Jupyter-enabled astrophysical analysis using data-proximate computing platforms

The advent of increasingly large and complex datasets has fundamentally altered the way that scientists conduct astronomy research. The need to work closely to the data has motivated the creation of online science platforms, which include a suite of software tools and services, therefore going beyond data storage and data access. We present two example applications of Jupyter as a part of astrophysical science platforms for professional researchers and students. First, the Astro Data Lab is developed and operated by NOIRLab with a mission to serve the astronomy community with now over 1500 registered users. Second, the Dark Energy Spectroscopic Instrument science platform serves its geographically distributed team comprising about 900 collaborators from over 90 institutions. We describe the main uses of Jupyter and the interfaces that needed to be created to embed it within science platform ecosystems. We use these examples to illustrate the broader concept of empowering researchers and providing them with access to not only large datasets but also cutting-edge software, tools, and data services without requiring any local installation, which can be relevant for a wide range of disciplines. Future advances may involve science platform networks, and tools for simultaneously developing Jupyter notebooks to facilitate collaborations.