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Related Concept Videos

Data Collection by Experiments01:13

Data Collection by Experiments

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Data collection is a systematic method of obtaining, observing, measuring, and analyzing accurate information. An experimental study is a standard method of data collection that involves the manipulation of the samples by applying some form of treatment prior to data collection. It refers to manipulating one variable to determine its changes on another variable. The sample subjected to treatment is known as “experimental units.”
An example of the experimental method is a public...
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Interactive and Visualized Online Experimentation System for Engineering Education and Research
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VEEVVIE: Visual Explorer for Empirical Visualization, VR and Interaction Experiments.

C Papadopoulos, I Gutenko, A E Kaufman

    IEEE Transactions on Visualization and Computer Graphics
    |November 4, 2015
    PubMed
    Summary
    This summary is machine-generated.

    VEEVVIE, a novel visual analytics tool, aids human-factors research by integrating experimental data. This system enhances the analysis of complex visualization and interaction experiments, improving scientific discovery.

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    Area of Science:

    • Human-Computer Interaction
    • Scientific Visualization
    • Experimental Design

    Background:

    • Empirical, hypothesis-driven experimentation is crucial in human-factors research.
    • Integrating visual analytics into experimental workflows presents challenges.
    • Existing tools may not adequately support diverse experimental designs and data types.

    Purpose of the Study:

    • To introduce VEEVVIE (Visual Explorer for Empirical Visualization, VR and Interaction Experiments), a system designed to facilitate the integration of visual analytics in empirical research.
    • To provide a query-able data capture and accessible front-end interface for experimental data.
    • To offer a flexible and expandable architecture for custom data types and visualizations.

    Main Methods:

    • Development of a back-end ontology to model various experimental designs.
    • Implementation of a front-end interface with multi-dimensional visualization widgets.
    • Inclusion of filtering and highlighting functionalities within the visualization widgets.
    • Design of a plug-in architecture for custom measurements and data types.

    Main Results:

    • VEEVVIE successfully models diverse experimental designs through its ontology.
    • The system provides accessible, query-able experimental data via its interface.
    • Case studies demonstrate VEEVVIE's utility in analyzing data from high-resolution display wall experiments.

    Conclusions:

    • VEEVVIE enhances the analysis of empirical data in human-factors research.
    • The system's flexible architecture supports custom data and visualizations.
    • VEEVVIE facilitates the integration of visual analytics into experimental workflows, aiding scientific discovery.