BoaT: A Domain Specific Language and Shared Data Science Infrastructure for Large Scale Transportation Data Analysis
General Material Designation
[Thesis]
First Statement of Responsibility
Islam, Johirul
Subsequent Statement of Responsibility
Rajan, Hridesh
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
Iowa State University
Date of Publication, Distribution, etc.
2019
GENERAL NOTES
Text of Note
35 p.
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
M.S.
Body granting the degree
Iowa State University
Text preceding or following the note
2019
SUMMARY OR ABSTRACT
Text of Note
Big data-driven transportation engineering has the potential to improve utilization of road infrastructure, decrease traffic fatalities, improve fuel consumption, and decrease construction worker injuries, among others. Despite these benefits, research on big data-driven transportation engineering is difficult today due to the computational expertise required to get started. This thesis proposes BoaT , a transportation-specific programming language, and its big data infrastructure that is aimed at decreasing this barrier to entry. Our evaluation, that uses over two dozen research questions from six categories, shows that research questions are easier to realize as BoaT computer programs, an order of magnitude faster when these programs are run, and exhibit 12-14x decrease in storage requirements.