Date of Award

Summer 2022

Document Type


Degree Name

Doctor of Philosophy (PhD)


Civil, Construction, and Environmental Engineering

First Advisor

Karshenas, Saeed

Second Advisor

Bai, Yong

Third Advisor

Ahamed, Sheikh Iqbal


A multi-sectoral collaboration completes a successful transportation infrastructure project. The cooperation involves designers, contractors, operators, users, government agencies, and maintenance staffs. Throughout the project's life cycle, a huge amount of data is generated and stored in various sectors. Therefore, an efficient information cross-sector exchange approach is necessary. Additionally, the World Wide Web is ubiquitous and enmeshed with multiple business processes. Therefore, it is imperative to represent business information in a format that improves information exchange as well as automated processing of business data. Ideally, road data scattered across different information sources, such as design software, geographic information systems (GIS), cost estimating software, and maintenance and repair databases can be shared across the Internet. However, the reality is the information in each transportation sector is created and updated separately. Moreover, the project's data is stored in various formats, such as text document, pdf, XML, and relational database. Different systems, file formats, technologies, and semantics hinder the smooth data exchange and systems interoperability throughout the road project's lifecycle (van Nederveen et al. 2015). Therefore, a new data modeling approach is required to facilitate automatic data integration.This dissertation proposes a novel approach to road infrastructure projects using the Semantic Web technology. The SW technology provides a modeling framework for representing various road data sources, such as design documents and GIS. A vocabulary is developed in this study to represent all the information involved in the modeling framework. The data structured by SW technology creates a knowledge base. This knowledge base can take advantage of machine processing, facilitate interoperability among distributed systems, and allow domain users to loosely and on-demand integrate several geographically, organizationally, or temporally distributed sources of information. This extendable data model enables domain engineers to complete a domain knowledge base and keep it up to date through the project's lifecycle independently for each road-related domain. This study focuses on streamlining the integration of distributed road infrastructure information provided by road designers, estimators, schedulers, and GIS. The information stored in knowledge bases can be queried with Simple Protocol and Resource Description Framework Query Language (SPARQL) endpoints or semantic web services

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