Dissertation/Thesis Abstract

Using a Data Science Driven Approach to Analyzing Chemistry Hazard Code Data
by Bomer, Devlon C., M.S., University of Arkansas at Little Rock, 2019, 36; 27548421
Abstract (Summary)

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.

Indexing (document details)
Advisor: Berleant, Daniel
Commitee: Belford, Robert, Bauer, Bruce L.
School: University of Arkansas at Little Rock
Department: Information Science
School Location: United States -- Arkansas
Source: MAI 81/7(E), Masters Abstracts International
Subjects: Information science
Keywords: Cheminformatics, Data, Database, GHS, Hazard, PubChem
Publication Number: 27548421
ISBN: 9781392372296
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