Information and process modelling for IT implementation at the briefing stage

During the early stages of a construction project, clients often have difficulties in\ud identifying and communicating their actual requirements to designers or other project\ud participants. This is mainly due to their difficulty in comprehending the vast amount of\ud information involved. In order to effectively address this information during the briefing\ud process, this study has modelled such information into structured data models using\ud EXPRESS-G technique. These data models represent a framework for the presentation\ud of the client's brief, with the aim of establishing a computerised tool to assist both\ud clients and designers to carry out this process effectively.\ud The process of developing the brief is then modelled using IDEFO technique. A two step\ud process modelling has been undertaken. Firstly, in the form of an abstract\ud representation of the briefing operations deduced from literature review, and secondly,\ud within the context of the forthcoming prototype development. The latter considers two\ud viewpoints; system architecture of the prototype and the information to be elicited from\ud the user.\ud The developed models establish the foundation for the development of a prototype\ud which utilises an object oriented environment. The use of structured analysis techniques\ud for the modelling process entails the relevant constructs of the developed models to be\ud transformed into their equivalents in the object oriented environment. The implemented\ud object oriented data models, then form the framework for the textual presentation of the\ud client's brief. The resulting prototype is called AUTOBRIEF (AUTOmated BRIEF development). AUTOBRIEF is a prototype for the generation of the client's brief,\ud which provides access to project information prior to the brief generation.\ud The implementation of the prototype has been tested to reflect how effective it is in\ud support of the briefing process, using IT as a tool. At the end of the study, conclusions\ud are drawn and recommendations are made for future research.