The Pangeo Big Data Ecosystem and its use at CNES

Type Proceedings paper
Date 2019
Language English
Other localization http://publications.jrc.ec.europa.eu/repository/handle/JRC115761
Author(s) Eynard-Bontemps Guillaume1, Abernathey Ryan2, Hamman Joseph3, Ponte AurelienORCID4, Rath Willi5
Affiliation(s) 1 : Centre National d’Etudes Spatiales (CNES), Toulouse, France
2 : Columbia University / Lamont Doherty Earth Observatory, New-York, USA
3 : National Center for Atmospheric Research (NCAR), Boulder, USA
4 : Ifremer, Univ. Brest, CNRS, IRD, Laboratoire dOcanographie Physique et Spatiale (LOPS), IUEM, Brest 29280, France
5 : GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
Meeting Big Data from Space (BiDS'19) .... Turning Data into insights... 19-21 fébruary 2019, Munich, Germany
Source P. Soille, S. Loekken, and S. Albani (Eds.) Proc. of the 2019 conference on Big Data from Space (BiDS’2019), EUR 29660 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-00034-1 , doi:10.2760/848593, 2019. Part. Interactive Processing and Visualisation, pp.49-52
Note EUR 29660 EN OP KJ-NA-29660-EN-N (online) ISSN: 1831-9424
Keyword(s) Pangeo, Dask, Jupyter, HPC, Cloud, Big Data, Analysis, Open Source
Abstract

Pangeo[1] is a community-driven effort for open-source big data initially focused on the Earth System Sciences. One of its primary goals is to enable scientists in analyzing petascale datasets both on classical high-performance computing (HPC) and on public cloud infrastructure. In only a few years, Pangeo has grown into a very productive community collaborating on the development of open-source analysis tools for science. It provides a set of example deployments based on open-source Scientific Python packages like Jupyter[2], Dask[3], and Xarray[4] that bring together scientists and developer with their actual use-cases. In this paper, we first describe Pangeo ecosystem and community. We then present its impact on the work of scientists from CNES on the HPC deployment there. We conclude with a future outlook for Pangeo in this agency and beyond.

Full Text
File Pages Size Access
Publisher's official version 6 446 KB Open access
Top of the page

How to cite 

Eynard-Bontemps Guillaume, Abernathey Ryan, Hamman Joseph, Ponte Aurelien, Rath Willi (2019). The Pangeo Big Data Ecosystem and its use at CNES. P. Soille, S. Loekken, and S. Albani (Eds.) Proc. of the 2019 conference on Big Data from Space (BiDS’2019), EUR 29660 EN, Publications Office of the European Union, Luxembourg, 2019, ISBN 978-92-76-00034-1 , doi:10.2760/848593, 2019. Part. Interactive Processing and Visualisation, pp.49-52. https://archimer.ifremer.fr/doc/00503/61441/