Methods and tools for information visualization on the basis of attributed hierarchical graphs with ports

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At present visualization of graph models is an inherent part of the processing of complex information about the structure of objects, systems and processes in many applications in science and technology, and at the market there are widely presented science-intensive software products, using the information visualization on the basis of graph models. Since the information that it is desirable to visualize is constantly growing and becoming more complex, more and more situations arise in which classical graph models cease to be adequate. More powerful graph-theoretic formalisms are required and appear to represent information models with a hierarchical structure, since hierarchy is the basis of numerous methods for visual processing of complex big data in various fields of application. One of these formalisms is the so-called hierarchical graphs. This formalism allows selecting in the given classical graph a set of such its parts (so-called fragments) that all elements of each selected fragment deserve separate joint consideration, and all fragments of the selected set form a nesting hierarchy. At the A. P. Ershov Institute of Informatics Systems constructed the Visual Graph visualization system, which is based on hierarchical graphs and allows exploring complex structured big data through their visual representations. In many applications, objects modeled by graph vertices are complex and contain non-intersecting logical parts (so-called ports) through which these objects are in a relationship modeled by arcs. In the paper the formalism of attributed hierarchical graphs with ports is introduced and new possibilities of the Visual Graph system for visualization of large structured data based on attributed hierarchical graphs with ports are considered.

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Attributed hierarchical graph, data visualization, graph model, port, visualization system

Короткий адрес: https://sciup.org/148326258

IDR: 148326258   |   DOI: 10.31772/2712-8970-2023-24-1-8-17

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