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RIS citation export for TUCPR02: Data Exploration and Analysis with Jupyter Notebooks

AU  - Fangohr, H.
AU  - Beg, M.
AU  - Bergemann, M.
AU  - Bondar, V.
AU  - Brockhauser, S.
AU  - Campbell, A.
AU  - Carinan, C.
AU  - Costa, R.
AU  - Dall'Antonia, F.
AU  - Danilevski, C.
AU  - E, J.C.
AU  - Ehsan, W.
AU  - Esenov, S.G.
AU  - Fabbri, R.
AU  - Fangohr, S.
AU  - Fernandez-del-Castillo, E.
AU  - Flucke, G.
AU  - Fortmann-Grote, C.
AU  - Fulla Marsa, D.
AU  - Giovanetti, G.
AU  - Goeries, D.
AU  - Götz, A.
AU  - Hall, J.
AU  - Hauf, S.
AU  - Hickin, D.G.
AU  - Holm Rod, T.
AU  - Jarosiewicz, T.
AU  - Kamil, E.
AU  - Karnevskiy, M.
AU  - Kieffer, J.
AU  - Kirienko, Y.
AU  - Klimovskaia, A.
AU  - Kluyver, T.A.
AU  - Kuster, M.
AU  - Le Guyader, L.
AU  - Madsen, A.
AU  - Maia, L.G.
AU  - Mamchyk, D.
AU  - Mercadier, L.
AU  - Michelat, T.
AU  - Mohacsi, I.
AU  - Möller, J.
AU  - Parenti, A.
AU  - Pellegrini, E.
AU  - Perrin, J.F.
AU  - Reiser, M.
AU  - Reppin, J.
AU  - Rosca, R.
AU  - Rück, D.B.
AU  - Rüter, T.
AU  - Santos, H.
AU  - Schaffer, R.
AU  - Scherz, A.
AU  - Schlünzen, F.
AU  - Scholz, M.
AU  - Schuh, M.
AU  - Selknaes, J.R.
AU  - Silenzi, A.
AU  - Sipos, G.
AU  - Spirzewski, M.
AU  - Sztuk, J.
AU  - Szuba, J.
AU  - Taylor, J.W.
AU  - Trojanowski, S.
AU  - Wrona, K.
AU  - Yaroslavtsev, A.A.
AU  - Zhu, J.
ED  - White, Karen S.
ED  - Brown, Kevin A.
ED  - Dyer, Philip S.
ED  - Schaa, Volker RW
TI  - Data Exploration and Analysis with Jupyter Notebooks
J2  - Proc. of ICALEPCS2019, New York, NY, USA, 05-11 October 2019
CY  - New York, NY, USA
T2  - International Conference on Accelerator and Large Experimental Physics Control Systems
T3  - 17
LA  - english
AB  - 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.
PB  - JACoW Publishing
CP  - Geneva, Switzerland
SP  - 799
EP  - 806
KW  - data-analysis
KW  - experiment
KW  - software
KW  - detector
DA  - 2020/08
PY  - 2020
SN  - 2226-0358
SN  - 978-3-95450-209-7
DO  - doi:10.18429/JACoW-ICALEPCS2019-TUCPR02
UR  - https://jacow.org/icalepcs2019/papers/tucpr02.pdf
ER  -