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https://hdl.handle.net/2142/128671
Description
Title
Mapping maintenance for data management
Author(s)
Al-Shebli, Bedoor Kh.
Issue Date
2005
Director of Research (if dissertation) or Advisor (if thesis)
Kelley, Mary Beth
Department of Study
Computer Science
Degree Granting Institution
University of Illinois at Urbana-Champaign
Degree Name
M.S. (master's)
Degree Level
Thesis
Date of Ingest
2025-06-04T11:11:02-05:00
Keyword(s)
Computer science
Data management
Language
eng
Abstract
Despite the potential of data integration systems, their deployment in practice is still quite limited. Building such a system is an expensive endeavor, for which numerous semiautomatic
tools have been developed. Once the system has been built and deployed, an equally daunting challenge is to maintain it over time. In dynamic environments (such as the Web), sources often autonomously change without regard for the system, resulting in
the need to continually monitor, detect, and repair broken components.
One particularly susceptible component is the set of semantic mappings between the
global schema and the schemas of data sources. In this thesis, MAVERIC, an automatic mapping verification system is presented. MAVERIC periodically probes a data integration system, and alerts the system administrator if a mapping has become broken. The
core architecture of MAVERIC: a collection of inexpensive sensors that are trained and deployed
to verify the mappings is described. Then three novel improvements are developed - perturbation and multi-source training to make the verification system more robust,
and filtering to reduce the number of false alarms. We present extensive experiments over
111 real-world sources in six domains. The results demonstrate the effectiveness of our
core approach over existing solutions, as well as the utility of our improvements.
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