicine technologies in remote interaction between medical specialists is directly related to the possibility of conducting telemedicine consultations with the participation of medical specialists of MOs of different departmental affiliation in the presence of common information space, including under the conditions of liquidation of medical and sanitary consequences of emergency situations.