## 7 Conclusions  
Construction projects generate vast amounts of data. For the data to be useful, it must be relevant, accurate, and organized into data sets that are large enough to be processed into meaningful analysis. Construction practitioners, therefore, require a consistent integrated data acquisition model to collect detailed data from different dimensions across multiple projects. The proposed Construction Data Hub (CDH) integrates the four main structures of any construction project: organization breakdown structures (OBSs), product breakdown structures (PBSs), resource breakdown structures (RBSs), and work breakdown structures (WBSs). The CDH also collects data related to twelve dimensions that impact the project's planning and control, and focuses on the work package as a connector between the four breakdown structures and a knowledge carrier across an organization's different projects. To enhance the traditional work package, the authors have introduced the multi-dimensional work package (MDWP), which includes new dimensions of data. Since construction organizations have different work-level definitions, a generic model is required to collect detailed data at a specific level, regardless of a particular organization's terminology. Defining standard levels, phases, and subphases is crucial to capturing meaningful metadata from various projects and organizations. Academic studies on construction planning often face difficulties during the data collection process, which researchers consider a critical step that directly impacts the accuracy of their models. The CDH contributes to academia by supporting a structured and comprehensive data warehouse that serves as a central data facility for various stakeholders to retrieve the right data for making sustainable decisions. Furthermore, the data warehouse contains high-quality data from several dimensions that can be utilized to perform detailed analyses, offering valuable insights and as resources for future studies, such as mathematical models for forecasting and optimization. This research also addresses a gap in the industry by utilizing details at the work package level, which is more efficient than the current industry practice. The CDH is a practical tool since it uses the data generated during the execution of the project and is kept updated during the progress of the project. The aim of collecting details from the four structures at the work package level is to provide project managers with a dynamic tool that can obtain insights about a specific element such as a project, program, resource, equipment, or construction work package (as a product), through rolling-up, drilling-down and slice and dice techniques using the group and sort option. Also, it can be utilized for forecasting work package requirements, such as durations, costs, and GHG emissions for future projects. Future research will explore the integration of BIM to automate data collection at the work package level. For instance, linking the CDH to BIM could enable real-time extraction of geometric, schedule, and cost data while enhancing the CDH with non-geometric attributes such as labor hours and embodied carbon. Additionally, the model's accuracy will be re-evaluated using work package-level data sets that capture finer-grained metrics (e.g., schedule, budgets, resources such as labor, materials, and equipment, and productivity rates per WP). Collaborations with industry partners are underway to access such data, addressing the current limitation of project-level aggregation. Conceptualization, M.G. and A.H.; Methodology, M.G. and A.H.; Software, M.G. ; Validation, M.G. and A.H.; Formal analysis, M.G. and A.H.; Investigation, M.G. ; Resources, M.G. ; Data curation, M.G. ; Writing--original draft, M.G. ; Writing--review & editing, M.G. and A.H.; Visualization, M.G. and A.H.; Supervision, A.H. All authors have read and agreed to the published version of the manuscript. This research was funded by the Natural Sciences and Engineering Research Council of Canada grant number ALLRP 577032-2022.