Diogo Castro Federated collaborative workflows for Jupyter | JupyterCon 2023

Cloud Storage for Synchronization and Sharing (CS3) platforms, like ownCloud or Nextcloud, have been widely deployed in the research and educational space, mostly by e-infrastructure providers, NRENs (National Research & Education Networks) and major research institutions. These services, used usually in daily workflows by hundreds of thousands of users (including researchers, students, scientists and engineers) remain largely disconnected, and are developed and deployed in isolation from each other. The same can be said about Jupyter deployments, the de-facto standard for data analysis in the scientific and research communities: each institution has its own configuration, deployment strategy and, more importantly, their customized way of giving users access to their (siloed) data and code. The EU-fundend project CS3MESH4EOSC was started to address these major technical, but also societal challenges. Science Mesh, its main asset, was idealized to provide an interoperable platform that easily integrates and extends sync & share services, applications (like Jupyter) and software components within the full CS3 community. Such federated service mesh provides a frictionless collaboration platform for hundreds of thousands of users, offering easy access to data across institutional and geographical boundaries. This presentation will focus on the development of the cs3api4lab, a plugin created by the project to connect Jupyter to the Science Mesh. It brings features like easy to configure access to CS3 services’ backends, sharing and parallel access to notebooks right from within the Jupyterlab interface. We will also discuss its applicability outside of the Mesh and, finally, on the project vision for collaborative scientific analysis.