data exploration and analysis with jupyter notebooks

• DOI: 10.18429/jacow-icalepcs2019-tucpr02
• Publication Date: 2019-10-05
• Authors: Fangohr, Hans; Beg, Marijan; Bergemann, Martin; Bondar, Valerii; Brockhauser, Sandor; Campbell, Aidan; Carinan, Cammille; Costa, Raul; Dall'Antonia, Fabio; Danilevski, Cyril; E, Juncheng; Ehsan, Wajid; Esenov, Sergey; Fabbri, Riccardo; Fangohr, Susanne; Fernandez-Del-Cas...; Flucke, Gero; Fortmann-Grote, C...; Fulla Marsa, Daniel; Giovanetti, Gabriele; Goeries, Dennis; Götz, Andrew; Hall, Jamie; Hauf, Steffen; Hickin, David; Holm Rod, Thomas; Jarosiewicz, Tobiasz; Kamil, Ebad; Karnevskiy, Mikhail; Kieffer, Jerome; Kirienko, Yury; Klimovskaia, Anna; Kluyver, Thomas; Kuster, Markus; Le Guyader, Loïc; Madsen, Anders; Maia, Luis; Mamchyk, Denys; Mercadier, Laurent; Michelat, Thomas; Möller, Johannes; Mohacsi, Istvan; Parenti, Andrea; Pellegrini, Eric; Perrin, Jean-Fran...; Reiser, Mario; Reppin, Johannes; Rosca, Robert; Rück, Denivy; Rüter, Tonn; Santos, Hugo; Schaffer, Robert; Scherz, Andreas; Schlünzen, Frank; Scholz, Markus; Schuh, Michael; Selknaes, Jesper ...; Silenzi, Alessandro; Sipos, Gergely; Spirzewski, Michal; Sztuk, Jolanta; Szuba, Janusz; Taylor, Jonathan; Trojanowski, Seba...; Wrona, Krzysztof; Yaroslavtsev, Ale...; Zhu, Jun
• Keywords: FEL; 0301 basic medicine; 03 medical and health sciences; experiment; detector; software; [PHYS.PHYS.PHYS-ACC-PH]Physics [physics]/Physics [physics]/Accelerator Physics [physics.acc-ph]; [PHYS.PHYS.PHYS-ACC-PH] Physics [physics]/Physics [physics]/Accelerator Physics [physics.acc-ph]; User Interfaces, User Perspective, and User Experience(UX); data-analysis; Accelerator Physics

Proceedings of the 17th International Conference on Accelerator and Large Experimental Physics Control Systems, ICALEPCS2019, New York, NY, USA<br/>Jupyter notebooks are executable documents that are displayed in a web browser. The notebook elements consist of human-authored contextual elements and computer code, and computer-generated output from executing the computer code. Such outputs can include tables and plots. The notebook elements can be executed interactively, and the whole notebook can be saved, re-loaded and re-executed, or converted to read-only formats such as HTML, LaTeX and PDF. Exploiting these characteristics, Jupyter notebooks can be used to improve the effectiveness of computational and data exploration, documentation, communication, reproducibility and re-usability of scientific research results. They also serve as building blocks of remote data access and analysis as is required for facilities hosting large data sets and initiatives such as the European Open Science Cloud (EOSC). In this contribution we report from our experience of using Jupyter notebooks for data analysis at research facilities, and outline opportunities and future plans.<br/>