Abstract
This paper presents a framework for the semiautomated development of textual requirements for the building construction industry, a domain in which quality of textual requirements has a direct bearing on the avoidance of unnecessary project losses and failures. The proposed framework is novel in three respects. First, it employs a combination of natural language processing (NLP) and template matching to restrict the range of ways in which textual requirements can be stated. Second, knowledge-based models work hand-in-hand with the NLP and templates to help designers fill in the details of a model that might be missing. Third, we envision the proposed approach being part of a multidomain semantic modeling and reasoning framework that includes the building construction domain and its connections to processes for project management and governance. To demonstrate the potential of the proposed approach to the practical development and construction of building systems, we developed a prototype software tool—the framework for linking ontology objects and textual requirements (FLOOR)—and procedures for the validation of individual textual requirements and groups of textual requirements related to construction tasks.
Practical Applications
This paper presents a new methodology and a prototype software framework for the semiautomated development and validation of textual requirements for the building construction industry. The work is novel in three respects: (1) it combines a natural language processing tool with a sentence-and-template matching technique to limit the ways in which textual requirements can be stated; (2) it employs a multidomain semantic modeling and reasoning framework to provide coverage in the range of textual requirements that can be handled; and (3) it employs a multidomain semantic modeling and reasoning framework that can work with individual requirements and groups of textual requirements. During the early phases of project development, these three factors work together to improve the quality of textual requirements, which in turn leads to improved levels of communication in construction management and avoidance of unnecessary project delays and failures.
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Data Availability Statement
The data models and software code from this study are available from the corresponding author.
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Journal of Management in Engineering
Volume 38 • Issue 5 • September 2022
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© 2022 American Society of Civil Engineers.
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Received: Oct 29, 2021
Accepted: May 4, 2022
Published online: Jul 12, 2022
Published in print: Sep 1, 2022
Discussion open until: Dec 12, 2022
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