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View all- Sun QLiu YTian WGuo Y(2019)CF-PROV: A Content-rich and Fine-grained Scientific Workflow Provenance ModelIEEE Access10.1109/ACCESS.2019.2900738(1-1)Online publication date: 2019
Print: a provenance model to support integration processes
Authors: 
Bruno Tomazela, Carmem S. Hara, Ricardo R. Ciferri, Cristina D.A. CiferriAuthors Info & Claims
Bruno Tomazela, Carmem S. Hara, Ricardo R. Ciferri, Cristina D.A. CiferriAuthors Info & ClaimsPages 1349 - 1352
Abstract
In some integration applications, users are allowed to import data from heterogeneous sources, but are not allowed to update source data directly. Imported data may be inconsistent, and even when inconsistencies are detected and solved, these changes may not be propagated to the sources due to their update policies. Therefore, they continue to provide the same inconsistent data in the future until the proper authority updates them. In this paper, we propose PrInt, a model that supports user's decisions on cleaning data to be automatically reapplied in subsequent integration processes. By reproducing previous decisions, the user may focus only on new inconsistencies originated from source modified data. The reproducibility provided by PrInt is based on logging, and by incorporating data provenance in the integration process.
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- Print: a provenance model to support integration processes
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Information & Contributors
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Published In
October 2010
2036 pages
ISBN:9781450300995
DOI:10.1145/1871437
- General Chair:
- Jimmy Huang,
- Program Chairs:
- Nick Koudas,
- Gareth Jones,
- Xindong Wu,
- Kevyn Collins-Thompson,
- Aijun An
Copyright © 2010 ACM.
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Published: 26 October 2010
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CIKM '10: International Conference on Information and Knowledge Management
October 26 - 30, 2010
ON, Toronto, Canada
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View all- Sun QLiu YTian WGuo Y(2019)CF-PROV: A Content-rich and Fine-grained Scientific Workflow Provenance ModelIEEE Access10.1109/ACCESS.2019.2900738(1-1)Online publication date: 2019
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