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Data Science interoperability environments in ScienceMesh






Technology Used




JupyterLab extensions


Node JS


REVA (cloud interoperability platform)

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About the project

Providing expertise in microservices architecture, integration, agile software development process and Data Science, the Software Mind team led tasks on the Reference cloud interoperability platform and Data Science environments.   

ScienceMesh, developed in an EU founded project, coordinated by CERN, creates the Federated Scientific Mesh that enables the federated sharing of data across different sync-and-share services, federated use of applications (such as collaborative document editing, data archiving, data publishing, fast transfer of large datasets and remote data analysis (distributed Data Science environments).   

As a result, Software Mind delivered a JupyterLab extension (cs3api4lab) integrating JupyterLab with ScienceMesh, thanks to which file browsing, additional share and collaboration functionalities for notebooks and resources across the federated cloud are now possible in the JupyterLab environment. JupyterLab is considered a complete, fully-fledged IDE for Data Science tasks and interactive computing, where data scientists can do all their work in one tool, so the point is that functionalities for sharing (full CS3APIs client) and concurrent editing are available inside this environment.

Furthermore, Data Science environments were integrated with a comprehensive suite of Data Services in ScienceMesh, to support complete research and Data Science workflows using existing collaboration tools. The collaborative JupyterLab extension became a part of CERN’s specialized Jupyter Notebook service – SWAN. 

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