Developed a foundational data provisioning capability for transportation network analysis within the DataScience-ArtificialIntelligence/OOPsJava repository, focusing on integrating the Chicago.tntp dataset. Leveraging Java and object-oriented programming principles, the work involved organizing and uploading a large-scale transportation network dataset to support immediate analysis and simulation workflows. This addition established a reproducible and accessible data source for downstream modeling, enabling faster experimentation and validation of analytical models. The approach emphasized maintainable data management and ensured that the dataset was readily available for future analytics tasks, enhancing the project’s ability to support transportation network research and simulation using robust data engineering practices.