Renku: a platform for sustainable data science

Presenter: Rok Roškar (, Head Of Engineering at Swiss Data Science Center

Schedule: Session 4 (Amsterdam / Online hybrid)
Wednesday 15 May
EMEA Friendly time

Sustainability in data-centric research implies efficient sharing and reuse of not only data, but also code, computational environments and workflows. Results are derived from data with code, and to understand and scrutinize them requires that data and code can be brought together in a predictable, repeatable way with minimal effort. At the Swiss Data Science Center we are building Renku, an open source platform focused on enhancing transparency, collaboration, and reproducibility in all types of data-centric research. In Renku, researchers can combine sources of data and code with containerized computational environments in a well-documented way for everything from day-to-day work to dissemination, demonstration, and publication. The use of data can be self-consistently tracked and indexed in a knowledge graph for search, discovery, and audit. In this contribution, we will summarize the design and features of the platform. We will dedicate specific focus to the role that workflow tools, like CWL, play in such an ecosystem and how they can be leveraged to improve FAIR-ness and sustainability of data science projects.

Please leave your questions for the presenter below!

As an alternative to YouTube, this presentations is also available on ConfTube

Useful Renku links: