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Integrating Ontologies and AI for Enhanced Workspace Planning and Knowledge Management

Diana Salhab et al.

Journal of Construction Engineering and Management2026https://doi.org/10.1061/jcemd4.coeng-17000article
AJG 2ABDC A*
Weight
0.50

Abstract

The evolution of industries requires the integration of knowledge and innovation to drive productivity. Accordingly, the construction sector must adapt by embracing emerging technologies and data-driven decision-making. In this context, strategic workspace planning, a crucial factor in workflow optimization, remains under-researched in its impact on project delivery. Therefore, this paper introduces a novel framework that integrates semantic ontologies and artificial intelligence (AI) to enhance workspace planning. Using a design science research (DSR) methodology, it employs quantitative and qualitative methods, including developing ontologies, creating a graphical user interface (GUI), and conducting an interview with an industry professional. The framework captures both explicit and tacit knowledge within a workspace-related ontology, which offers a deeper understanding of workspace dynamics. A GPT-powered AI bot for spatiotemporal analysis is included to provide predictions and optimization strategies. Feedback from practitioners ensures the ontology and AI reflect real-world construction scenarios, demonstrating the framework’s practical potential to improve workspace planning. The framework automates decision-making in workspace planning and provides a structured approach to addressing complex spatial and temporal challenges in projects, which advances the current automation capabilities in the field.

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https://doi.org/https://doi.org/10.1061/jcemd4.coeng-17000

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@article{diana2026,
  title        = {{Integrating Ontologies and AI for Enhanced Workspace Planning and Knowledge Management}},
  author       = {Diana Salhab et al.},
  journal      = {Journal of Construction Engineering and Management},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1061/jcemd4.coeng-17000},
}

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Integrating Ontologies and AI for Enhanced Workspace Planning and Knowledge Management

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.