Evaluating and predicting design performance
Evaluating and predicting design performance
Toward principles for the design of ontologies used for knowledge sharing
International Journal of Human-Computer Studies - Special issue: the role of formal ontology in the information technology
Introduction to ISO 10303—the STEP standard for product data exchange
Journal of Computing and Information Science in Engineering
Building Product Models: Computer Environments Supporting Design and Construction
Building Product Models: Computer Environments Supporting Design and Construction
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Ontologies: How can They be Built?
Knowledge and Information Systems
Architecture's New Media: Principles, Theories, and Methods of Computer-Aided Design
Architecture's New Media: Principles, Theories, and Methods of Computer-Aided Design
Eliciting information for product modeling using process modeling
Data & Knowledge Engineering
Computer integrated construction: A review and proposals for future direction
Advances in Engineering Software
An intelligent method for selecting optimal materials and its application
Advanced Engineering Informatics
Semantic interoperability in building design: Methods and tools
Computer-Aided Design
BIM Handbook: A Guide to Building Information Modeling for Owners, Managers, Designers, Engineers and Contractors
Algorithms for fuzzy multi expert multi criteria decision making (ME-MCDM)
Knowledge-Based Systems
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Fostering collaboration in the AEC (Architecture/Engineering/Construction) field is difficult, due to the differing educational and disciplinary backgrounds of the participants. Current approaches to managing such collaboration in the AEC industry often fail to overcome the disciplinary differences among the participants, resulting in cost overruns, missed schedules, and diminished satisfaction of the clients or society. Their failure is due to the lack of understanding of the nature of multi-disciplinary design and the lack of tools that can support them. The primary objective of this research is to establish a suitable model for machine-mediated collaboration. In contrast to the monolithic model, which is insensitive to changes, we propose to develop a distributed and flexible model, where each domain of expertise retains its own data in the form most appropriate for its needs, and where ontology-based, intelligent filters translate neutral design data into domain-specific ones. The filtered data appear semantically-rich to the participant, even when it was generated by another participant. To verify the feasibility of the proposed filter-based communication model, we developed and tested a prototype. The result of the prototype test demonstrates that the proposed model can enable designers from different disciplines participating in an AEC project to better understand the dynamic process of design and achieve a high level of shared understanding.