Challenges of Big Data in the Age of Building Information Modeling: A High-Level Conceptual Pipeline http://link.springer.com/chapter/10.1007%2F978-3-319-24132-6_6
N-dimensional BIM models integrate many aspects of Architecture, Engineering and Construction (AEC) projects information. These models are well structured and allow users to practically query them, however they are more and more combined with other data sources, provided e.g. by Geographic Information Systems (GIS), Building Automation Systems (BAS) or Facility Management (FM) systems. Construction project managers are facing an important challenge related to making meaningful deduction from these heterogeneous data sets. In this context the current data mining approaches are showing their limitations. Big Data is then gradually getting a reality in the construction industry. This paper characterizes AEC project management data following the conceptual definition of Big Data and proposes a high-level conceptual pipeline aiming at bridging the gap between BIM-based related visualization works and information visualization domain.
BIM, Big data, Information visualization, Information pipeline, Architecture, Engineering and construction