Identify Best Types of Commodity Flow Data for Freight, Railroad, Ports and Waterways Studies

Principal Investigator(s):

Camila Fonseca Sarmiento, Director of Fiscal Research, Humphrey School of Public Affairs


  • Lee Munnich, Senior Fellow (Retired), Humphrey School of Public Affairs

Project summary:

Having recent, relevant, accessible, and easily updated freight data across various modes is important to prioritize transportation investments, develop transport policy, and attract new businesses while enabling existing ones to grow. Current datasets are limited in their ability to demonstrate supply chain patterns or lack commodity and spatial details and are expensive. This data deficiency severely limits the ability of policymakers to properly plan for and leverage freight movement for economic purposes. The continued strength of industry clusters in Minnesota depends on the state's ability to understand the movement of these goods in and out of the state. This project aims to analyze various types of databases and to determine which of them are the most helpful for planning, programming, and design of future infrastructure on the truck freight, railroad, and ports and waterways networks within Minnesota and surrounding states. Researchers will also assess and recommend methodologies for the generation and collection of freight data, freight trip generation, and service trips within the context of MnDOT's freight studies.

Project details: