Digital Transformation and Global Society

Recently, the growing role of social network users in content dissemination has brought to life the concept of secondary gatekeeping – selection and republication of content already selected and published by traditional gatekeepers. Secondary gatekeeping is believed to be raising the media in-platform visibility, but it may also have negative effects such as adding to creation of echo chambers and deepening the gaps between conflicting views. Such studies are particularly relevant for emergencies or social conflicts where sharing relevant content may be crucial for lowering social unease. But till today the nature of secondary gatekeeping remains highly understudied. We have conducted a comparative study of three ad-hoc Twitter discussions on heated ethnic/racial conflicts in the USA (Ferguson riots), Germany (Köln mass abuse), and Russia (Biryulyovo anti-migrant bashings) to assess the patterns of content sharing by active discussants. We used vocabulary-based web crawling and human coding of over 1,000 tweets in randomized samples. Our results show that, in all cases, there’s weak but significant correlation between the type of user and his/her attitude to minority with the attitudes expressed in content, while it is not always true that users prefer the same gatekeeper type, e.g. online or social media. As difference between individual users remains statistically significant, this may mean that the nature of heated ad-hoc discussions facilitates formation of ‘individual-level filter bubbles’ in addition to bigger echo chambers.

The ability of social media to rapidly disseminate judgements on ethnicity and to influence offline ethnic relations creates demand for the methods of automatic monitoring of ethnicity related online content. In this study we seek to measure the overall volume of ethnicity related discussion in the Russian language social media and to develop an approach that would automatically detect various aspects of attitudes to those ethnic groups. We develop a comprehensive list of ethnonyms and related bigrams that embrace 97 Post-Soviet ethnic groups and obtain all messages containing one of those words from a two-year period from all Russian language social media (N = 2,660,222 texts). We hand-code 7,181 messages where rare ethnicities are overrepresented and train a number of classifiers to recognize different aspects of authors’ attitudes and other text features. After calculating a number of standard quality metrics, we find that we reach good quality in detecting intergroup conflict, positive intergroup contact, and overall negative and positive sentiment. Relevance to the topic of ethnicity and general attitude to an ethnic group are least well predicted, while some aspects such as calls for violence against an ethnic group are not sufficiently present in the data to be predicted.

Today, the use of Online Social Media (OSM) is not restricted to merely networking and socializing. Recent events all around the globe attest to the prevalence of use of OSM sites for bringing about dramatic and drastic reforms in real world, phenomenon being referred as Cyber Activism. The real world is marred with various turmoils and people hold myriad variety of views and judgments regarding various issues. Their opinions are often poorly backed by facts. We refer to such inconclusive judgements that users generate and propagate on OSM platforms as Multi-Opinionated Content. One of the greatest challenge in such an environment is to analyze and classify such content into multiple opinion classes. In this work, we propose a generic semi-supervised classification based methodology for analyzing and classifying multi-opinionated content. We have used widely known off-the-shelf classifiers namely KNN, decision tree and random forest in our approach. To implement and validate our methodology, we have mined opinions on content in various forms, namely videos, tweets and posts on three popular social media platforms namely Youtube, Twitter and Facebook, respectively. In our validation, we have taken the Kashmir conflict between India and Pakistan as our case study. We have used plethora of features in building the classification model. Our experiments show that Random Forest classifier gives maximum accuracy of 90.02% and user level features give the best results. Our work can be used to process large amount of multi-opinionated content for effective and accurate decision making in the era of cyber activism generating multi-opinionated content.

The paper focuses on fashion bloggers as cultural intermediaries, which taste origins connect different audiences and groups in the fashion industry. Our sample consists of 15 blogs, which were nominated for two major awards for fashion bloggers Bloglovin.com and Stylight.com in 2015. We analyzed 1223 looks they produced for 1 year (brand choices for every look). We created a two-mode network (blogger - brand) and converted it to the one-mode network (brand-brand). The main research question is whether fashion bloggers as cultural intermediates tend to follow professional community and replicate its hierarchies or rebel against it by creating their owns. The analysis consists of 2 steps. First, we look at three dimensions of brand combination (a) mass-market and haute-couture brands (b) brands oriented to male or female audiences (c) global and local brands. Second, we apply the association rules algorithm to extract combinations of brands matching with not only by the quantity of coupling but probabilistically explore brand unions.

The paper focused on analysis of heterogeneous panel data characterizing recourses, conditions, levels, habits, and effects of online communication between people, enterprises and public organizations. The data were obtained from open access sources of federal and regional government bodies, social media, and service providers, and included statistics on key word searches, communities in social networks, demography of organizations, online purchasing, public online services, indicators of socioeconomics development, and ICT recourses. Multidimensional classification of regions and statistical analysis of dependencies between time-series data items let determine main factors of online socioeconomics activities and provided a technique of their forecasting.

An important role of digital inequality for hindering the development of civil society is being increasingly acknowledged. Simultaneously, differences in availability and the practices of use of social network sites (SNS) may be considered as major manifestations of such digital divide. While SNS are in principle highly convenient spaces for public discussion, lack of access or domination by socially insignificant small talk may indicate underdevelopment of the public sphere. At the same time, agenda differences between regions may signal about local problems. In this study we seek to find out whether regional digital divide exists in such a large country as Russia. We start from a theory of uneven modernization of Russia and use the data from its most popular SNS “VK.com” as a proxy for measuring digital inequality. By analyzing user activity data from a sample of 77,000 users and texts from a carefully selected sub-sample of 36,000 users we conclude that regional level explains an extremely small share of variance in the overall variation of behavioral user data. A notable exception is attention to the topics of Islam and Ukraine. However, our data reveal that historically geographical penetration of “VK.com” proceeded from the regions considered the most modernized to those considered the most traditional. This finding supports the theory of uneven modernization, but it also shows that digital inequality is subject to change with time.

In this study authors examined the relationships between preschoolers’ usage of digital technologies and their social competence. Previous research has shown that there aren’t many connections between children’s ICT using and their social competence. Social competence was measured through three types of a source of information (children, parents, kindergarten teachers). The impact of two independent variables (gender and engagement if ICT usage) on social competence of preschoolers was considered. The findings revealed impact of gender on children’s social competence’s development regarding their engagement in ICT usage.

The ‘VKontakte’ social network is increasingly becoming a useful source of data for studying many aspects of Russian social life. This research paper uses this source to investigate one of the most crucial issues for many young Russians – how successful are Russia’s leading universities in the employability rates of their graduates on completion of their studies. Official data from the Ministry of Education and Science of the Russian Federation show fairly high rates of employment, but the methodology used gives us little indication of the extent to which their employment corresponds to the professional or occupational specialism they acquired at their university. The analysis with the use of the ‘VKontakte’ network provides significant insight into this question. This paper presents results about the employability of graduates from the leading Russian universities participating in the 5–100 Competitiveness and Growth Program specifically in the subjects of “Mathematics and Information Technology” and “Engineering” where a high degree of correlation between subject specialism and employment is expected (The Russian Academic Excellence Project aiming at bringing 5 Russian Universities into their list of the Top 100 world universities (For more details see: http://5top100.com/)).

In this paper, we analyse the strategies and stratification of Russian universities in the Northwestern region. By enriching traditional social network analysis scientometric tools, we developed web presence indicators focused on the contexts in which universities are linked with businesses and are mentioned in media. We treat resulting groups in terms of Gouldner’s cosmopolitans versus locals theory, based on differences in their publication strategies, and embeddedness in business connections and media contexts.

Creation of an information and communication infrastructure of the digital economy requires specialists capable of initiating, developing, and implementing projects in the field of information technologies and communications. In Russia there is still no scientific specialty exactly named Software Engineering for the training of post-graduate students and doctoral candidates. Moreover, such a specialty is missing in the list of scientific specialties on which the degrees of the candidate and the doctor of sciences are defended. The article provides an analysis of the current status of Russian higher education in the field of bachelor’s and master’s training in Software Engineering and related specialties and formulates a proposal to include Software Engineering in the Nomenclature of Specialties of Scientists of the Russian Federation. To solve this problem, it is necessary to organize training for specialists in this area at the third level of higher professional education, namely the training of PhDs - candidates and doctors of sciences - in the field of Software Engineering.

This article discusses the domains of information and communication technologies such as Big Data, Computational Biology, Cloud Computing, Cyber-Physical Systems, Embedded Systems, Information Security, Internet of Things, Human-Machine Systems, Mobile Computing, Machine Learning, Machine-to-Machine, Multi-Agent Systems, Neural Networks, Robotics, Visualization, Augmented Reality, SDN, 5G, e-Governance, Smart City, Smart Grid. The assessment of link strength in ICT research domains is made; refined and formalized semantic networks of ICT domains are constructed based on the metrics of the normalized (information) distance and the semantic similarity proposed in the literature. These semantic networks show the relative values of the research domain and their relation to each other.

Use of social media represents now a global trend that also contaminates the sphere of public administration and other governmental activities. Despite so wide use and popularity of social media among individuals, business and social institutes, they become more and more subject for censorship and blocking with different reasoning and outreach. Recent incidents all over the world show an emerging tendency to restrict social media use by companies, employers and the governments. It is worth noting, that not only China or North Korea which are traditionally famous for their restrictive policies towards Internet activities are spotted for blocking social media but a large part of African countries and even countries rather close to Europe, e.g. Turkey, Ukraine, Russia. The authors are seeking to provide a brief review of reasoning and legal grounds for social media blocking used by the governments.

The article examines the legal issues of dissemination and use of children computer games. Computer games industry affects the interests of many stakeholders. There are various factors that determine the need for introduction of state regulation of legislative measures in this area. The article compares the laws of Russia and America in the field of children computer games provided the protection and rights of children. The research showed the existence of common characters, tendencies and issues in this field, in spite of differences between two countries legislation. The study established legal uncertainty of the ‘computer game’ concept; revealed the scientific community opinion contradiction about the nature of computer games and their valid influence on behavior, health and mentality of children and teenagers; identified the instability of society interest in the legislative initiatives connected with computer games.

The article analyzes the issues related to the legal regulation of games with augmented reality. The authors summarized the numerous incidents, the statements of politicians and legislative initiatives caused by the global fascination with such games. They identified two groups of problems, not typical for the previous generation of computer games. First, the threat to life and health of the player. Second, the threat to the rights and interests of other people and the public interest. The authors proposed the criterion of the prohibition (restriction) of distribution of such games – stimulation of illegal behavior of players. Bodies authorized to apply the appropriate restrictions, as well as means to ensure the ban – legal acts, state information systems – are considered by the example of the Russian Federation law.

Despite the positive aspects of usage of the Internet and social networks within the concept of eSociety, huge data collections available for viewing and analysis to the user of the Internet can contain information which can be unwanted or malicious. The paper considers the problem of protection of users in the “electronic society” infrastructure against such information. The paper discusses the nature of the problem and possible approaches to its solution. To solve the problem it is proposed to use modular approach to construction of automated systems of protection against information, based on application of Data Mining methods. We consider the implementation of the system of protection against unwanted and harmful content, based on the classifier with three-level hierarchical architecture. Its experimental evaluation, which confirmed high efficiency of functioning of the system for most of the analyzed categories of web sites, are also discussed.

Despite certain advances in automation of software quality assurance, testing and debugging remain the most laborious activities in the software development cycle. Evaluation of web interaction quality is still largely performed with traditional human effort-intensive methods, particularly due to the inevitable association of website usability with particular contexts of use, target users, tasks, etc. We believe that testing automation in this field may ultimately lead to better online experience for all and are important in promoting e-society development. We propose to employ artificial neural networks to predict website users’ subjective impressions, whose importance is widely recognized but that are somehow overshadowed by the effectiveness and efficiency dimensions. We justify the structure of the network, with the input layer reflecting context of use, while the output layer consisting of the subjective evaluation scales (Beautiful, Evident, Fun, Trustworthy, and Usable). The experimental session with 82 users and 21 university websites was undertaken to collect the evaluation data for the network training. Finally, we verify the validity of the model by comparing it to a certain baseline, analyze the importance of the input factors, and provide recommendations for future evaluations-collecting sessions.

In this paper, we contribute to the research of e-government development from a demand-side. The study was carried out in groups of online services’ consumers, per E. Rogers adopter categories: innovators, early adopters, early majority, late majority, and laggards. The sociological survey has been conducted with the purpose to reveal differentiation of online services’ users. 450 respondents have been interviewed during the research.The study concentrated on the following indicators connected with citizens or a demand-side: IT skills and Internet usage, online services usage, awareness of new services, level of satisfaction, and reasons of dissatisfaction with the portals.The survey detected a frequent Internet usage, growth of citizens’ awareness of online services portal, interest to the interactive part of the portal, and 4 times increase of satisfaction with online services.The authors proved recommendations for a smoother online services’ adoption by the late majority and laggards groups.

The present article explains the prospects of an anthropological approach to study the effects of the technological innovations.This article is focused on the empirical research of using the Common Government Services Portal in South Russia Region. In the study we used such methods as the in-depth interviews, observation, and experiment. The research guide included four conceptual blocks: Familiarity; Experience in the use of Internet technologies; Interaction with the government authorities; and Experience in the use of Common Government Services Portal.As a result of research, it became clear that many portal users do not realize its connection with the State, but classify it as a part of Internet environment. If the user realizes that the portal is a technological intermediary between the State and the citizen, the practice of using it varies considerably with respect to general Internet practices.

The paper describes a scientific research on e-participation development in Russia. The portal “Russian Public Initiative” has become the research object. This e-participation portal considers to be an official e-petition portal in Russia and was launched in 2013. However, the results of its work are not obvious.In the research, we appealed to the international practice and the national context (revealed after an expert poll) and conducted an analysis of an e-petition portal by using a combination of factors and criteria. The data describing the institutional factors, the results of previously conducted expert poll on e-participation barriers, and applied automated tool to assess the portal operation for the period 2013–2017 was used in the survey.The results show the efficiency through analysis of quantitative data on petitions’ publication, votes for and against the petitions, as well as a qualitative assessment of regulations and decision-making on the petitions that collected the necessary number of votes.

The wide use of social media by public authorities and officials is now an international trend now. Modern political and government leaders find here great opportunities to promote their policies and boost citizens’ participation. On the other hand, recently adopted legal and official documents e.g. Guidelines, Codes of Conduct demonstrate that the use of social media by public servants and employees is not so encouraged or sometimes explicitly prohibited even when it is for purely ‘personal’ purposes. Thus, it becomes evident that national governments seek now to control online activities of their employees explaining it mainly by ethical reasons in order to guarantee fairness, impartiality and neutrality of public service and to avoid any adverse interference. For this purpose, Russia adopted in 2016 a federal law creating an obligation of public servants to declare any use of social media before their authority. This new initiative could shift the existing balance between the right to privacy and public service ethics especially in absence of any coherent and explicit regulation on social media use by public employees in Russia.

The practice of citizens’ involvement in the process of the formation, monitoring and evaluation of performance of the public budget has become one of the most important forms of cooperation of citizens and government. Of particular importance is acquiring a digital form of government where the public use of data creates a solid platform for the modern type of “co-production” of public budgets. Modern budgeting based on cooperation transforms designs of budgetary policy, accountability systems, processes of identifying public values, and others. Ensuring citizen-oriented data relating to the budget here gets particular importance, and sharing the learning of citizens and the government for inclusive budget process becomes the main requisite for successful collaboration. This paper analyzes the Russian practice of open budget and “budget for the citizens” in the context of different requisites: social-economic and informational, which construct an inclusive capacity of the regions. This practice was introduced in 2013 at the federal and regional levels. Though institutions of “budget for the citizens” inure for legitimating regimes, they are also good factors for mutual learning for cooperation. Transparency of budgetary data, its transformation for the citizens, and budgeting, initiated by citizens, affect the character of Russian designs for inclusive budgeting in the regions. On the basis of different ratings of open budgeting and requisites, this paper explains the complex configuration of requisites for the open budget and the ‘budget for citizens’ and three models of introducing forms of e-participation. The main hypothesis of the study is the higher the level of inclusive capacity of the region, the higher the openness of budget data and the “budget for citizens”. For a comparison of 22 Russian regions, the QCA method has been used.

This paper is devoted to the study of political attitudes of Internet-users in Russia. The study is based on empirical data obtained by a survey conducted in 2015 in St. Petersburg. The authors have identified groups of political ideologies’ supporters in St. Petersburg which compose a political spectrum of communists, social-democrats, conservatives, liberals, and nationalists. These ideologically motivated groups tend to be unlike in terms of online news consumption, political online activities, and political approaches to regulate cyberspace. The authors were able to identify ideological groups that can be described as cyber-leftists and cyber-rightists in the Russian Internet.

This article explores the map of political preferences of Russian Twitter users in the wake of March 2017 anti-corruption protests. So far there is little research on the political aspects of Twitter in Russia and our paper seeks to fill this gap in the scholarship. It is based on content analysis of over 45,000 tweets published during a week after March 26 events. According to the project preliminary results, political attitudes of Russians remain fairly moderate, though evidence points to some polarization among the politically involved. The research also reveals a variety of value patterns shared by politically active users and investigates corresponding clusters of users that are taking shape in the ongoing online discussion and networking. The article concludes with an interpretation of how these clusters might relate to menu of political participation during current electoral cycle in Russia.

This ongoing paper is devoted to the empirical study of the interaction between the Internet and the political regime. Departing from several theoretical assumptions, we aim to explore the correlation between the development of the Internet and democracy from 1995 to 2015. Our findings suggest that although the Internet is associated with democracy, this link has been losing its significance over time, and more consolidated autocracies are utilizing the potential of the Internet.

A Science City (SC) is an urban development vision of a Smart City that includes a powerful city-forming scientific-industrial complex in an advanced fashion with a view to managing a city’s assets and human capital. Therefore, the strategic planning of the SC’s socioeconomic development requires as special scientific-industrial and cultural marketing analysis involving citizens in strategic processes (civic participation). Certain factors should be considered, such as the fact that SC strategic planning must be coordinated with the federal government and regional authorities, as citizens are demanding more accountability from the government and it is necessary to create conditions for networked group self-organization. So, SC strategic planning has become a transparent networked multilevel decision-making process where marketing analysis and civic participation are the challenge for Smart City strategic planning methodology. Under such conditions this paper aims to develop the author’s convergent approach (CA), which would help to accelerate the networked strategic meetings by applying Situational Center, Cognitive Modeling, Genetic Algorithm, and Big Data analysis technology for the verification of cognitive models. This study is an attempt to address the issue of applying CA for accelerating SC strategic planning with civic participation and marketing analysis. To portray the issue of scientific-industrial complex and cultural marketing analysis in these terms, Quality Function Deployment was used. This ground was tested in the SC strategic planning process in the SCs of Korolev and Fryazino, Moscow Region, Russia. It was shown that the CA helps to speed up the traditional strategic planning significantly.

The article suggests considering a Smart city as a complex of innovative projects implemented in various sectors of an urban economy. The expediency of implementation of the projects is determined, on the one hand, by the requirements of national and international standards and regulatory documents on urban development, and, on the other hand, by the current needs of city residents. The article presents a formalized set of criteria, which can be used to rank innovative projects in accordance to their importance for implementation within Smart cities. Final part of the article includes results of application of the proposed approach to projects ranking in the process of development of a Smart city in St. Petersburg.

This project will demonstrate how ICT-based solutions can contribute to saving energy by motivating behavioural change of energy end-users. The project will demonstrate how energy service providers can be more open (involvement of end-users and other energy market participants) and innovative (open living lab concept for co-creation and co-design practices) in the development of smart energy solutions. This project will develop an effective intervention to change the behaviour of above-average energy users via training them to use smart tools and coaching them throughout the process. The aim is to increase knowledge of the energy market, change thinking patterns, initiate smarter decisions and through this create actual change in consumers’ behaviour – in pilot test group energy consumption is expected to decrease by 5–10%. This project will integrate at least seven third party digital energy tools with the Estfeed platform that connects over 600 000 energy users in Estonia. Therefore, we expect to deliver and popularise smart tools for minimum of 100 000 of energy-users, with slightly stronger focus on the large-scale users (both individuals and corporate/public).

The paper has deal with the problem of public transport network design. Collected data about people’s travelling in urban area opens up new opportunities related to the design of novel solutions for analysing real needs of people. The issue is how to make a rational choice of preferable PTN according to: (i) a set of selected quality criteria; (ii) decision makers preferences. In the paper we propose a multi-criteria decision analysis (MCDA) method adopted for choice of PTN obtained automatically based on geospatial data analysis. The evaluation criteria of the PTN were developed for the particular task: (i) degree of transport demand satisfaction, (ii) coefficient of non-straightness, and (iii) transport network density. This technique was tested on the routes constructed by the expert, as well as on the automatically generated route. The results suggested by the expert and design in automation mode is close to each other in terms of efficiency. It lead to conclusion that data-driven approaches migh be used for urban planning and monitoring with minimal human intervention.

In this work in progress, we analyze how perceived hotel value dimensions and the perception of city sights are connected with categories of hotels. Applying a topic modelling algorithm to 21,165 reviews from 201 hotels located in Saint Petersburg, we show that clients of hotels of different categories pay attention to different value dimensions. Analyzing local aspect of value perception, we show how existing differences in perceiving the city by guests of the hotels can be explained in terms of the diversity of the socioeconomic status of clients.

Within the framework of this study, the problem of insufficient effectiveness of interaction between information spaces of various departments was discussed, in particular, duplication of hardware, software, data and methods of their processing, which is especially important in the conditions of instability of the economic situation in the country and in a world, and excludes extensive approaches to the region’s information infrastructure development by increasing budgetary funding only. In order to deal with this problem, the notion of NBIC (nano, bio, info, cogni) information space was introduced, the content of NBIC clusters was disclosed. Periodization of the evolution of the regional informatization management system had been carried out, key factors of transition to NBIC convergence were shown. The concept of convergence of information spaces was introduced and its role in the characterized process of NBIC convergence was shown. The synergetic effect of the information space transformation to the NBIC information space has been determined. The necessity of transformation of development vector of the information space for the transition to NBIC information space was shown. The economic efficiency of the transition to NBIC information space has been determined. Methods and models for assessing the social effect from the transition to NBIC information space were characterized. Rationale for improving the management of the information space through the transition to NBIC information space was justified. It was proved that the transition to NBIC information space will allow to ensure the convergence of clusters of information spaces. Finally, conclusions are made about the applicability of developed methods and models in the process of managing the informatization of the region and also further prospects for research are shown.

This paper proposes an ontology based system for storing information on medical diagnostics. The proposed system is focused on a specific way of storing the medical content – it allows the user not only to store standard information in a medical domain, but gives an opportunity to store the ongoing research. The main contribution of this system is its extensibility to contain all types of medical information and its capability to provide the needed research material at hand, including the quickly way of finding and evaluating the controversial current results. This makes it possible for researchers to work together in team and remotely. The system has been tested on real experimental data we obtained in the diagnosis of lung cancer based on gene expression. The experiments have shown that the proposed system tends to cover the needs of users.

The work is dedicated to enhancing the performance of the model calibration framework used for influenza prediction in Russian cities. To increase the speed of calculations and to avoid the decreased fitting accuracy due to local minima problem, the parallelized version of the algorithm is introduced and the comparison of the available optimization methods is performed. The numerical experiments were performed on the data of influenza outbreak incidence in Moscow and Saint Petersburg. The obtained speedup of the calibration algorithm allows to work with bigger incidence datasets and obtain influenza dynamics prediction in more reasonable time compared to the initial serial algorithm. The work results can be applied to enhance performance of different healthcare decision support systems, as well as for increasing the effectiveness of decision making in adjacent areas.

Despite the great potential for healthcare professionals, individuals and researchers, the integration of healthcare information from Electronic Health Records (EHR) and Personal Health Records (PHR) systems is complicated because of structural and semantic heterogeneity. Existing ways of PHR- and EHR-collection include harvesting medical and individual data from different data sources that store different medical, not standardized data. Such a heterogeneity increases the complexity of merging PHR and EHR. We focus on the integration process as a main aspect for solving the heterogeneity issue. Thereby, we aim at reducing the merging complexity by defining the requirements for PHR data collection and creating an ontology for a semantically sound data-set merger for personal-centric healthcare systems and we evaluate the results with formal means.

The article discusses the issues of using e-health technologies and analyses the quality of Internet access for health care services in Russia and the CIS. The paper presents a critical research of financing the introduction of information technologies in health care services in various regions of Russia and proves the necessity of developing and implementing regional standards, the system of certifying both IT services and new types of health care activities. In order to create a single healthcare space, the authors suggest the principle of systematic approach to introducing information technologies in Russian healthcare services.To evaluate the economic efficiency of medical information technologies the authors present various methods based on the specific features of Russian healthcare service. The paper suggests using the Total Cost of Ownership method to assess the efficiency of IT systems as it is this method that can provide a comparative analysis of costs incurred in implementation and maintenance of information technologies. The paper provides a detailed analysis of the benefits of implementing electronic health records for outpatient and hospital healthcare services. The assessment of cost and outcome results in the evaluation of the economic efficiency of implementing IT in medicine.

One of the main problems in the organization of inter-system data exchange and the comparison of data coming from different sources is the identification of similar objects. To solve this problem, it is necessary that the users of information services agree on the rules for naming objects and their identification. In global communities, such as the community of stock market participants, the consistency problem requires the creation of a permanently functioning structure that tracks all changes in the sources of data providers, and updates the codification system data in accordance with these changes. The codification system allows comparison of data coming from different sources and provides quality data to end users. The global stock market is one of the most information rich sectors; performing analysis of stock market data assumes the availability of information from various sources: the various tax authorities, statistical bodies, the national settlement depository, stock exchanges and other sources. In order to collect data from different sources, a methodology is needed to transform the data and bring it to a comparable level.The article describes the experience of applying the information model of inter-agency interaction based on the distributed data core using the codification system. The model presents the organization of a data exchange, which is based on a three-layer core. The article describes the experience of using this model to collect and analyze stock market information. Finally, an example of the model is presented using international identification systems, in particular, a global identification system is considered for the identification of legal entities, and the financial instrument identifier FIGI is considered for the stock market instruments.

Digital transformation is becoming a mainstream of world economic development providing benefits both to consumers and to businesses adapting to the technological change. Russia, among many other countries, is currently developing a digital economy strategy aimed at supporting sustainable economic growth and increasing productivity. This paper aims to add to the current debate on the priorities of digital economy in Russia by benchmarking Russian ICT development with that in the EU countries and identifying some important preconditions for the digital transformation.The analysis demonstrates that while the use for Internet and demand for web-based content in Russia is high even by European standards, in Russia, digital technologies in Russia are still seen more as a means of communication rather than a channel for transactions and a source for enhancing business productivity. The lag in terms of connectivity, digital skills, and business adoption of digital technology is significant and is likely to further increase. The economic incentives driving digital economy in the EU countries (such as high labor costs and competition) are insufficient in the Russian context.Based on the analysis, the new digital economy strategy should be oriented at supporting three main priorities: reducing administrative barriers and creating economic incentives for business digitalization; developing ICT infrastructure with special attention to speed and quality of connection services; and investing in digital skills. These efforts should be complemented by a monitoring and evaluation framework including both core dimensions measured in the EU and sector-specific metrics of digital transformation.

This paper presents analysis of problems and applicability of Knowledge Management (KM) methods in enterprise engineering focusing on KM areas for supporting multiprofessional and multiorganizational teams, organizational structures and business processes created and changed dynamically, including engagement of collective and individual agents from the enterprise ecosystem. Knowledge barriers in the way of adequate agents’ participation in the dynamic environment of dynamic network business process (DNBP) and knowledge-intensive business process (KiBP) requiring better developed knowledge acquisition methods and information support are examined. As a result of the research, the fundamental reason for the knowledge barriers existence is given, and the organizational and dynamic factors which increase damage caused by barriers are provided. The paper describes the priority set of knowledge elicitation, structurization, and representation methods oriented towards knowledge workers, domain experts, or other human agents for organizing agents’ cooperation. The paper suggests the framework of methods aimed at requirements of DNBP and KiBP.

The main objective of this paper is to understand and describe how knowledge management practices are organized in Russian firms of different industries and the extent to which these practices have been adopted to support the business strategy in the digital economy age. Based on hierarchical cluster analysis of 104 Russian companies, this study highlights the specific combinations of KM practices and accents made by Russian managers in this area.