The Synthesize Data for Emerging Data Cleaning and Fusion Tool dataset is a privacy-preserving synthetic dataset developed to support and demonstrate the functionalities of the Emerging Data Cleaning and Fusion Tool. It replicates the general structure and statistical characteristics of real-world multimodal traffic data while ensuring that no sensitive or identifiable information is included. The dataset integrates multiple data sources, including TMC data, sensor data, waypoint data, trip path data, and probe OD data. It is designed to facilitate testing, validation, and demonstration of data cleaning, fusion, and calibration processes without relying on proprietary datasets. All data elements have been anonymized and perturbed through controlled noise-injection mechanisms to preserve analytical utility while maintaining strong privacy protection. This work is funded by the Federal Highway Administration (FHWA) under the project titled Emerging Data Cleaning and Fusion for Traffic Model Calibration, as part of ongoing efforts to promote the effective use of emerging data sources in transportation modeling and planning. This file contains timestamped lane-level volume and occupancy readings.