Ontology-Driven Project Management: A Framework for Structured Data and Automation

Abstract

Construction project management grapples with significant complexity and knowledge integration challenges, often hindering efficient decision-making. This paper presents an ontology-oriented programming paradigm designed to model construction projects, providing a semantically rich framework for capturing domain knowledge. The methodology centers on the development of a project management ontology mirroring Work Breakdown Structure (WBS) principles. This involves hierarchically organizing core concepts like Project, Task, Resource, and Deliverable. Key relationships governing task dependencies, hierarchical structures, resource assignments, along with essential task attributes including temporal constraints and cost information, are formally defined using OWL classes and properties. This conceptual ontology was implemented using the Owlready2 Python library, facilitating structured data representation and manipulation. The paper further explores the practical application of this ontology framework through five distinct use cases: enhanced progress monitoring, data-driven informed decision-making, integrated Building Information Modeling (BIM), automated compliance checking, and synergistic Artificial Intelligence (AI) integration. A supporting workflow is also proposed. This research highlights the potential of structured ontologies, realized via tools like Owlready2, to significantly improve knowledge representation, system interoperability, and overall decision support effectiveness within the demanding construction domain.