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Information-analytical semantic model of an expert system for studying the co-evolution of the sociotechnical landscape in digital reality
Author(s) -
М. В. Артеменко,
Vladimir G. Budanov,
Nikolay Korenevskiy
Publication year - 2020
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1658/1/012002
Subject(s) - sociotechnical system , computer science , process (computing) , augmented reality , knowledge base , data science , ontology , the internet , information technology , semantic web , knowledge management , world wide web , artificial intelligence , philosophy , epistemology , operating system
Currently, the development of society is largely determined by the expansion of digital technology into various social practices. Prediction and management of the co-evolution of society in digital reality is determined by the need to ensure sustainable development of society and adequate satisfaction of practices with information technology. The aim of the study was the development and pilot study of the capabilities of the information-analytical semantic model of an expert system for the analysis and management of socio-technical landscapes (STL) in digital reality. The network semantic structure of the knowledge base with unified decision modules in network nodes is substantiated. An enlarged diagram of the model is given and its functioning is described. Examples of the pilot application of the crucial modules of the expert system are examined: social practice “medicine” and digital technologies: “Artificial Intelligence”, “Information Technology”, “Mobile Technologies”, “Internet of Things”, “Big Data”. There are sharp changes in the ratios of feasibility and demand for technologies that occurred in the first half of 2020 compared to 2019 (which is associated with the consequences of the COVIN-19 pandemic). It is shown that the STL reaction is modeled by a transient process characteristic of the vibrational link.

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