MODAS

Mob Data Sourcing

Coordinatore	TEL AVIV UNIVERSITY    more Spiacenti, non ci sono informazioni su questo coordinatore. Contattare Fabio per maggiori infomrazioni, grazie.
Nazionalità Coordinatore	Israel [IL]
Totale costo	1˙706˙400 €
EC contributo	1˙706˙400 €
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-2011-ADG_20110209
Funding Scheme	ERC-AG
Anno di inizio	2012
Periodo (anno-mese-giorno)	2012-04-01   -   2017-03-31

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	TEL AVIV UNIVERSITY  Organization address address: RAMAT AVIV city: TEL AVIV postcode: 69978 contact info Titolo: Ms. Nome: Lea Cognome: Pais Email: send email Telefono: 97236408774 Fax: 97236409697	IL (TEL AVIV)	hostInstitution	1˙706˙400.00
2	TEL AVIV UNIVERSITY  Organization address address: RAMAT AVIV city: TEL AVIV postcode: 69978 contact info Titolo: Prof. Nome: Tova Cognome: Milo Email: send email Telefono: 97236406075	IL (TEL AVIV)	hostInstitution	1˙706˙400.00

Mappa

 Word cloud

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 Obiettivo del progetto (Objective)

'Crowd-based data sourcing is a new and powerful data procurement paradigm that engages Web users to collectively contribute data, analyze information and share opinions. This brings to light, out of the huge, inconsistent Web ocean, an important body of knowledge that would otherwise not be attainable. Crowd-based data sourcing democratizes data-collection, cutting companies and researchers reliance on stagnant, overused datasets, and has great potential for revolutionizing our information world. Yet, triumph has so far been limited to only a handful of successful projects such as Wikipedia or IMDb. This comes notably from the difficulty of managing huge volumes of data and users of questionable quality and reliability. Every single initiative had to battle, almost from scratch, the same non-trivial challenges. The ad hoc solutions, even when successful, are application specific and rarely sharable.

In this project we propose to develop solid scientific foundations for Web-scale data sourcing. We believe that such a principled approach is essential to obtain knowledge of superior quality, to realize the task more effectively and automatically, be able to reuse solutions, and thereby to accelerate the pace of the absorption of this new technology that is revolutionizing our life. Our goal is very ambitious. We will develop the logical, algorithmic, and methodological foundations for the management of large scale crowd-sourced data and for the development of applications over such information. This encompasses a formal model capturing all the diverse facets of crowd-sourced data. This also means developing the necessary reasoning capabilities for managing data sourcing, cleaning, verification, integration, sharing, querying and updating, in a dynamic Web environment. This technological breakthrough will open the way for developing new and otherwise unattainable universe of knowledge in a wide range of applications, from scientific to social and economical ones.'