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Pay-as-you-go Data Integration: Experiences and Recurring Themes

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Date
2016
Notes
Lecture Notes in Computer Science, Vol. 9587
Dewey
Informatique générale
Sujet
data integration
DOI
http://dx.doi.org/10.1007/978-3-662-49192-8_7
Conference name
42nd International Conference on Current Trends in Theory and Practice of Computer Science
Conference date
01-2016
Conference city
Harrachov
Conference country
Czech Republic
Book title
SOFSEM 2016: Theory and Practice of Computer Science
Author
Freivalds, Rūsiņš Mārtiņš; Engels, Gregor; Catania, Barbara
Publisher
Springer
Publisher city
Berlin Heidelberg
Year
01-2016
Pages number
630
ISBN
978-3-662-49191-1
Book URL
10.1007/978-3-662-49192-8
URI
https://basepub.dauphine.fr/handle/123456789/16228
Collections
  • LAMSADE : Publications
Metadata
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Author
Paton, Norman W.
90659 School of Computer Science [Manchester]
Belhajjame, Khalid
989 Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Embury, Suzanne
90659 School of Computer Science [Manchester]
Fernandes, Alvaro A. A.
90659 School of Computer Science [Manchester]
Maskat, Ruhaila
90659 School of Computer Science [Manchester]
Type
Communication / Conférence
Item number of pages
81-92
Abstract (EN)
Data integration typically seeks to provide the illusion that data from multiple distributed sources comes from a single, well managed source. Providing this illusion in practice tends to involve the design of a global schema that captures the users data requirements, followed by manual (with tool support) construction of mappings between sources and the global schema. This overall approach can provide high quality integrations but at high cost, and tends to be unsuitable for areas with large numbers of rapidly changing sources, where users may be willing to cope with a less than perfect integration. Pay-as-you-go data integration has been proposed to overcome the need for costly manual data integration. Pay-as-you-go data integration tends to involve two steps. Initialisation: automatic creation of mappings (generally of poor quality) between sources. Improvement: the obtaining of feedback on some aspect of the integration, and the application of this feedback to revise the integration. There has been considerable research in this area over a ten year period. This paper reviews some experiences with pay-as-you-go data integration, providing a framework that can be used to compare or develop pay-as-you-go data integration techniques.

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