Date of Award
2-7-2020
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Information Science
First Advisor
Daniel Berleant
Abstract
There exists a mostly unexplored ‘big data’ dataset comprising of chemical hazard and safety codes. The purpose of this research is to apply a data science methodology to the problem of exploring this data. The data was run through extract-transform-load protocols, and then through data mining algorithms. The results are described and discussed. More work could be done on the subject, but this paper starts the process.
Recommended Citation
Bomer, Devlon, "Using a Data Science Driven Approach to Analyzing Chemistry Hazard Code Data" (2020). Theses and Dissertations. 919.
https://research.ualr.edu/etd/919
