Group02 Report

Overview	Proposal	Poster	Application	Report

Introduction

Environmental criminology focuses on the relations between crime (including aspects such as victim characteristics and criminality) and spatial and behavioural factors. As crime data becomes increasingly available to the public, geo-spatial and temporal analysis of crime occurrence matures to provide better insights. This increased understanding will potentially contribute to enhanced law enforcement efforts and even urban management.

In our research, we take a step in this direction by examining how geographic and date-time variables interact with other variables to better understand crime occurrences in the city of Los Angeles (LA). Crime data coupled with population by zip code were obtained from the LA city official data repository for analysis and visualization. The research culminates in an interactive application built on R Shiny that allows a casual user to explore, analyse and model data to derive insights. R is used as the tool of choice in creating the web application due to its rich library of packages for statistical analysis and data visualization. With the data visualizations and intuitive user interface in this application, the user can easily filter and transform crime data to derive the insights he or she requires. R’s status as a free software environment for statistical computing and graphics allows for availability for use by many, which would further encourage the spread of such visual analytics initiatives across more fields.

This paper provides information on our analytical development efforts for the application and consists of 8 sections. The introduction is followed by the motivation and objectives of this research. Section 3 provides a review on previous works in the field. Section 4 describes the dataset and its preparation for modelling. Section 5 describes the design framework as well as visualization methodologies whereas section 6 provides insights we have derived in the process of the development of the application. Future works are stated in section 7 and finally, an installation and user guide in section 8.

Motivation and Objectives

Governmental agencies in Singapore such as data.gov and Ministry of Home Affairs provide crime data reports on a bi-annual and annual basis that displays trend for instance by crime type and across year. Even so, these data only provide an overview of crimes and there is no information on crime details (e.g. location, time), victim profiles and possible associations between the different crime variables. Our research aims to incorporate geo-spatial and temporal analytics for better insights on crime occurrence modelled using the rich data of crime occurrences in Los Angeles that may be replicated with increased availability of similar data in Singapore.
This research aims to:
(a) Create a user-friendly and interactive visualization platform for data exploration that supports both macro and micro views that can be potentially used by members of the public and law enforcement agencies alike
(b) Provide statistical analysis on crime occurrences with data on population and location spatial area
(c) Build a predictive model of crime occurrence based on geo-spatial temporal data, crime details and victim profiles