Abstract
The paper analyzes the methods to formalize the components of cognitive graphics. It scrutinizes the approach to formalizing visual models of complex systems on the basis of the visual cognitive meta-language VI-XML. Using knowledge paradigms, the metaphors of cognitive visualization represent the object under study from different perspectives and levels of specification (expertise). The metaphors of visualization form the mechanisms for processing and transferring knowledge by comparing abstract or concrete objects with visual images. The given knowledge-based approach to formalizing visual models underlies the universal visual modeling environment that provides a single interface to create and modify visual conceptual, structural-functional and object-based models. Such an approach allows encapsulating the levels of visual modeling in a single closed hierarchy that corresponds to the stages of a system project and resolves its three main problems: cognition, convergence, and encapsulation. The heterogeneity of the methods applied for each of the design levels determines the cognitive problem (the difficulty of identifying the concepts when moving from one control level to another). Currently, the boundaries between certain levels are erased, and there emerges the problem of convergence that is due to the difficulty of the interpenetration of technologies (conceptual, structural-functional, logical and physical levels of the model). Another problem is the problem of encapsulation that is ascribed to the fragmentation of classical visual languages and the isolation of existing tools. The method developed in the paper applies the meta-language VI-XML (Visual Intelligence XML). The method describes the rules, concepts and notions, is focused on the presentation of the components of visual models at different hierarchical levels and based on the unified graph structure. The method aims to deal with the problems of system design in the context of synchronous design procedures.
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Some results were obtained with the financial support of the Ministry of science and higher education for the project “Fundamental research of methods of digital transformation of the component base of micro-and nanosystems”.
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Vlasov, A.I., Juravleva, L.V., Shakhnov, V.A. (2021). Knowledge-Based Model for Formal Representation of Complex System Visual Models. In: Arai, K., Kapoor, S., Bhatia, R. (eds) Intelligent Systems and Applications. IntelliSys 2020. Advances in Intelligent Systems and Computing, vol 1251. Springer, Cham. https://doi.org/10.1007/978-3-030-55187-2_45
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