Electronic document as a tool of digital economy
The article reviews the problems of using an electronic document (i.e. legally significant computer information) as a necessary tool for building a digital economy. This problem becomes of special importance in terms of implementation of distributed computing in the interests ofmodern technologies, including Big Data,Artificial Intelligence, Blockchain, Industry 4.0,Industrial Internetof Things,Virtual and Augmented Reality technologies, etc. The authors showthat in case of development and adoption ofthe Law "On Electronic Document", we can link the concepts of "Electronic Document" and "Data Message", and can identify several categories of Computer Information (Electronic data interchange) having asignificance: specified Computer data, traffic data, stored Computer data, traffic data,content data.
The article reviews the problems of using an electronic document (i.e. legally significant computer information) as a necessary tool for building a digital economy. This problem becomes of special importance in terms of implementation of distributed computing in the interests of modern technologies, including Big Data, Artificial Intelligence, Blockchain, Industry 4.0, Industrial Internet of Things, Virtual and Augmented Reality technologies, etc. The authors show that in case of development and adoption of the Law "On Electronic Document", we can link the concepts of "Electronic Document" and "Data Message", and can identify several categories of Computer Information (Electronic data interchange) having a significance: specified Computer data, traffic data, stored Computer data, traffic data, content data.
The modern mining industry has huge innovative potential for the introduction and development of digital revolution products. It has always been the most important industry of modelling development, as many operations and processes here are directly empirical and provide a large amount of data for quantitative analysis, which is now well suited to the use of digital intelligent technologies. With the development of digital technologies, effective integrated modeling techniques and the introduction of new process management, knowledge and data analysis tools are needed. Analytical models here are primarily designed to symbolize object properties in dynamics. Intelligent models and solutions based on the use of information technologies and methods of working with big data were becoming most popular, and the processes of integrated monitoring, personalization, risk management, search and generation of solutions, web orientation of programs and technologies and formation of network organizational structures of management were becoming particularly important. Mining enterprises have specific risks: mining and geological risks, risks of loss of market share and investment attractiveness due to biased valuation of useful fossil reserves, risks related to cybersecurity and innovation. Enterprises need to implement new technologies in a comprehensive manner, and information innovation is becoming very important in the face of a lack of financial resources. Expert systems, fuzzy logic, neural networks and genetic algorithms are the most relevant applications in international practice of geoinformation resource management, which largely determines the practical use of artificial intelligence methods and tools in interaction with pound-based management solutions. Modern analytical expertise includes the integration of process management systems, in particular those that are different, which is based on the development of a large number of integration technologies and techniques that apply different data models and are carried out through different procedures. The study examines the development of analytical models based on intelligent technologies, which are now increasingly used in various areas of the mining industry.
The complexity of modern technology and the increase in the number of functions performed by the required equipment in the processing of large amounts of data, puts, especially given the conditions of import substitution, the problem of ensuring the quality and efficiency of engineering works in various directions. In addition, among other industries in the mining industry, the quality of computer technology depends not only on indirect statistical quantitative analysis, but also on the management of safety systems and, hence, people’s lives. The concept of the main directions of the state policy in the sphere of education for 2016-2020, based on the world standards of training of CDIO engineers, creates a favorable environment for the organization of training of competent competitive specialists of a certain engineering profile for the growth of competitiveness of the mining and mining industry of the Russian Federation in the world market, obtaining key economic results and achievements. The improvement of educational methods and tools for training and advanced training of mining engineers in the current period is based on the active implementation of the Standard of global engineering education, which forms a complex environment where trained engineers must be able to “Think-Design-Implement” and “Manage” systems in a team interaction for maximum synergetic effect. On the basis of a number of national universities of the 5-100 program, an open space of engineering education is being created, which involves the formation of an innovative environment and infrastructure based on modern technology (including super-computers), engineering and digital components in the framework of educational and research processes of training in-demand specialists. The implementation of the digital approach and design principles in specialized engineering education is aimed at the formation of key research skills, conducting virtual experiments in cooperation and collaboration with colleagues and experts. Accordingly, the development of new geographic information methods of spatial data analysis in digital project engineering training is an important task in view of the current challenges of the information society and the economy.
The influence of available information on personal development and on the formation of pseudo-complemented discussed in this paper. Free access to information leads to a sense of «know-it-all» and a wealth of skills and knowledge. This phenomenon can be particularly evident in children and adolescents who have not yet learned social norms, have poorly developed critical thinking and don’t know how to select and analyze information.
The spread of digital technologies in the economy changes production processes and used business models. The technologies associated with the fourth industrial revolution, such as the industrial Internet of Things and additive manufacturing, have a significant impact on the production cycle in the manufacturing industry.
Based on short-term and medium-term entrepreneurial opinions and intentions, the work reflects the key aspects of the digitalization process in Russian enterprises, using the method of conjuncture observations and surveys, which supplements the methods of quantitative statistics. On this basis, taking into account the differentiation of the manufacturing industries into low-, medium- and high-tech, a set of trends in the digital technologies development, the industrial participation in digital transformation in the forms of the business processes digitalization and the digitalization of labor, as well as many other important indicators not measured or only partially measured by quantitative statistics is presented. For all the industries, factors hindering digital transformation were identified and ranked.
In general, a survey of managers showed a significant variation in entrepreneurial judgment regarding most aspects of the production digitalization. Despite the fact that the transition to Industry 4.0 is taking place in Russia on the background of rather unfavorable trends in the business climate, the resulting opinions allow us to state that progress is obvious, though the level of immersion into digitalization processes is not yet deep. Consideration of digital activity from the point of industrial separation view, as well as taking into account the classification of industries as low-, medium- and high-tech, allowed us to identify the industrial features of the digital transformation. In particular, it was shown that some technologies, such as the industrial Internet of Things, were predominantly distributed in the medium and high-tech segment, while others, such as 3D printing and RFID tags, were represented in most manufacturing industries.
The main promising areas for continuing research on digital transformation in the Russian manufacturing include expanding the conjuncture observation program by including other industries in it, the development of appropriate composite indicators, an analysis of the relationship between economic indicators and digitalization, a foresight study of the qualitative aspects of digital transformation.