PRODIMA

PRODIMA: PRObabilistic Data and information Integration with provenance MAnagement

Coordinatore	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD    more  Organization address address: University Offices, Wellington Square city: OXFORD postcode: OX1 2JD contact info Titolo: Ms. Nome: Gill Cognome: Wells Email: send email Telefono: +44 1865 289800 Fax: +44 1865 289801
Nazionalità Coordinatore	United Kingdom [UK]
Totale costo	200˙371 €
EC contributo	200˙371 €
Programma	FP7-PEOPLE Specific programme "People" implementing the Seventh Framework Programme of the European Community for research, technological development and demonstration activities (2007 to 2013)
Code Call	FP7-PEOPLE-2011-IEF
Funding Scheme	MC-IEF
Anno di inizio	2013
Periodo (anno-mese-giorno)	2013-03-01   -   2015-02-28

 Partecipanti

#	participant	country	role	EC contrib. [€]
1	THE CHANCELLOR, MASTERS AND SCHOLARS OF THE UNIVERSITY OF OXFORD  Organization address address: University Offices, Wellington Square city: OXFORD postcode: OX1 2JD contact info Titolo: Ms. Nome: Gill Cognome: Wells Email: send email Telefono: +44 1865 289800 Fax: +44 1865 289801	UK (OXFORD)	coordinator	200˙371.80

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 Obiettivo del progetto (Objective)

'The PRODIMA project investigates provenance-based probabilistic information integration in the semantic web. During the project, a notion of uncertain provenance will be defined for probabilistic information integration frameworks suitable in the semantic web context. Properties of this notion of uncertain provenance will be formally and logically investigated. Furthermore, scalable reasoning algorithms will be developed for collecting, storing and querying provenance information in order to facilitate the computation of probabilities but als in order to enable provenance-based mapping debugging. By this means reasoning, mapping debugging and provenance management shall be combined through scalable algorithms. The properties algorithms will be investigated formally and logically. At the end of the project, a small demo system will be implemented showing the benefits of provenance-based probabilistic information integration in the semantic web context.'