Difference between revisions of "Competence centre EISCAT 3D"
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[[Category:EGI-Engage]] | [[Category:EGI-Engage]] | ||
'''CC Coordinator:''' Ingemar Häggström | |||
'''CC contact:''' cc-eiscat3d AT mailman.egi.eu | |||
The design of the next generation incoherent scatter radar system, EISCAT_3D introduces significant challenges in handling large-scale experimental data which will be massively generated at great speeds and volumes. The CC will build an e-Infrastructure to meet the requirements of the EISCAT_3D data system, will support the EISCAT science community in their acquisition, curation, access to and processing of the data, and will train data scientists who can explore new approaches to solve problems via new data-centric way of conceptualising, organising and carrying out research activities. <br> | The design of the next generation incoherent scatter radar system, EISCAT_3D introduces significant challenges in handling large-scale experimental data which will be massively generated at great speeds and volumes. The CC will build an e-Infrastructure to meet the requirements of the EISCAT_3D data system, will support the EISCAT science community in their acquisition, curation, access to and processing of the data, and will train data scientists who can explore new approaches to solve problems via new data-centric way of conceptualising, organising and carrying out research activities. <br> |
Revision as of 20:04, 19 February 2015
EGI-Engage Competence centres: | Main page | ELIXIR | BBMRI | MoBrain | DARIAH | LifeWatch | EISCAT_3D | EPOS | Disaster Mitigation | | EGI-Engage Knowledge Commons |
CC Coordinator: Ingemar Häggström
CC contact: cc-eiscat3d AT mailman.egi.eu
The design of the next generation incoherent scatter radar system, EISCAT_3D introduces significant challenges in handling large-scale experimental data which will be massively generated at great speeds and volumes. The CC will build an e-Infrastructure to meet the requirements of the EISCAT_3D data system, will support the EISCAT science community in their acquisition, curation, access to and processing of the data, and will train data scientists who can explore new approaches to solve problems via new data-centric way of conceptualising, organising and carrying out research activities.