An Enhanced Visualization Process Model for Incremental Visualization

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.