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    Incremental visualization methods allow users to interact with and modify visualizations during the process. This paper introduces a model for incremental visualizations, enhancing data state models for dynamic updates and flexible compromises between quality and responsiveness.

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    Area of Science:

    • Computer Science
    • Information Visualization

    Background:

    • Traditional visualization scenarios assume stable data and display setups.
    • Modern technical possibilities introduce dynamic data and display configurations.
    • Incremental visualization allows user interaction and steering at intermediate stages.

    Purpose of the Study:

    • To propose a novel model for incremental visualizations.
    • To extend the Data State Reference Model for dynamic visualization scenarios.
    • To facilitate intermediate visualization updates through partitioned data and operators.

    Main Methods:

    • Extension of the Data State Reference Model.
    • Incorporation of partitioned data representations.
    • Integration of visualization operators for intermediate updates.

    Main Results:

    • The proposed model enables tailored compromises between output quality, data quantity, and responsiveness (frame rates).
    • Partitioned data and operators can be used independently or in combination.
    • Demonstrates new expressive power for incremental visualization.

    Conclusions:

    • The model effectively addresses challenges in dynamic visualization scenarios.
    • Facilitates flexible and interactive visualization updates.
    • Applicable in real-world scenarios requiring adaptable visualization.