Structural Graph-based Metamodel Matching

Date

Nov 2, 2011

Time

9:00 AM - 10:00 AM

Speaker

Dipl.-Inf. Konrad Voigt

Affiliation

Institut für Software- und Multimediatechnik, Lehrstuhl für Softwaretechnologie

Language

en

Main Topic

Informatik

Other Topics

Informatik

Description

Across the domains of schemas, ontologies, and metamodels, the integration of heterogeneous data imposes the need for mapping specifications, i.e. the task of discovering semantic correspondences between elements. Support for the development of such mappings has been researched, producing matching systems that automatically propose mapping suggestions. However, especially in the context of metamodel matching the result quality of state of the art matching techniques leaves room for improvement. Although the traditional approach of pair-wise element comparison works on smaller data sets, its quadratic complexity leads to poor runtime and memory performance and eventually to the inability to match, when applied on real-world data. The work presented in this thesis takes advantage of the graph structure of metamodels. We derive a planar graph edit distance and mining-based matching as metamodel similarity metrics as well as a planar graph-based partitioning to cope with large-scale matching. These techniques are then evaluated using real-world mappings to demonstrate improvements in quality and support for large-scale metamodel matching.

Last modified: Nov 2, 2011, 8:36:45 AM