Toward Open Science in the AEC Community: An Ecosystem for Sustainable Digital Knowledge Sharing and Reuse
Ruoxin Xiong, Yanyu Wang, Jiannan Cai, Kaijian Liu, Yuansheng Zhu, Pingbo Tang, Nora El-Gohary, George Edward Gibson Jr

TL;DR
This paper presents OpenConstruction, an open-science ecosystem for the AEC industry that aggregates and organizes digital resources to enhance discoverability, reuse, and collaboration across the built environment lifecycle.
Contribution
It introduces a structured, community-driven platform with validation and governance to facilitate sustainable digital knowledge sharing in the AEC sector.
Findings
Hosts 94 datasets and 65 models as of December 2025
Supports benchmarking, curriculum development, and open-science adoption
Demonstrated through two case studies
Abstract
The Architecture, Engineering, and Construction (AEC) industry is undergoing rapid digital transformation, producing diverse digital assets such as datasets, computational models, use cases, and educational materials across the built environment lifecycle. However, these resources are often fragmented across repositories and inconsistently documented, limiting their discoverability, interpretability, and reuse in research, education, and practice. This study introduces OpenConstruction, a community-driven open-science ecosystem that aggregates, organizes, and contextualizes openly accessible AEC digital resources. The ecosystem is structured into four catalogs, including datasets, models, use cases, and educational resources, supported by consistent descriptors, curator-led validation, and transparent governance. As of December 2025, the platform hosts 94 datasets, 65 models, and a…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsBIM and Construction Integration · Research Data Management Practices · Scientific Computing and Data Management
