From copernicus big data to extreme earth analytics

Manolis Koubarakis*, Konstantina Bereta, Dimitris Bilidas, Konstantinos Giannousis, Theofilos Ioannidis, Despina-Athanasia Pantazi, George Stamoulis, Seif Haridi, Vladimir Vlassov, Lorenzo Bruzzone, Claudia Paris, Torbjørn Eltoft, Thomas Krämer, Angelos Charalabidis, Vangelis Karkaletsis, Stasinos Konstantopoulos, Jim Dowling, Theofilis Kakantousis, Mihai Datcu, Corneliu Octavian DumitruFlorian Appel, Heike Bach, Silke Migdall, Nick Hughes, David Arthurs, Andres Fleming

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)
1 Downloads (Pure)

Abstract

Copernicus is the European programme for monitoring the Earth. It consists of a set of systems that collect data from satellites and in-situ sensors, process this data and provide users with reliable and up-to-date information on a range of environmental and security issues. The data and information processed and disseminated puts Copernicus at the forefront of the big data paradigm, giving rise to all relevant challenges, the so-called 5 Vs: volume, velocity, variety, veracity and value. In this short paper, we discuss the challenges of extracting information and knowledge from huge archives of Copernicus data. We propose to achieve this by scale-out distributed deep learning techniques that run on very big clusters offering virtual machines and GPUs. We also discuss the challenges of achieving scalability in the management of the extreme volumes of information and knowledge extracted from Copernicus data. The envisioned scientific and
technical work will be carried out in the context of the H2020 project ExtremeEarth which starts in January 2019.
Original languageEnglish
Title of host publicationEDBT/ICDT 2019 Joint Conference
Pages690-693
Number of pages4
DOIs
Publication statusPublished - Mar 2019
Externally publishedYes
Event22nd International Conference on Extending Database Technology, EDBT 2019 - IST Congress Center, Campus Alameda, Lisbon, Portugal
Duration: 26 Mar 201929 Mar 2019
Conference number: 22
http://edbticdt2019.inesc-id.pt/

Publication series

Name
ISSN (Print)2367-2005

Conference

Conference22nd International Conference on Extending Database Technology, EDBT 2019
Abbreviated titleECBT 2019
Country/TerritoryPortugal
CityLisbon
Period26/03/1929/03/19
Internet address

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