Dataset of characterised construction safety risks and related treatments

Osorio-Sandoval, Carlos A.; Crick, Gordon; Collinge, William H.; Farghaly, Karim; Mosleh, Mojgan Hadi; Manu, Patrick; Cheung, Clara Man

Abstract

The Safety Risk Library is a structured database that integrates knowledge drawn from multiple sources to address the problem of information disaggregation in the construction industry. This knowledge base maps construction safety risk scenarios to treatment suggestions that help designers implement the concept of prevention through design. In the context of the Safety Risk Library, risk scenarios are characterised by six data categories based on a formalised ontology [3]. To build the first iteration of the Safety Risk Library, nine different risk scenarios were identified and mapped to relevant risk treatments in focus groups. Subsequently, the Safety Risk Library was pilot tested in six construction projects, and user feedback and input were used to expand the list of risk scenarios and treatment prompts. Additionally, public press releases reporting construction accidents were analysed to identify and characterise risk scenarios, which were then mapped to appropriate treatment suggestions and included in the Safety Risk Library. This dataset can assist construction industry stakeholders in identifying, characterising, communicating and mitigating safety risks in construction projects. It can also be integrated into building information modelling environments to assist designers to implement prevention through design.

Citation

Osorio-Sandoval, C. A., Crick, G., Collinge, W. H., Farghaly, K., Mosleh, M. H., Manu, P., & Cheung, C. M. (2023). Dataset of characterised construction safety risks and related treatments. Data in Brief, 48, Article 109293. https://doi.org/10.1016/j.dib.2023.109293

• Journal Article Type: Article
• Acceptance Date: May 30, 2023
• Online Publication Date: Jun 4, 2023
• Publication Date: 2023-06
• Deposit Date: Jun 12, 2023
• Publicly Available Date: Jun 12, 2023
• Journal: Data in Brief
• Electronic ISSN: 2352-3409
• Publisher: Elsevier BV
• Peer Reviewed: Peer Reviewed
• Volume: 48
• Article Number: 109293
• DOI: https://doi.org/10.1016/j.dib.2023.109293
• Keywords: Design for safety; Prevention through design; Risk scenarios; Building information modelling
• Public URL: https://nottingham-repository.worktribe.com/output/21646276
• Publisher URL: https://www.sciencedirect.com/science/article/pii/S2352340923004122?via%3Dihub