A big data analytics framework for border crossing transportation. (2017)

• Record Type: Journal Article
• Authors: Wang, Haibo; Huo, Da; Xu, Yaquan
• Is Part Of: International journal of big data intelligence. Volume 4:Number 4(2017)
• Page Start: 227
• Page End: 236
• Publication Date: 2017
• Subjects: big data analytics -- border crossing transportation -- difference-in-difference estimation; Big data -- Periodicals; 005.705
• Languages: English
• ISSNs: 2053-1389

Abstract

In this paper, the authors present a framework on developing a comprehensive system to analyse border crossing transportation using an open-source meta-data acquisition and aggregation tool. It is a platform integration approach based on Hadoop, MapReduce and MongoDB to consolidate databases from both the USA and Mexico. We design data-driven XML schema for tagging the data entries from different sources with different formats, and implement a package using open-source software R to aggregate XML-transformed data into time and space dimensions. Then the transformed data is analysed by a difference-in-difference (DiD) estimation model to understand the behaviour of border crossing transportation.