American Society of Civil Engineers

Domain Ontology for Processes in Infrastructure and Construction

by Nora M. El-Gohary, (corresponding author), A.M.ASCE, (Assistant Professor, Dept. of Civil and Environmental Engineering, Univ. of Illinois at Urbana-Champaign, Newmark Civil Engineering Lab, 205 N. Mathews Ave., Urbana, IL 61801 E-mail: and Tamer E. El-Diraby, (Associate Professor and Director, Dept. of Civil Engineering, Center for Information Systems in Infrastructure and Construction, Univ. of Toronto, 35 St. George St., Toronto, ON, Canada M5S 1A4. E-mail:

Journal of Construction Engineering and Management, Vol. 136, No. 7, July 2010, pp. 730-744, (doi:

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Document type: Journal Paper
Section Heading: Information Technologies
Abstract: With the increasing demands for domain-wide integrated construction and infrastructure development, there is a need for developing a domain ontology to build a knowledge model that describes the multistakeholder project development process. This paper presents a domain ontology for supporting knowledge-enabled process management and coordination across various stakeholders, disciplines, and projects. The ontological model is composed of concepts, relations, and axioms. Concepts represent the "things" in the domain of interest; relations establish the interconcept links; and axioms specify the definitions of concepts and relations and constraints on their behavior and interpretation. The ontology models the most fundamental concepts in the domain in a structured, extendable, and flexible format to facilitate future evolution and extension of the ontology for representing application-specific and/or enterprise-specific knowledge. The ontology was evaluated through technical evaluation and user evaluation. User evaluation was conducted through one-to-one expert evaluation interviews.

ASCE Subject Headings:
Project management
Construction industry
Information management
Knowledge-based systems

Author Keywords:
Project development
Construction industry
Process modeling
Information and knowledge management
Knowledge-based computer models