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Navigating the Mass Spectrometry-Based Proteomic Data Using Free Computational Tools
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Expanding Access to Science Participation: A FAIR Framework for Petascale Data Visualization and Analytics.

Aashish Panta, Alper Sahistan, Xuan Huang

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    Scientists can now easily access and analyze massive climate datasets using a new data fabric. This democratizes petascale data, enabling dynamic trend identification and fostering scientific discovery for everyone.

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    Area of Science:

    • Data Science
    • Climate Science
    • Scientific Computing

    Background:

    • Massive scientific data generation presents accessibility challenges.
    • Petascale datasets are often difficult for researchers to access and analyze.
    • Democratizing access to large scientific datasets is crucial for innovation.

    Purpose of the Study:

    • To introduce a novel data fabric abstraction layer for democratizing access to petascale scientific data.
    • To enable user-friendly querying and analysis of complex datasets, hiding underlying infrastructure.
    • To facilitate FAIR (Findable, Accessible, Interoperable, Reusable) data access for the scientific community.

    Main Methods:

    • Developed a data fabric abstraction layer to simplify data access and querying.
    • Utilized progressive compression algorithms and machine learning for scalable data visualization.
    • Created interactive, browser-based dashboards for managing, visualizing, and analyzing petabytes of data.
    • Enabled data analysis on diverse hardware, from supercomputers to laptops.

    Main Results:

    • Achieved user-friendly, FAIR access to NASA's petascale climate datasets.
    • Enabled dynamic identification of extreme events and trends in large datasets.
    • Improved climate scientists' ability to visually explore data through interactive dashboards.
    • Successfully deployed dashboards and training in an academic setting and for the general public.

    Conclusions:

    • The novel data fabric effectively removes barriers to accessing and utilizing petascale scientific data.
    • The approach democratizes scientific data, enabling broader discovery and educational applications.
    • Interactive dashboards enhance data exploration capabilities for climate scientists and the public.