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Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings' data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept. [ABSTRACT FROM AUTHOR]

Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept.