The ENES Climate Analytics Service (ECAS) will enable scientific end-users to perform data analysis
experiments on large volumes of climate data, by exploiting a PID-enabled, server-side, and parallel approach.
It aims at providing a paradigm shift for the ENES community with a strong focus on data intensive analysis,
provenance management, and server-side approaches as opposed to the current ones mostly client-based,
sequential and with limited/missing end-to-end analytics workflow/provenance capabilities.
If you already own an account and joined the project, go here to access the JupyterHub instance.
