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    Analyzing large building energy performance is difficult. This study introduces scalable visualization designs for better energy data analysis and monitoring, improving insights for energy professionals.

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    Area of Science:

    • Data Visualization
    • Energy Systems Analysis
    • Human-Computer Interaction

    Background:

    • Current energy analysis tools lack scalability and present data at an overly aggregated level, hindering effective monitoring of large building portfolios.
    • Analyzing energy performance across extensive building portfolios presents significant challenges due to data complexity and limitations of existing analytical methods.

    Purpose of the Study:

    • To design and evaluate novel visualization techniques for scalable energy performance analysis in large building portfolios.
    • To address research questions concerning scalability, view coordination, and the suitability of different chart types for complex energy data.

    Main Methods:

    • Conducted a visualization design study involving work domain analysis and data/task abstraction.
    • Developed generalizable visual encoding strategies for time-oriented energy data, focusing on matches and mismatches.
    • Investigated workflow design considerations and methodological aspects of visualization design studies.

    Main Results:

    • Developed scalable visualization designs that overcome limitations of current tools for analyzing large building energy data.
    • Demonstrated the inappropriateness of line charts for derived and aggregated energy data, proposing alternatives.
    • Provided guidelines for visualization design, emphasizing familiarity, trust, and methodological rigor.

    Conclusions:

    • The developed visualization designs offer a scalable solution for analyzing and monitoring energy performance in large building portfolios.
    • These findings inform the creation of more effective energy analysis software, enhancing usability for thousands of energy workers.
    • The study provides a framework for future visualization design research in complex data domains.