Oral Abstract

Oral Contribution (O9.2) Steven Crawford (STScI)

Theme: Data processing pipelines

Science Platforms for the reduction and analysis of data for the James Webb Space Telescope

What does the future hold for how we reduce, analyze, and interact with observations? How will we enable investigators to quickly extract the scientific results from complex observations? In this talk, we present the browser-based science platform currently being developed using Jupyterhub to provide access to observations from the James Webb Space Telescope along with the data reduction and analysis tools necessary to carry out scientific investigations. This cloud-based implementation allows for the management and scaling of resources while providing an environment for the user with common astronomy tools installed. Direct access to the data for authorized users is provided to the Mikulski Archive for Space Telescopes. A suite of tutorials in the form of Jupyter notebooks demonstrate how data can be reduced and analyzed. The technology to enable this--including the data processing software, analysis tools, data access APIs, and infrastructure-- are all provided as open-source repositories that can be adapted to meet the needs of other missions and observatories. The science platform enables a wide range of functionality: applying user-specific steps to the calibration software, testing new software, quickly providing access to the tools to a large number of users, and a platform for education. We highlight how this flexible platform can be quickly adapted to help other missions supported by STScI to achieve their scientific goals as well.