01555233

Component

With the recognized importance of freight planning on a nation’s economy, accurate, complete, and reliable data is needed to make effective policy decisions and adequately assess the current freight system. Identifying current freight data gaps is an essential step in determining the needed improvements for and limitations of current freight data sources. Current methods rely on focus groups and conferences to identify gaps through the attendees’ familiarity with a particular data source based on their level of experience. While effective, such strategies may be limited by the practitioners’ knowledge of all available data sources. A formal classification of freight data gaps is presented in this paper to better identify and address those gaps that often hinder researchers and policy-makers in making sound decisions. The proposed classification is then validated using a freight data ontology developed for querying multiple freight data sources using a common query statement. Seven publicly available databases were selected for demonstration of the proposed data gap identification approach. The result is a well-structured tool for identifying freight data gaps based on user queries and the different types of gaps. With such improvements in data gap identification, agencies can better focus their data collection efforts to adequately address currently existing data gaps.

This paper was sponsored by TRB committee ABJ90 Freight Transportation Data.

01550057

15-2183

English

19p

2015

Transportation Research Board 94th Annual Meeting

Digital/other

Figures; References; Tables

Classification; Data analysis; Data collection; Freight traffic measurement

Gap analysis

Data and Information Technology; Freight Transportation; Planning and Forecasting; I72: Traffic and Transport Planning

Transportation Research Board Annual Meeting 2015 Paper #15-2183

TRIS, TRB, ATRI

Dec 30 2014 12:46PM