Double-layered schema integration of heterogeneous XML sources

  • Authors:

  • Hong-Quang Nguyen;David Taniar;J. Wenny Rahayu;Kinh Nguyen

  • Affiliations:

  • Dept. of Computer Science and Computer Engineering, La Trobe University, VIC 3086, Australia;Clayton School of Information Technology, Monash University, Clayton, VIC 3800, Australia;Dept. of Computer Science and Computer Engineering, La Trobe University, VIC 3086, Australia;Dept. of Computer Science and Computer Engineering, La Trobe University, VIC 3086, Australia

  • Venue:
  • Journal of Systems and Software
  • Year:
  • 2011

Quantified Score

Hi-index 0.00

Visualization

Abstract

Schema integration aims to create a mediated schema as a unified representation of existing heterogeneous sources sharing a common application domain. These sources have been increasingly written in XML due to its versatility and expressive power. Unfortunately, these sources often use different elements and structures to express the same concepts and relations, thus causing substantial semantic and structural conflicts. Such a challenge impedes the creation of high-quality mediated schemas and has not been adequately addressed by existing integration methods. In this paper, we propose a novel method, named XINTOR, for automating the integration of heterogeneous schemas. Given a set of XML sources and a set of correspondences between the source schemas, our method aims to create a complete and minimal mediated schema: it completely captures all of the concepts and relations in the sources without duplication, provided that the concepts do not overlap. Our contributions are fourfold. First, we resolve structural conflicts inherent in the source schemas. Second, we introduce a new statistics-based measure, called path cohesion, for selecting concepts and relations to be a part of the mediated schema. The path cohesion is statistically computed based on multiple path quality dimensions such as average path length and path frequency. Third, we resolve semantic conflicts by augmenting the semantics of similar concepts with context-dependent information. Finally, we propose a novel double-layered mediated schema to retain a wider range of concepts and relations than existing mediated schemas, which are at best either complete or minimal, but not both. Performed on both real and synthetic datasets, our experimental results show that XINTOR outperforms existing methods with respect to (i) the mediated-schema quality using precision, recall, F-measure, and schema minimality; and (ii) the execution performance based on execution time and scale-up performance.