Semi-automated model matching using version difference

Authors:
Hongjun Wang;Burcu Akinci;James H. Garrett, Jr.;Eric Nyberg;Kent A. Reed
Affiliations:
ANSYS, Inc., 275 Technology Dr., Canonsburg, PA 15317, USA;Department of Civil and Environmental Engineering, Carnegie Mellon University, USA;Department of Civil and Environmental Engineering, Carnegie Mellon University, USA;Language Technologies Institute, School of Computer Science, Carnegie Mellon University, USA;National Institute of Standard and Technology, USA
Venue:
Advanced Engineering Informatics
Year:
2009

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Abstract

Interoperability of software is a critical requirement in the architecture, engineering, and construction (AEC) industry, where a number of data exchange standards have been created to enable data exchange among different software packages. To be able to comply with existing data exchange standards, the software developers need to match their internal data schemas to the schema defined in a standard and vice versa. The process of matching two large scale data models is time consuming and cumbersome when performed manually, and becomes even more challenging when a source and/or a target model is being updated frequently to meet the ever expanding real world requirements. While several prior studies discussed the need for approaches toward automated or semi-automated schema matching, an approach that builds on existing matches between two models has rarely been studied. In this paper, we present a semi-automated approach for model matching. This approach leverages a given set of existing matching between two models and upgrades those matching when a new version of a target model is released. The paper describes in detail a list of upgrade patterns generated and validated through a prototype by matching a domain-specific data model to several recent releases of the industry foundation classes.