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The overwhelming majority of modern information systems are built on the basis of a modular principle. This principle involves the creation of independent software subsystems that perform separate groups of tasks. The success of building an information system depends on the quality of the division of tasks into groups. Known approaches to modular partitioning are based on the organizational structure of the enterprise and job descriptions of employees. This leads to unmanaged intermodular connections and loss of the advantages of the modular approach (flexibility, interchangeability of modules, etc.). To solve this problem, the article proposes a new method for designing a modular structure of information systems based on the analysis of information and information flows. This allows minimizing inter-module communications and building systems that are independent of the organizational structure of the enterprise.

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The COVID-19 pandemic has caused the deaths of millions of people around the world. The scientific community faces a tough struggle to reduce the effects of this pandemic. Several investigations dealing with different perspectives have been carried out. However, it is not easy to find studies focused on COVID-19 contagion chains. A deep analysis of contagion chains may contribute new findings that can be used to reduce the effects of COVID-19. For example, some interesting chains with specific behaviors could be identified and more in-depth analyses could be performed to investigate the reasons for such behaviors. To represent, validate and analyze the information of contagion chains, we adopted an ontological approach. Ontologies are artificial intelligence techniques that have become widely accepted solutions for the representation of knowledge and corresponding analyses. The semantic representation of information by means of ontologies enables the consistency of the information to be checked, as well as automatic reasoning to infer new knowledge. The ontology was implemented in Ontology Web Language (OWL), which is a formal language based on description logics. This approach could have a special impact on smart cities, which are characterized as using information to enhance the quality of basic services for citizens. In particular, health services could take advantage of this approach to reduce the effects of COVID-19.