Speaker
Description
The James Webb Space Telescope is producing a firehose of extragalactic imaging data through its diversity of legacy programs. Community organized initiatives, such as the Dawn JWST Archive, have come to fill the gap between archive products to uniformly-reduced data that enable large-scale exploration and analysis. These programs are catalyzing further initiatives to generate value-added catalogs of inferred parameters, such as those from SED fitting, morphology extraction, and machine learning algorithms. Using and comparing these catalogues will become increasingly challenging as more data is made available and new parameters are created.
Through the J-HIVE initiative, we have created a platform to generate purpose-specific catalogs that combine the community generated data products in a versionable and traceable manner. The platform also generates schema to enable access to all of this data in a discoverable and documented manner. The Python/JSON based system can be easily modified to add in new catalogues or datasets as they are available. It also performs simple transformations and filters on the data, which can be added to as needed. The output catalogue can then be easily pushed to visualization mechanisms for exploration and analysis. In this talk, we will present how the platform was developed and the benefits it provides to researchers using JWST data now and in the future.
| Attendance | in-person |
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