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Data Tectonics: A Framework for Building Physical and Immersive Data Representations.

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    This paper introduces data tectonics, a framework for understanding how context, data, representation, materiality, fabrication, and interactions create meaningful data experiences.

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    Area of Science:

    • Data Science
    • Human-Computer Interaction
    • Information Visualization

    Background:

    • Current approaches to data experience design lack a unifying theoretical framework.
    • Understanding the interplay between abstract data and its physical manifestation is crucial.

    Purpose of the Study:

    • To introduce and define the concept of data tectonics.
    • To propose a unifying principle for structuring data experiences.
    • To identify key elements influencing data meaning.

    Main Methods:

    • Conceptual framework development.
    • Literature review on data representation and interaction.
    • Synthesis of relationships between six core elements.

    Main Results:

    • Data tectonics provides a structured approach to analyzing data experiences.
    • Identified six key elements: context, data, representation, materiality, fabrication method, and interactions.
    • Demonstrated how these elements collectively shape meaningful data experiences.

    Conclusions:

    • Data tectonics offers a novel lens for designing and understanding data-driven interactions.
    • This framework facilitates the creation of more impactful and intuitive data experiences.
    • Further research can explore the application of data tectonics across diverse domains.