Dissertations, Theses, and Capstone Projects
Date of Degree
6-2023
Document Type
Capstone Project
Degree Name
M.S.
Program
Data Analysis & Visualization
Advisor
Michelle A. McSweeney
Subject Categories
Business Analytics | Business Intelligence | Data Science | Digital Humanities
Keywords
Shooting, Data Feminism, Open Data, Data, Critique, NYC
Abstract
This capstone is a website designed to critique NYC Open Data reporting with respect to shootings through a series of visualizations and discoveries. The NYPD Shooting Incidents datasets (Historic and Year to Date) introduce themselves to the user by claiming to be a “list of every shooting incident that occurred in NYC.” The supplied documentation reveals that this is not the case.
After understanding the supporting materials, there are still undisclosed truths. My exploration of the data revealed that a single victim may be represented across multiple entries. Additionally, multiple victims may be represented by a single entry. It is impossible to determine if the relationship between records and individuals is one-to-one, one-to-many, many-to-one, or many-to-many. As such, any analysis of this dataset which counts people should be avoided. These truths are not available in any of the documentation. The findings are presented in this project.
Recommended Citation
Ambris, Allan, "Phantom Shootings" (2023). CUNY Academic Works.
https://academicworks.cuny.edu/gc_etds/5410
Zip file of GitHub repository used
DashboardScreenshots.pdf (324 kB)
Screenshots of Tableau dashboard
Included in
Business Analytics Commons, Business Intelligence Commons, Data Science Commons, Digital Humanities Commons
Comments
Online component: https://numbersequence.github.io/PhantomShootings/