EPJ Web Conf.
Volume 214, 201923rd International Conference on Computing in High Energy and Nuclear Physics (CHEP 2018)
|Number of page(s)||7|
|Section||T7 - Clouds, virtualisation & containers|
|Published online||17 September 2019|
Facilitating Collaborative Analysis in SWAN
CERN. 1 Esplanade des Particules,
* e-mail: email@example.com
Published online: 17 September 2019
SWAN (Service for Web-based ANalysis) is a CERN service that allows users to perform interactive data analysis in the cloud, in a “software as a service” model. It is built upon the widely-used Jupyter notebooks, allowing users to write - and run - their data analysis using only a web browser. By connecting to SWAN, users have immediate access to storage, software and computing resources that CERN provides and that they need to do their analyses.
Besides providing an easier way of producing scientific code and results, SWAN is also a great tool to create shareable content. From results that need to be reproducible, to tutorials and demonstrations for outreach and teaching, Jupyter notebooks are the ideal way of distributing this content. In one single file, users can include their code, the results of the calculations and all the relevant textual information. By sharing them, it allows others to visualize, modify, personalize or even re-run all the code.
In that sense, this paper describes the efforts made to facilitate sharing in SWAN. Given the importance of collaboration in our scientific community, we have brought the sharing functionality from CERNBox, CERN’s cloud storage service, directly inside SWAN. SWAN users have available a new and redesigned interface where theycan share “Projects”: a special kind of folder containing notebooks and other files, e.g., like input datasets and images. When a user shares a Project with some other users, the latter can immediately see andwork with the contents of that project from SWAN.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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