The article is devoted to the study of interface patterns of digital services and methods of translating the complex system structure of a product into understandable interface solutions. Particular attention is paid to digital systems that work with large volumes of interconnected data and are characterized by high complexity of interaction processes. In such environments, the interface acts not only as a tool for displaying information, but also as a mechanism for supporting the user's cognitive processes during data analysis and decision-making. The purpose of the article is to study modern interface patterns of digital systems and to substantiate methods for translating the system structure of products with high data complexity into effective interface solutions. To achieve this goal, the methods of scientific generalization, system analysis, comparative analysis of scientific approaches in the field of human-computer interaction, as well as the method of structural modeling of user interaction processes with digital systems, were used. The results of the study show that the effectiveness of interfaces of complex digital products largely depends on the ability of interface solutions to reflect the internal logic of the system in the form of understandable interaction scenarios. It was established that in systems with high data density, approaches aimed at reducing the cognitive load of users, structuring information and supporting decision-making in the process of working with the interface play an important role. The paper summarizes existing approaches to translating system logic into interface solutions and proposes the author's Systems-to-Interfaces (S2I) approach, which involves deconstruction of system logic, modeling of user workflows, role-based adaptation of the interface and organization of a decision-making support environment. The practical value of the study lies in the formation of a methodological approach to transforming the system structure of complex digital products into scalable interface patterns.
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Liudmyla Shumilina
University of Economics and Law
Alfred Nobel University
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Liudmyla Shumilina (Wed,) studied this question.
www.synapsesocial.com/papers/69df2c01e4eeef8a2a6b0f71 — DOI: https://doi.org/10.5281/zenodo.19546880
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