Salhab, D; Pourrahimian, E and Hamzeh, F (2026) Integrating ontologies and AI for enhanced workspace planning and knowledge management. Journal of Construction Engineering and Management, 152(4): 04026031, ISSN 0733-9364
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.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | artificial intelligence; semantic ontologies; spatiotemporal; tacit knowledge; workspace planning |
| Index terms: | productivity, workspace, emerging technology, dynamics, automation, project delivery, artificial intelligence, interview, design science research, user interface, strategy, qualitative method, ontology, integration, evolution, decision-making, methodology, practitioner, tacit knowledge, workflow, construction sector, data-driven decision-making, knowledge management |
| Subjects: | data collection methods, research design and methodology, artificial intelligence, project delivery, management, education and knowledge transfer, design practice, professional development, organizational analysis, decision analysis, industry analysis, systems engineering, practitioner, innovation and technology management, environmental science, research methods, automation and robotics, human-computer interaction |
| Topics: | Risk Management, Sustainability, Procurement, Engineering Principles, Organizational Design, Digital Applications, Design Practice, Roles and Professions, Stakeholder Management, Business Strategy, Information Management, Research Practice |
| Descriptive scope: | 5 PCTEA |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here