Pay-as-you-go Data Integration: Experiences and Recurring Themes
Paton, Norman W.; Belhajjame, Khalid; Embury, Suzanne; Fernandes, Alvaro A. A.; Maskat, Ruhaila (2016), Pay-as-you-go Data Integration: Experiences and Recurring Themes, in Freivalds, Rūsiņš Mārtiņš; Engels, Gregor; Catania, Barbara, SOFSEM 2016: Theory and Practice of Computer Science, Springer : Berlin Heidelberg, p. 81-92. 10.1007/978-3-662-49192-8_7
Type
Communication / ConférenceDate
2016Conference title
42nd International Conference on Current Trends in Theory and Practice of Computer ScienceConference date
2016-01Conference city
HarrachovConference country
Czech RepublicBook title
SOFSEM 2016: Theory and Practice of Computer ScienceBook author
Freivalds, Rūsiņš Mārtiņš; Engels, Gregor; Catania, BarbaraPublisher
Springer
Published in
Berlin Heidelberg
ISBN
978-3-662-49191-1
Number of pages
630Pages
81-92
Publication identifier
Metadata
Show full item recordAuthor(s)
Paton, Norman W.School of Computer Science [Manchester]
Belhajjame, Khalid
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Embury, Suzanne
School of Computer Science [Manchester]
Fernandes, Alvaro A. A.
School of Computer Science [Manchester]
Maskat, Ruhaila
School of Computer Science [Manchester]
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.Subjects / Keywords
data integrationRelated items
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