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Translating Data into Knowledge

A variety of tools are available to ensure the astronomical community is able to download, analyze, and interpret JWST observations for their research. The user-customizable JWST pipeline produces calibrated, science-ready data. All calibration levels of those data are available for download from the Mikulski Archive for Space Telescopes (MAST). STScI, along with members of the astronomical community, have built data-analysis tools to facilitate the translation of data into scientific knowledge.

JWST Pipeline and Data Products

Follow the links below to learn how to install and use the JWST pipeline on your computer and to learn more about the services at MAST for downloading data. JDox  contains detailed documentation on the JWST data files produced by all stages of the pipeline. Also, simulated data that have been processed by the pipeline are available to familiarize yourself with the JWST data formats.

Post-Pipeline Data Analysis Tools

There are a variety of tools available to visualize and analyze fully processed data products from JWST’s diverse set of observing modes. Jdavz is a custom package developed by STScI for interactive visualization of spectroscopic and imaging data. Many other community-based astronomical analysis packages, datasets, and tools are available to support JWST data analysis and proposal planning.

Learning the Ecosystem

To learn how to use the Python data analysis tools, STScI has created virtual classes, example workflow notebooks, and videos to highlight how to use different aspects of the Python data analysis ecosystem.

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For technical assistance, please contact the JWST Help Desk.

 

The NASA James Webb Space Telescope, developed in partnership with ESA and CSA, is operated by AURA’s Space Telescope Science Institute.

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