PRODIMA

PRODIMA: PRObabilistic Data and information Integration with provenance MAnagement

 Coordinatore 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

 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

Mappa


 Word cloud

Esplora la "nuvola delle parole (Word Cloud) per avere un'idea di massima del progetto.

context    mapping    uncertain    semantic    reasoning    provenance    scalable    logically    web    formally    probabilistic    debugging    notion    integration    algorithms   

 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.'

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