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    Nebula is a new natural language grammar for coordinating multiple coordinated views (MCVs). It simplifies creating complex visualizations by formalizing user interactions and data transformations, enhancing usability.

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    Area of Science:

    • Human-Computer Interaction
    • Information Visualization
    • Software Engineering

    Background:

    • Multiple coordinated views (MCVs) enable dynamic visualization updates based on user interactions.
    • Current methods for view coordination are limited by predefined templates or technical complexity.
    • A gap exists between flexible textual specification and user-friendly direct manipulation.

    Purpose of the Study:

    • To introduce Nebula, a novel natural language-based grammar for specifying visualization coordination in MCVs.
    • To develop a framework for understanding and formalizing coordination by demonstration.
    • To bridge the gap between flexible coordination specification and ease of use.

    Main Methods:

    • A systematic review of 176 existing coordinations informed the framework design.
    • Developed a framework describing coordination based on user-performed interactions.
    • Formalized coordination as a composition of interactions and data transformations within Nebula's grammar.

    Main Results:

    • Nebula provides a flexible and expressive grammar for coordinating visualizations.
    • Demonstrated Nebula's capabilities through a diverse gallery of examples.
    • Evaluated Nebula's usability across cognitive dimensions.

    Conclusions:

    • Nebula offers a user-friendly, natural language approach to complex visualization coordination.
    • The framework provides a systematic understanding of coordination by demonstration.
    • Nebula enhances the expressiveness and usability of multiple coordinated views.