K-DRIVE
Knowledge Driven Data Exploitation
| Coordinatore | THE UNIVERSITY COURT OF THE UNIVERSITY OF ABERDEEN
Organization address
address: KING'S COLLEGE REGENT WALK contact info |
| Nazionalità Coordinatore | United Kingdom [UK] |
| Totale costo | 1˙696˙064 € |
| EC contributo | 1˙696˙064 € |
| 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-IAPP |
| Funding Scheme | MC-IAPP |
| Anno di inizio | 2012 |
| Periodo (anno-mese-giorno) | 2012-01-01 - 2015-12-31 |
Partecipanti
| # | ||||
|---|---|---|---|---|
| 1 |
THE UNIVERSITY COURT OF THE UNIVERSITY OF ABERDEEN
Organization address
address: KING'S COLLEGE REGENT WALK contact info |
UK (ABERDEEN) | coordinator | 798˙032.00 |
| 2 |
IBM ITALIA SPA*
Organization address
address: Circonvallazione Idroscalo SNC contact info |
IT (Segrate (MI)) | participant | 464˙266.00 |
| 3 |
INTELLIGENT SOFTWARE COMPONENTS S.A.
Organization address
address: AVENIDA TORRE BLANCA 57 3C15 contact info |
ES (SANT CUGAT DEL VALLES) | participant | 433˙766.00 |
Mappa
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Obiettivo del progetto (Objective)
'The development of innovative technology for the discovery new insights (such as trends) of digital data and real time guidance of using digital data is one of the priorities in the areas of semantic technologies. The first objective of this project is the identification of novel query generation techniques to facilitate experts to identify key dimensions within semantic data and to recommend users with queries related to their interests, with an emphasis on the development of innovative techniques for efficient and scalable query generation and query answering.
We first evaluate the query generation approaches with two use cases on electronic tender data and healthcare data. The most promising and effective approaches will be further investigated with the view of dealing with update of the data and relevant knowledge. For example, the EU Tenders Electronic Daily (TED, http://ted.europa.eu) data is updated daily; bio-medical data regarding patients is constantly generated. The main goals of the projects are (1) the development of efficient and scalable query generation techniques with potential for dealing with streaming data and knowledge, (2) detailed studies of their use for exploiting both public data (such as TED data) and private data (such as that in the healthcare domain), with the future perspective of using these novel knowledge driven data analysis tools as diagnostic and guidance tools for domain experts and end users.'