EVER-EST: The Platform Allowing Scientists to Cross-Fertilize and Cross-Validate Data. (8th May 2020)

• Record Type: Journal Article
• Authors: Albani, Mirko; Leone, Rosemarie; Foglini, Federica; De Leo, Francesco; Marelli, Fulvio; Maggio, Iolanda
• Is Part Of: Data science journal. Volume 19(2020)
• Publication Date: 2020-05-08
• Subjects: Virtual Research Environment -- Remote Sensing -- Research Object -- Cross-fertilization -- Data Analysis -- Earth Science -- Education; Science -- Data processing -- Periodicals; Database management -- Periodicals; 502.85
• DOI: 10.5334/dsj-2020-021
• Languages: English
• ISSNs: 1683-1470

Abstract

Over recent decades large amounts of data about our Planet have become available. If this information could be easily discoverable, accessible and properly exploited, preserved and shared, it would potentially represent a wealth of information for a whole spectrum of stakeholders: from scientists and researchers to the highest level of decision and policy makers. By creating a Virtual Research Environment (VRE) using a service oriented architecture (SOA) tailored to the needs of Earth Science (ES) communities, the EVER-EST (http://ever-est.eu ) project provides a range of both generic and domain specific data analysis and management services to support a dynamic approach to collaborative research. EVER-EST provides the means to overcome existing barriers to sharing of Earth Science data and information allowing research teams to discover, access, share and process heterogeneous data, algorithms, results and experiences within and across their communities, including those domains beyond Earth Science. The main objective of this paper is to present the EVER-EST platform in all its components describing the most relevant use cases implemented by the Virtual Research Communities (VRCs) involved in the project.