VIDA

Transforming Raw Data into Information through Virtualization

Coordinatore	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	Switzerland [CH]
Totale costo	1˙976˙762 €
EC contributo	1˙976˙762 €
Programma	FP7-IDEAS-ERC Specific programme: "Ideas" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	ERC-2013-CoG
Funding Scheme	ERC-CG
Anno di inizio	2014
Periodo (anno-mese-giorno)	2014-05-01   -   2019-04-30

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE  Organization address address: BATIMENT CE 3316 STATION 1 city: LAUSANNE postcode: 1015 contact info Titolo: Dr. Nome: Caroline Cognome: Vandevyver Email: send email Telefono: +41 21 693 35 73 Fax: +41 21 693 55 83	CH (LAUSANNE)	hostInstitution	1˙976˙762.40
2	ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE  Organization address address: BATIMENT CE 3316 STATION 1 city: LAUSANNE postcode: 1015 contact info Titolo: Prof. Nome: Anastasia Cognome: Ailamaki Email: send email Telefono: +41 216937564 Fax: +41 216936700	CH (LAUSANNE)	hostInstitution	1˙976˙762.40

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 Obiettivo del progetto (Objective)

'The unprecedented evolution of computing power, combined with the decreasing costs of computation and storage infrastructure, has revolutionized all scientific fields and enterprises; at the heart of this revolution is the ability to collect unprecedented amounts of data. Real progress, however, depends on how efficiently we can ‘extract value from chaos’, i.e., process the collected data and transform it into useful information. Unfortunately, despite the impressive growth of data management technologies, data analysis application efficiency is hindered by the increasing data growth. The typical business intelligence architecture is far too complex to yield answers productively, with businesses operating large numbers of specialized data processing systems, with data being repeatedly moved, copied or transformed between them. The reason is that, despite tremendous progress, data management tools are based on legacy designs whose requirements are no longer adequate. A novel approach is needed urgently, or users risk losing the ability to leverage their hard-earned data. In this proposal, we identify assumptions that do not scale with today’s massive data explosion, and design a comprehensive end-to-end solution that implements a novel form of data virtualization to vastly simplify data analysis. Our approach removes barriers to data handling and maximizes efficiency for science, businesses, and their users, by enabling new forms of data computation that are unrestrained by how data is collected or stored. This project constructs the building blocks for data-driven computing and the fourth paradigm of scientific discovery, thereby advancing our ability to automatically explore massive and complex datasets at sight, and dictate the new developments in sciences and the industry.'