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The coordination of the information flows within and across companies participating in a supply chain is vital to any product development projects. To support meaningful information sharing, software applications must be able to convey and understand the semantics among each other. Current developments of interoperability standards, although they do provide the means of communication among the tools within a narrowly defined domain, do not resolve the complex interoperability issues in a supply chain, which typically involves information and service integration across multiple disciplines. This research project aims to address this fundamental problem by developing
1) a formal methodology to resolve the semantic similarities and differences among the standards, thus allowing meaningful data exchange across disciplines; and
2) a framework to support coordination and integration of distributed engineering services.
Semantic Similarities and Differences Coordination and Integration of Services
Project Summary
The AEC supply chain is fragmented in the same way as most information management processes in the industry are. As the current practice indicates, having information available as needed can significantly reduce lead-time as well as increase accountability for tracking purpose. More...


Test Case
For various model rebuilding and data exchange purposes, comparison and mapping between heterogeneous ontologies in the same industry are often inevitable. A new approach to map OmniClass and IfcXML, two of the most commonly used data models for buildings and constructions has been demonstrated. More...


Future Plan
In the coming future, we hope to extend our research to:
  • Include more engineering workflows and applications;
  • Apply on a broader domain of ontologies;
  • Consider the reliability and user-friendiness of the distributed service coordination framework;
  • Handle the security issue of the information sharing network system.
Should you have any comments or suggestions, please contact Jack Cheng at cpcheng@stanford.edu.
All rights reserved. Engineering Informatics Group, Stanford University.