In the context of the EU H2020 INDIGO-DataCloud project several use case on large scale scientific data analysis regarding different research communities have been implemented. All of them require the availability of large amount of data related to either output of simulations or observed data from sensors and need scientific (big) data solutions to run data analysis experiments. More specifically, the paper presents the case studies related to the following research communities: (i) the European Multidisciplinary Seafloor and water column Observatory (INGV-EMSO), (ii) the Large Binocular Telescope, (iii) LifeWatch, and (iv) the European Network for Earth System Modelling (ENES).
Big Data Analytics on Large-Scale Scientific Datasets in the INDIGO-DataCloud Project / Fiore, Sandro; Płóciennik, Marcin; De Lucas, Jesús E. Marco; Aloisio, Giovanni; Palazzo, Cosimo; D'Anca, Alessandro; Elia, Donatello; Londero, Elisa; Knapic, Cristina; Monna, Stephen; Marcucci, Nicola M.; Aguilar, Fernando. - (2017), pp. 343-348. ( 14th ACM International Conference on Computing Frontiers, CF 2017 Siena, Italy May 17, 2017) [10.1145/3075564.3078884].
Big Data Analytics on Large-Scale Scientific Datasets in the INDIGO-DataCloud Project
Fiore, Sandro;
2017-01-01
Abstract
In the context of the EU H2020 INDIGO-DataCloud project several use case on large scale scientific data analysis regarding different research communities have been implemented. All of them require the availability of large amount of data related to either output of simulations or observed data from sensors and need scientific (big) data solutions to run data analysis experiments. More specifically, the paper presents the case studies related to the following research communities: (i) the European Multidisciplinary Seafloor and water column Observatory (INGV-EMSO), (ii) the Large Binocular Telescope, (iii) LifeWatch, and (iv) the European Network for Earth System Modelling (ENES).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione
