Abstract
In this paper, authors present a framework on developing a comprehensive system to analyze 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 U. S. 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 analyzed by a Difference-in-Difference (DiD) estimation model to understand the behavior of border crossing transportation.
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