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Collaborative Schema Matching Reconciliation

  • Hung Quoc Viet Nguyen
  • Xuan Hoai Luong
  • Zoltán Miklós
  • Tho Thanh Quan
  • Karl Aberer
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8185)

Abstract

Schema matching is the process of establishing correspondences between the attributes of database schemas for data integration purpose. Although several schema matching tools have been developed, their results are often incomplete or erroneous. To obtain correct attribute correspondences, in practice, human experts edit the mapping results and fix the mapping problems. As the scale and complexity of data integration tasks have increased dramatically in recent years, the reconciliation phase becomes more and more a bottleneck. Moreover, one often needs to establish the correspondences in not only between two but a network of schemas simultaneously. In such reconciliation settings, it is desirable to involve several experts. In this paper, we propose a tool that supports a group of experts to collaboratively reconcile a set of matched correspondences. The experts might have conflicting views whether a given correspondence is correct or not. As one expects global consistency conditions in the network, the conflict resolution might require discussion and negotiation among the experts to resolve such disagreements. We have developed techniques and a tool that allow approaching this reconciliation phase in a systematic way. We represent the expert’s views as arguments to enable formal reasoning on the assertions of the experts. We detect complex dependencies in their arguments, guide and present them the possible consequences of their decisions. These techniques thus can greatly help them to overlook the complex cases and work more effectively.

Keywords

Integrity Constraint Schema Match Argumentation Framework Attack Relation Multiple Expert 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Hung Quoc Viet Nguyen
    • 1
  • Xuan Hoai Luong
    • 1
  • Zoltán Miklós
    • 2
  • Tho Thanh Quan
    • 3
  • Karl Aberer
    • 1
  1. 1.École Polytechnique Fédérale de LausanneSwitzerland
  2. 2.Université de Rennes 1France
  3. 3.Ho Chi Minh City University of TechnologyVietnam

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