Big Data challenges in building the Global Earth Observation System of Systems. (June 2015)

• Record Type: Journal Article
• Authors: Nativi, Stefano; Mazzetti, Paolo; Santoro, Mattia; Papeschi, Fabrizio; Craglia, Max; Ochiai, Osamu
• Is Part Of: Environmental modelling & software. Volume 68(2015:Jun.)
• Page Start: 1
• Page End: 26
• Publication Date: 2015-06
• Subjects: GEOSS -- Big Data -- Multidisciplinary systems -- Earth System Science -- Research infrastructures -- Interoperability -- Cloud systems; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2015.01.017
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: There are many expectations and concerns about Big Data in the sector of Earth Observation. It is necessary to understand whether Big Data is a radical shift or an incremental change for the existing digital infrastructures. This manuscript explores the impact of Big Data dimensionalities (commonly known as 'V' axes: volume, variety, velocity, veracity, visualization) on the Global Earth Observation System of Systems (GEOSS) and particularly its common digital infrastructure (i.e. the GEOSS Common Infrastructure). GEOSS is a global and flexible network of content providers allowing decision makers to access an extraordinary range of data and information. GEOSS is a pioneering framework for global and multidisciplinary data sharing in the EO realm. The manuscript introduces and discusses the general GEOSS strategies to address Big Data challenges, focusing on the cloud-based discovery and access solutions. A final section reports the results of the scalability and flexibility performance tests. Graphical abstract: Highlights: Big Data challenges for the Global Earth Observation System of Systems (GEOSS). GEOSS Common Infrastructure (GCI) solutions to address Big Data challenges. The role played by the GEO Brokering framework (GEO DAB). GEO DAB cloud configuration. Performance Tests.